Optimum beamforming subject to multiple linear constraints
Steele, A. K.
1980-09-01
Optimum beamformers with a single look direction constraint can suffer from signal suppression problems when the optimum weights are calculated from the inverse of the signal-plus-noise cross-spectral matrix. Signal suppression occurs when the beam steer direction does not exactly correspond to the signal direction and this can occur if the number of fixed beams is small. The use of multiple linear constraints upon the optimum weights reduces this signal suppression. Multiple directional constraints can lead to ill-conditioned equations. However, it is shown that the limiting solutions of multiple directional constraints are multiple derivative contraints and these do not lead to ill-conditioned equations. The ability of various derivative constraints to prevent signal suppression is analyzed quantitatively.
Directory of Open Access Journals (Sweden)
Daniel E. Rio
2013-01-01
Full Text Available A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI blood-oxygen level-dependent (BOLD multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF where prewhitening of the data is attempted using autoregressive (AR models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain. This is especially important for experimental designs involving multiple states (either stimulus or drug induced that may alter the form of the response function.
Practical Session: Multiple Linear Regression
Clausel, M.; Grégoire, G.
2014-12-01
Three exercises are proposed to illustrate the simple linear regression. In the first one investigates the influence of several factors on atmospheric pollution. It has been proposed by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr33.pdf) and is based on data coming from 20 cities of U.S. Exercise 2 is an introduction to model selection whereas Exercise 3 provides a first example of analysis of variance. Exercises 2 and 3 have been proposed by A. Dalalyan at ENPC (see Exercises 2 and 3 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_5.pdf).
Advanced statistics: linear regression, part II: multiple linear regression.
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.
Multiple Imputations for Linear Regression Models
Brownstone, David
1991-01-01
Rubin (1987) has proposed multiple imputations as a general method for estimation in the presence of missing data. Rubinâ€™s results only strictly apply to Bayesian models, but Schenker and Welsh (1988) directly prove the consistency Â multiple imputations inference~ when there are missing values of the dependent variable in linear regression models. This paper extends and modifies Schenker and Welshâ€™s theorems to give conditions where multiple imputations yield consistent inferences for bo...
Dimension reduction of the explanatory variables in multiple linear regression
Filzmoser, P; Croux, Christophe
2003-01-01
2002 Mathematics Subject Classification: 62J05, 62G35. In classical multiple linear regression analysis problems will occur if the regressors are either multicollinear or if the number of regressors is larger than the number of observations. In this note a new method is introduced which constructs orthogonal predictor variables in a way to have a maximal correlation with the dependent variable. The predictor variables are linear combinations of the original regressors. This ...
Multiple Image Arrangement for Subjective Quality Assessment
Wang, Yan; Zhai, Guangtao
2017-12-01
Subjective quality assessment serves as the foundation for almost all visual quality related researches. Size of the image quality databases has expanded from dozens to thousands in the last decades. Since each subjective rating therein has to be averaged over quite a few participants, the ever-increasing overall size of those databases calls for an evolution of existing subjective test methods. Traditional single/double stimulus based approaches are being replaced by multiple image tests, where several distorted versions of the original one are displayed and rated at once. And this naturally brings upon the question of how to arrange those multiple images on screen during the test. In this paper, we answer this question by performing subjective viewing test with eye tracker for different types arrangements. Our research indicates that isometric arrangement imposes less duress on participants and has more uniform distribution of eye fixations and movements and therefore is expected to generate more reliable subjective ratings.
A test for the parameters of multiple linear regression models ...
African Journals Online (AJOL)
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
Simple and multiple linear regression: sample size considerations.
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 Â© 2016 Elsevier Inc. All rights reserved.
LINEAR AND NON-LINEAR ANALYSES OF CABLE-STAYED STEEL FRAME SUBJECTED TO SEISMIC ACTIONS
Directory of Open Access Journals (Sweden)
Marko Đuran
2017-01-01
Full Text Available In this study, linear and non-linear dynamic analyses of a cable-stayed steel frame subjected to seismic actions are performed. The analyzed cable-stayed frame is the main supporting structure of a wide-span sports hall. Since the complex dynamic behavior of cable-stayed structures results in significant geometric nonlinearity, a nonlinear time history analysis is conducted. As a reference, an analysis using the European standard approach, the so-called linear modal response spectrum method, is also performed. The analyses are conducted for different seismic actions considering dependence on the response spectrums for various ground types and the corresponding artificially generated accelerograms. Despite fundamental differences between the two analyses, results indicate that the modal response spectrum analysis is surprisingly consistent with the internal forces and bending moment distributions of the nonlinear time history analysis. However, significantly smaller values of bending moments, internal forces, and displacements are obtained with the response spectrum analysis.
Proof nets with explicit negation for multiplicative linear logic
Puite, Q.
1998-01-01
Multiplicative linear logic MLL was introduced in Gi as a onesided sequent calculus linear negation is a notion that is dened via De Morgan identities One obtains proof nets for MLL by identifying derivations in the onesided calculus that are equal up to a permutation of inference rules In this
On Multiplicative Linear Logic, Modality and Quantum Circuits
Directory of Open Access Journals (Sweden)
Ugo Dal Lago
2012-10-01
Full Text Available A logical system derived from linear logic and called QMLL is introduced and shown able to capture all unitary quantum circuits. Conversely, any proof is shown to compute, through a concrete GoI interpretation, some quantum circuits. The system QMLL, which enjoys cut-elimination, is obtained by endowing multiplicative linear logic with a quantum modality.
Using Multiple Linear Regression Techniques to Quantify Carbon ...
African Journals Online (AJOL)
komla
locations, the study applied the stepwise multiple regression technique to identify ecological variables that would .... Data analyses. The Statistical Package for Social Sciences (SPSS 8.0) for Windows programme was used for statistical analyses of the data. Multiple linear regression methods were applied to analyse the.
Variable selection in multiple linear regression: The influence of ...
African Journals Online (AJOL)
Akaike's information criterion, influential data cases, Mallows' Cp criterion, multiple linear regression, variable ... may be modified, and hopefully improved, by making use of the influence measures. Four practical ..... information to any practitioner who analyses the fuel data, will surely be helpful in the decision as to whether ...
Full completeness of the multiplicative linear logic of Chu spaces
Devarajan, Harish; Hughes, Dominic; Plotkin, Gordon; Pratt, Vaughan
1999-01-01
We prove full completeness of multiplicative linear logic (MLL) without MIX under the Chu interpretation. In particular we show that the cut-free proofs of MLL theorems are in a natural bijection with the binary logical transformations of the corresponding operations on the category of Chu spaces on a two-letter alphabet.
Simple and multiple linear regressions between oil palm annual ...
African Journals Online (AJOL)
This study was aimed at determining whether variations in oil palm annual yields were significantly influenced by years of production, and at establishing if so simple and multiple linear regression relationships between oil palm annual yields and yearly climatic variables. Climatic and yield data were gathered in three ...
Variable selection in multiple linear regression: The influence of ...
African Journals Online (AJOL)
The influence of individual cases in a data set is studied when variable selection is applied in multiple linear regression. Two different influence measures, based on the Cp criterion and Akaike's information criterion, are introduced. The relative change in the selection criterion when an individual case is omitted is proposed ...
Criteria for stability of linear dynamical systems with multiple delays ...
African Journals Online (AJOL)
In this study we considered a linear Dynamical system with multiple delays and find suitable conditions on the systems parameters such that for a given initial function, we can define a mapping in a carefully chosen complete metric space on which the mapping has a unique fixed point. An asymptotic stability theory for the ...
Towards the Capacity Region of Multiplicative Linear Operator Broadcast Channels
Pang, Yimin
2010-01-01
Recent research indicates that packet multicasting employing random linear network coding can be regarded as transmitting subspaces as codewords over a linear operator channel (LOC). A LOC is normally viewed as a discrete memoryless unicast subspace channel over a finite field. In this paper we propose the framework of linear operator broadcast channels (LOBCs) and start initial work on determining their capacity region. LOBC correspond to a single-source multiple-recipients network, where every recipient's subchannel is a LOC having its own capacity. Our discussion concerns a class of constant-dimension multiplicative LOBCs (CMLOBCs), whose input subspaces have constant dimension and missing vectors of a subspace constitute the only possible channel interference. We first give a necessary and sufficient condition for a CMLOBC being stochastically degraded. Then we classify weakly and strongly degraded CMLOBCs. By numerically computing capacity regions with an Arimoto-Blahut type algorithm and discussing seve...
Optimized multiple linear mappings for single image super-resolution
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.
Output regulation of linear plants subject to constraints
Saberi, Ali; Stoorvogel, Antonie Arij; Shi, Guoyong; Sannuti, Peddapullaiah
Output regulation problems for continuous-time linear systems with state and/or input constraints are studied. The problems are formulated in global and semi-global setting by using state or full information feedback. The goal of this paper is to develop solvability conditions for the posed
Nonlinear Interactions of Multiple Linearly Unstable Thermoacoustic Modes
Directory of Open Access Journals (Sweden)
Jonas P. Moeck
2012-03-01
Full Text Available We investigate the dynamics of thermoacoustic systems with multiple linearly unstable modes. If a linear analysis reveals more than one mode with positive growth rate, nonlinear methods have to be used to determine the existence and stability of steady-state oscillations. One possible way to engage this problem is a first-order harmonic balance approach based on describing function representations for the flame response. In contrast to the case of a single unstable mode, the nonlinearity output to multiple sinusoidal components with different frequencies and amplitudes has to be known. Based on this approach, we present conditions for the existence and stability of single- or multi-mode steady-state oscillations. We apply this method to a thermoacoustic model system having two linearly unstable modes. By varying one of the system parameters, we find stable and unstable single-mode steady-states as well as unstable simultaneous oscillations. Associated with the stability of the single-mode limit cycles, we identify hysteresis in the oscillation type. Some related experimental observations are discussed.
EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
Lian, Yao; Ge, Meng; Pan, Xian-Ming
2014-12-19
B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
Galerkin projection methods for solving multiple related linear systems
Energy Technology Data Exchange (ETDEWEB)
Chan, T.F.; Ng, M.; Wan, W.L.
1996-12-31
We consider using Galerkin projection methods for solving multiple related linear systems A{sup (i)}x{sup (i)} = b{sup (i)} for 1 {le} i {le} s, where A{sup (i)} and b{sup (i)} are different in general. We start with the special case where A{sup (i)} = A and A is symmetric positive definite. The method generates a Krylov subspace from a set of direction vectors obtained by solving one of the systems, called the seed system, by the CG method and then projects the residuals of other systems orthogonally onto the generated Krylov subspace to get the approximate solutions. The whole process is repeated with another unsolved system as a seed until all the systems are solved. We observe in practice a super-convergence behaviour of the CG process of the seed system when compared with the usual CG process. We also observe that only a small number of restarts is required to solve all the systems if the right-hand sides are close to each other. These two features together make the method particularly effective. In this talk, we give theoretical proof to justify these observations. Furthermore, we combine the advantages of this method and the block CG method and propose a block extension of this single seed method. The above procedure can actually be modified for solving multiple linear systems A{sup (i)}x{sup (i)} = b{sup (i)}, where A{sup (i)} are now different. We can also extend the previous analytical results to this more general case. Applications of this method to multiple related linear systems arising from image restoration and recursive least squares computations are considered as examples.
The Impact of Multiple Fluency Interventions on a Single Subject
Morra, Jennifer; Tracey, Dianne H.
2006-01-01
This study investigates the effectiveness of multiple fluency interventions on a single subject in grade three. Fluency interventions, including choral reading, echo reading, repeated reading, audio book modeling, and teacher modeling were implemented over a period of eight weeks. Results indicated that using multiple fluency strategies, rather…
Estimation of Students’ Graduation Using Multiple Linear Regression Method
Directory of Open Access Journals (Sweden)
Bintang Dewi Fajar Kurniatullah
2017-04-01
Full Text Available Utilization of students’ academic data to produce information used by management in monitoring students’ study period on Information System Department. Multiple linier regression method will produce multiple linier regression equation used for estimating students’ graduation equipped with prototype. According to analysis carried out by using nine variable SKS1, SKS2, SKS3, SKS4, IPS1, IPS2, IPS3, IPS4, and the number of repeated courses of 2008 to 2012 the multiple linier regression equation is Y = 13.49 + 0.099 X1 + (-0.068 X2 + 0.025 X3 + (-0.059 X4 + (-0.585 X5 + (-0.443 X6 + (-0.155 X7 + (-0.368 X8 + (-0.082 X9. From the equation there is an error of MSE and RMSE that is equal to 0.1168 and 0.3418. The prototype uses a PHP-based program using sublime text and XAMPP. The prototype monitoring the students’ study time in this research is very helpful if supported by management. Keywords: Data mining, multiple linear regression, estimation, monitoring, study time
The linearized inversion of the generalized interferometric multiple imaging
Aldawood, Ali
2016-09-06
The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.
Growth performance of pigs subjected to multiple concurrent environmental stressors.
Hyun, Y; Ellis, M; Riskowski, G; Johnson, R W
1998-03-01
The effects of many single stressors have been reported, but how pigs perform when subjected to more than one or two stressors at a time, as is common in commercial swine production, has not. To study this, 256 Yorkshire x Hampshire or purebred Duroc pigs (34.7+/-.5 kg) were subjected to one of the eight treatment combinations (2 x 2 x 2 factorial) of ambient temperature (constant thermoneutral [24 degrees C] or high cycling temperature [28 to 34 degrees C]), stocking density (.56 or .25 m2/pig), and social group (static group or regrouped at the start of wk 1 and 3) during a 4-wk experiment. The temperature regimens were imposed in two adjacent mechanically ventilated rooms, and each temperature was imposed in each room across two trials. Four barrows and four gilts were assigned to each of the eight pens in the two rooms, and they always had free access to water and a corn-soybean meal-based diet. Treatments were imposed after a 7-d acclimation period at 24 degrees C and .56 m2/pig. Weight gain and feed intake were measured weekly. The main effects of each of the stressors for 4-wk ADG and ADFI were significant (P stressor interactions for ADG, ADFI, and gain:feed (G:F), there were no significant three-way interactions and only six two-way interactions, suggesting that the effects of the individual stressors were additive. Accordingly, the growth rate of pigs subjected to the single stressor of high cycling temperature, restricted space allowance, or regrouping was depressed 10, 16, and 11%, respectively, and ADG of pigs subjected to all three stressors simultaneously was depressed by 31%. Stressor additivity was further corroborated by examining the effect of stressor order, or the number of stressors imposed simultaneously. As the number of stressors increased from 0 to 3, ADG, ADFI, and G:F decreased linearly. These data suggest that multiple concurrent stressors affect growth performance of pigs in a predictable fashion (i.e., additively) and indicate that
Direction of Effects in Multiple Linear Regression Models.
Wiedermann, Wolfgang; von Eye, Alexander
2015-01-01
Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.
Decentralized stabilization of linear time invariant systems subject to actuator saturation
Stoorvogel, Antonie Arij; Saberi, Ali; Deliu, Ciprian; Deliu, C.; Sannuti, Peddapullaiah; Tarbouriech, S.; Garcia, G.; Glattfelder, A.H.
2007-01-01
We are concerned here with the stabilization of a linear time invariant system subject to actuator saturation via decentralized control while using linear time invariant dynamic controllers. When there exists no actuator saturation, i.e. when we consider just linear time invariant systems, it is
Design of Linear Systolic Arrays for Matrix Multiplication
Directory of Open Access Journals (Sweden)
MILOVANOVIC, E. I.
2014-02-01
Full Text Available This paper presents architecture for matrix multiplication optimized to be integrated as an accelerator unit to a host computer. Two linear systolic arrays with unidirectional data flow (ULSA, used as hardware accelerators, where synthesized in this paper. The solution proposed here is designed to accelerate both the computation and communication by employing hardware address generator units (AGUs. The proposed design has been implemented on Xilinx Spartan-2E and Virtex4 FPGAs. In order to evaluate performance of the proposed solution, we have introduced quantitative and qualitative performance criteria. For the ULSA with n processing elements (PEs, the speed-up is O(n/2. Average gain factor of hardware AGUs is about 2.7, with hardware overhead of 0.6% for 32-bit PEs.
Contiguous Uniform Deviation for Multiple Linear Regression in Pattern Recognition
Andriana, A. S.; Prihatmanto, D.; Hidaya, E. M. I.; Supriana, I.; Machbub, C.
2017-01-01
Understanding images by recognizing its objects is still a challenging task. Face elements detection has been developed by researchers but not yet shows enough information (low resolution in information) needed for recognizing objects. Available face recognition methods still have error in classification and need a huge amount of examples which may still be incomplete. Another approach which is still rare in understanding images uses pattern structures or syntactic grammars describing shape detail features. Image pixel values are also processed as signal patterns which are approximated by mathematical function curve fitting. This paper attempts to add contiguous uniform deviation method to curve fitting algorithm to increase applicability in image recognition system related to object movement. The combination of multiple linear regression and contiguous uniform deviation method are applied to the function of image pixel values, and show results in higher resolution (more information) of visual object detail description in object movement.
Predicting flight delay based on multiple linear regression
Ding, Yi
2017-08-01
Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.
DEFF Research Database (Denmark)
Holst, René; Jørgensen, Bent
2015-01-01
The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....
Stability Criterion of Linear Stochastic Systems Subject to Mixed H2/Passivity Performance
Directory of Open Access Journals (Sweden)
Cheung-Chieh Ku
2015-01-01
Full Text Available The H2 control scheme and passivity theory are applied to investigate the stability criterion of continuous-time linear stochastic system subject to mixed performance. Based on the stochastic differential equation, the stochastic behaviors can be described as multiplicative noise terms. For the considered system, the H2 control scheme is applied to deal with the problem on minimizing output energy. And the asymptotical stability of the system can be guaranteed under desired initial conditions. Besides, the passivity theory is employed to constrain the effect of external disturbance on the system. Moreover, the Itô formula and Lyapunov function are used to derive the sufficient conditions which are converted into linear matrix inequality (LMI form for applying convex optimization algorithm. Via solving the sufficient conditions, the state feedback controller can be established such that the asymptotical stability and mixed performance of the system are achieved in the mean square. Finally, the synchronous generator system is used to verify the effectiveness and applicability of the proposed design method.
Semi-global stabilization of linear systems subject to non-right invertible constraints
Saberi, Ali; Stoorvogel, Antonie Arij; Shi, Guoyong; Sannuti, Peddapullaiah
Stabilization problems of linear systems with right invertible constraints have mostly been solved for both global and semi-global frameworks. Linear systems subject to non-right invertible constraints have completely different characteristics compared to those with right invertible constraints.
Sugiura, Minoru; Matsumoto, Hikaru; Kato, Masaya; Ikoma, Yoshinori; Yano, Masamichi; Nagao, Akihiko
2004-06-01
Beta-cryptoxanthin (beta-CRX) is a carotenoid pigment found in Satsuma mandarin (Citrus unshiu Marc.) fruit, which is heavily produced in Japan. In this study, we evaluated the seasonal changes in the serum beta-CRX level and investigated predictors of serum beta-CRX level by multiple linear regression analysis. Blood tests and self-administered questionnaires were used every other month for one year. The subjects were healthy volunteers, 15 males and 12 females. The serum beta-CRX levels increased dramatically as the intake of Satsuma mandarin increased; the maximum increase was noted in January. Multiple linear regression analysis showed that, in males, the serum beta-CRX level could be predicted by Satsuma mandarin intake, age and the month of blood sampling; however, it was inversely associated with alcohol and smoking habits. Conversely, in females, the serum beta-CRX concentration could be predicted by Satsuma mandarin intake, the month of blood sampling and age; however, it was inversely associated with body mass index. The results of multiple linear regression analysis suggest that the serum beta-CRX levels can be used to evaluate the intake volume of Satsuma mandarin. Furthermore, beta-CRX is a useful biomarker to estimate the beneficial effects of Satsuma mandarin intake in epidemiological studies.
Gillam, Barbara; Marlow, Phillip J
2014-01-01
One current view is that subjective contours may involve high-level detection of a salient shape with back propagation to early visual areas where small receptive fields allow for scrutiny of relevant details. This idea applies to Kanizsa-type figures. However, Gillam and Chan (2002 Psychological Science, 13, 279-282) using figures based on Gillam's graphic 'New York Titanic' (Gillam, 1997 Thresholds: Limits of perception. New York: Arts Magazine) showed that strong subjective contours can be seen along the linearly aligned edges of a set of shapes if occlusion cues of 'extrinsic edge' and 'entropy contrast' are strong. Here we compared ratings of the strength of subjective contours along linear alignments with those seen in Kanizsa figures. The strongest subjective contour for a single set of linearly aligned shapes was similar in strength to the edges of a Kanizsa square (controlling for support ratio) despite the lack of a salient region. The addition of a second set of linearly aligned inducers consistent with a common surface increased subjective-contour strength, as did having four rather than two 'pacmen' in the Kanizsa figure, indicating a role for surface support. We argue that linear subjective contours allow for the investigation of certain occlusion cues and the interactions between them that are not easily explored with Kanizsa figures.
On optimal control of linear systems in the presence of multiplicative noise
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.
Subjective experience of difficulty depends on multiple cues
Desender, Kobe; Van Opstal, Filip; Van den Bussche, Eva
2017-01-01
Human cognition is characterized by subjective experiences that go along with our actions, but the nature and stability of these experiences remain largely unclear. In the current report, the subjective experience of difficulty is studied and it is proposed that this experience is constructed by integrating information from multiple cues. Such an account can explain the tight relationship between primary task performance and subjective difficulty, while allowing for dissociations between both to occur. Confirming this hypothesis, response conflict, reaction time and response repetition were identified as variables that contribute to the experience of difficulty. Trials that were congruent, fast or required the same response as the previous trial were more frequently rated as easy than trials that were incongruent, slow or required a different response as the previous trial. Furthermore, in line with theoretical accounts that relate metacognition to learning, a three day training procedure showed that the influence of these variables on subjective difficulty judgments can be changed. Results of the current study are discussed in relation to work on meta-memory and to recent theoretical advancements in the understanding of subjective confidence. PMID:28287137
Sequents and link graphs: contraction criteria for refinements of multiplicative linear logic
Puite, G.-W.Q.
2001-01-01
In this thesis we investigate certain structural refinements of multiplicative linear logic, obtained by removing structural rules like commutativity and associativity, in addition to the removal of weakening and contraction, which characterizes linear logic. We define a notion of sequent
Internet Purchases in European Union Countries: Multiple Linear Regression Approach
Ksenija Dumičić; Anita Čeh Časni; Irena Palić
2014-01-01
This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the In...
Multiple origins of linear dunes on Earth and Titan
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.
Semi-global stabilization of linear systems subject to non-right invertible constraints
Saberi, Ali; Stoorvogel, Antonie Arij; Shi, Guoyong; Sannuti, Peddapullaiah
Much progress has been made for the stabilization of linear systems subject to constraints. This paper summarizes the results established along the line of constraints modeled by a constrained output. Stabilization results established earlier for right invertible constraints are reviewed. New
Total shrinkage versus partial shrinkage in multiple linear regression ...
African Journals Online (AJOL)
The paper discusses the merits of partial shrinkage of the ordinary least square estimator of the coefficients of the multiple regression model of full rank. Theoretical comparisons of scalar and matrix-valued risks of the partially shrunken and totally shrunken estimators are given. The strategy of partial shrinkage is applied to ...
Using multiple linear regression techniques to quantify carbon ...
African Journals Online (AJOL)
Fallow ecosystems provide a significant carbon stock that can be quantified for inclusion in the accounts of global carbon budgets. Process and statistical models of productivity, though useful, are often technically rigid as the conditions for their application are not easy to satisfy. Multiple regression techniques have been ...
Interpreting Multiple Linear Regression: A Guidebook of Variable Importance
Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim
2012-01-01
Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…
DEFF Research Database (Denmark)
Köyluoglu, H.U.; Nielsen, Søren R.K.; Cakmak, A.S.
1994-01-01
The paper deals with the first and second order statistical moments of the response of linear systems with random parameters subject to random excitation modelled as white-noise multiplied by an envelope function with random parameters. The method of analysis is basically a second order perturbat......The paper deals with the first and second order statistical moments of the response of linear systems with random parameters subject to random excitation modelled as white-noise multiplied by an envelope function with random parameters. The method of analysis is basically a second order...... for multi-degree-of-freedom (MDOF) systems and the method is illustrated for a single-degree-of-freedom (SDOF) oscillator. The results are compared to those of exact results for a random oscillator subject to white noise excitation with random intensity....
Hierarchical Linear Modeling Meta-Analysis of Single-Subject Design Research
Gage, Nicholas A.; Lewis, Timothy J.
2014-01-01
The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD's utility centers on three issues: sample size, effect size, and serial dependence. One potential…
Non-linear canonical correlation for joint analysis of MEG signals from two subjects
Directory of Open Access Journals (Sweden)
Cristina eCampi
2013-06-01
Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.
Improved Hidden Clique Detection by Optimal Linear Fusion of Multiple Adjacency Matrices
2015-11-30
Improved Hidden Clique Detection by Optimal Linear Fusion of Multiple Adjacency Matrices (Invited Paper) Himanshu Nayar∗, Rajmonda S. Caceres†, Kelly...where we are a given multiple Erdős- Renyi modeled adjacency matrices containing a common hidden or planted clique. The objective is to combine them...probability—we adopt a linear fusion model in which we analyze a convex combination of the adjacency matrices of the graphs. Within this context, we
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Non-linear modal analysis of structural components subjected to unilateral constraints
Attar, M.; Karrech, A.; Regenauer-Lieb, K.
2017-02-01
a new NNM with a period equal to the integer multiple of the main mode period. Our results also indicate that the bilinear formula can accurately predict the non-linear frequencies only if the corresponding mode exhibits a smooth character, regardless of the commutativity conditions of the system stiffness matrix. However, it is obvious that the assumption of smooth bilinear behaviour for non-linear modes is not generally valid. This highlights the importance of the present numerical framework for the computation of non-smooth resonance frequencies.
Chun, E.; Rosner, R.
1993-01-01
We study the linear stability of an optically thin uniform radiating plasma subject to nonlocal heat transport. We derive the dispersion relation appropriate to this problem, and the marginal wavenumbers for instability. Our analysis indicates that nonlocal heat transport acts to reduce the stabilizing influence of thermal conduction, and that there are critical values for the electron mean free path such that the plasma is always unstable. Our results may be applied to a number of astrophysical plasmas, one such example being the halos of clusters of galaxies.
Maximising water supply system yield subject to multiple reliability ...
African Journals Online (AJOL)
The realistic incorporation of reliability into the optimisation of reservoir system design and operation remains a particularly difficult task after decades of research. While most of this research has worked with methods based on linear or dynamic programming, little has been done to find out how well the problem could be ...
Massimiliano Ferraioli; Alberto Mandara
2016-01-01
Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation ...
Qin, Weiwei; He, Bing; Zhao, Pengtao; Liu, Gang
2015-01-01
The problem of robust asymptotic stabilization is considered for a class of discrete-time uncertain linear systems with multiple uncertain time-delayed states and input constraints. Compared with other works in the literature, the proposed approach takes the information of the delayed states with the estimated time-delays indices into full consideration. Based on the predictive control principle of receding horizon optimization and Lyapunov stability theory combined with linear matrix inequal...
*S. Saaidpour; S. A. Zarei; F. Nasri
2012-01-01
The multiple linear regression (MLR) was used to build the linear quantitative structure-property relationship (QSPR) model for the prediction of the molar diamagnetic susceptibility (χm) for 140 diverse organic compounds using the three significant descriptors calculated from the molecular structures alone and selected by stepwise regression method. Stepwise regression was employed to develop a regression equation based on 100 training compounds, and predictive ability was tested on 40 compo...
Directory of Open Access Journals (Sweden)
Cui Y
2013-12-01
Full Text Available Yimin Cui,1 Yan Song,2 Jessie Wang,2 Zhigang Yu,2 Alan Schuster,2 Yu Chen Barrett,2 Charles Frost2 1Peking University First Hospital, Beijing, People's Republic of China; 2Bristol-Myers Squibb, Princeton, NJ, USA Background: The pharmacokinetics (PK, pharmacodynamics (PD, and safety of apixaban were assessed in healthy Chinese subjects in this randomized, placebo-controlled, double-blind, single-sequence, single- and multiple-dose study. Subjects and methods: Eighteen subjects 18–45 years of age were randomly assigned (2:1 ratio to receive apixaban or matched placebo. Subjects received a single 10 mg dose of apixaban or placebo on day 1, followed by 10 mg apixaban or placebo twice daily for 6 days (days 4–9. The PK and PD of apixaban were assessed by collecting plasma samples for 72 hours following the dose on day 1 and the morning dose on day 9, and measuring apixaban concentration and anti-Xa activity. Safety was assessed via physical examinations, vital sign measurements, electrocardiograms, and clinical laboratory evaluations. Results: PK analysis showed similar characteristics of apixaban after single and multiple doses, including a median time to maximum concentration of ~3 hours, mean elimination half-life of ~11 hours, and renal clearance of ~1.2 L/hour. The accumulation index was 1.7, consistent with twice-daily dosing and the observed elimination half-life. Single-dose data predict multiple-dose PK, therefore apixaban PK are time-independent. The relationship between anti-Xa activity and plasma apixaban concentrations appears to be linear. Apixaban was safe and well tolerated, with no bleeding-related adverse events reported. Conclusion: Apixaban was safe and well tolerated in healthy Chinese subjects. Apixaban PK and PD were predictable and consistent with findings from previous studies in Asian and non-Asian subjects. The administration of apixaban does not require any dose modification based on race. Keywords: apixaban, oral
Zhang, Xiaodong; Zhao, Yinxia; Hu, Shaoyong; Hao, Shuai; Yan, Jiewen; Zhang, Lingyan; Zhao, Jing; Li, Shaolin
2015-09-01
To investigate the correlation between the lumbar vertebra bone mineral density (BMD) and age, gender, height, weight, body mass index, waistline, hipline, bone marrow and abdomen fat, and to explore the key factor affecting the BMD. A total of 72 cases were randomly recruited. All the subjects underwent a spectroscopic examination of the third lumber vertebra with single-voxel method in 1.5T MR. Lipid fractions (FF%) were measured. Quantitative CT were also performed to get the BMD of L3 and the corresponding abdomen subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT). The statistical analysis were performed by SPSS 19.0. Multiple linear regression showed except the age and FF% showed significant difference (P0.05). The correlation of age and FF% with BMD was statistically negatively significant (r=-0.830, -0.521, P<0.05). The ROC curve analysis showed that the sensitivety and specificity of predicting osteoporosis were 81.8% and 86.9%, with a threshold of 58.5 years old. And it showed that the sensitivety and specificity of predicting osteoporosis were 90.9% and 55.7%, with a threshold of 52.8% for FF%. The lumbar vertebra BMD was significantly and negatively correlated with age and bone marrow FF%, but it was not significantly correlated with gender, height, weight, BMI, waistline, hipline, SAT and VAT. And age was the critical factor.
Egg hatchability prediction by multiple linear regression and artificial neural networks
Directory of Open Access Journals (Sweden)
AC Bolzan
2008-06-01
Full Text Available An artificial neural network (ANN was compared with a multiple linear regression statistical method to predict hatchability in an artificial incubation process. A feedforward neural network architecture was applied. Network trainings were made by the backpropagation algorithm based on data obtained from industrial incubations. The ANN model was chosen as it produced data that fit better the experimental data as compared to the multiple linear regression model, which used coefficients determined by minimum square method. The proposed simulation results of these approaches indicate that this ANN can be used for incubation performance prediction.
Non-linear molecular pattern classification using molecular beacons with multiple targets.
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.
Dandu, Sriram Raju; Patek, Stephen D.; Lach, John C.; Goldman, Myla D.
2016-01-01
Background The six-minute walk (6MW) is a common walking outcome in multiple sclerosis (MS) thought to measure fatigability in addition to overall walking disability. However, direct evidence of 6MW induced gait deterioration is limited by the difficulty of measuring qualitative changes in walking. Objectives This study aims to (1) define and validate a measure of fatigue-related gait deterioration based on data from body-worn sensors; and (2) use this measure to detect gait deterioration induced by the 6MW. Methods Gait deterioration was assessed using the Warp Score, a measure of similarity between gait cycles based on dynamic time warping (DTW). Cycles from later minutes were compared to baseline cycles in 89 subjects with MS and 29 controls. Correlation, corrected (partial) correlation, and linear regression were used to quantify relationships to walking and fatigue outcomes. Results Warp Scores rose between minute 3 and minute 6 in subjects with mild and moderate disability (p Warp Scores and walking speed explained 73.9% of response variance. Correlations to individual MSWS-12 and MFIS items strongly suggest a relationship to fatigability. Conclusion The Warp Score has been validated in MS subjects as an objective measure of fatigue-related gait deterioration. Progressive changes to gait cycles induced by the 6MW often appeared in later minutes, supporting the importance of sustained walking in clinical assessment. PMID:27479220
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.
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.
A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants
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…
Application of range-test in multiple linear regression analysis in ...
African Journals Online (AJOL)
Application of range-test in multiple linear regression analysis in the presence of outliers is studied in this paper. First, the plot of the explanatory variables (i.e. Administration, Social/Commercial, Economic services and Transfer) on the dependent variable (i.e. GDP) was done to identify the statistical trend over the years.
Tightness of M-estimators for multiple linear regression in time series
DEFF Research Database (Denmark)
Johansen, Søren; Nielsen, Bent
We show tightness of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semi-continuous and sufficiently large for large argument: Particular cases are the Huber-skip and quantile regression. Tightness requires...
A Quantitative and Combinatorial Approach to Non-Linear Meanings of Multiplication
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…
Single image super-resolution using locally adaptive multiple linear regression.
Yu, Soohwan; Kang, Wonseok; Ko, Seungyong; Paik, Joonki
2015-12-01
This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.
Khalil, Mohamed H; Shebl, Mostafa K; Kosba, Mohamed A; El-Sabrout, Karim; Zaki, Nesma
2016-08-01
This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens' eggs. 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. 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. A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens.
Feminist Physics Education: Deconstructed Physics and Students' Multiple Subjectivities
Jammula, Diane Crenshaw
Physics is one of the least diverse sciences; in the U.S. in 2010, only 21% of bachelors degrees in physics were awarded to women, 2.5% to African Americans, and 4% to Hispanic Americans (AIP, 2012). Though physics education reform efforts supporting interactive engagement have doubled students' learning gains (Hake, 1998), gender and race gaps persist (Brewe et al., 2010; Kost, Pollock, & Finkelstein, 2009). When students' subjectivities align with presentations of physics, they are more likely to develop positive physics identities (Hughes, 2001). However, both traditional and reformed physics classrooms may present physics singularly as abstract, elite, and rational (Carlone, 2004). Drawing from feminist science, I argue that binaries including abstract / concrete, elite / accessible, and rational / emotional are hierarchal and gendered, raced and classed. The words on the left define conventional physics and are associated with middle class white masculinity, while the words on the right are associated with femininity or other, and are often missing or delegitimized in physics education, as are females and minorities. To conceptualize a feminist physics education, I deconstructed these binaries by including the words on the right as part of doing physics. I do not imply that women and men think differently, but that broadening notions of physics may allow a wider range of students to connect with the discipline. I used this conceptual framework to modify a popular reformed physics curriculum called Modeling Instruction (Hestenes, 1987). I taught this curriculum at an urban public college in an introductory physics course for non-science majors. Twenty-three students of diverse gender, race, ethnic, immigrant and class backgrounds enrolled. I conducted an ethnography of the classroom to learn how students negotiate their subjectivities to affiliate with or alienate from their perceptions of physics, and to understand how classroom experiences exacerbate or
Application of wavelet-based multiple linear regression model to rainfall forecasting in Australia
He, X.; Guan, H.; Zhang, X.; Simmons, C.
2013-12-01
In this study, a wavelet-based multiple linear regression model is applied to forecast monthly rainfall in Australia by using monthly historical rainfall data and climate indices as inputs. The wavelet-based model is constructed by incorporating the multi-resolution analysis (MRA) with the discrete wavelet transform and multiple linear regression (MLR) model. The standardized monthly rainfall anomaly and large-scale climate index time series are decomposed using MRA into a certain number of component subseries at different temporal scales. The hierarchical lag relationship between the rainfall anomaly and each potential predictor is identified by cross correlation analysis with a lag time of at least one month at different temporal scales. The components of predictor variables with known lag times are then screened with a stepwise linear regression algorithm to be selectively included into the final forecast model. The MRA-based rainfall forecasting method is examined with 255 stations over Australia, and compared to the traditional multiple linear regression model based on the original time series. The models are trained with data from the 1959-1995 period and then tested in the 1996-2008 period for each station. The performance is compared with observed rainfall values, and evaluated by common statistics of relative absolute error and correlation coefficient. The results show that the wavelet-based regression model provides considerably more accurate monthly rainfall forecasts for all of the selected stations over Australia than the traditional regression model.
Directory of Open Access Journals (Sweden)
Kepler Thomas B
2005-06-01
Full Text Available Abstract Background In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE libraries, it is critical to account for both between and within library variation. Several methods have been proposed, including the t test, tw test, and an overdispersed logistic regression approach. The merits of these tests, however, have not been fully evaluated. Questions still remain on whether further improvements can be made. Results In this article, we introduce an overdispersed log-linear model approach to analyzing SAGE; we evaluate and compare its performance with three other tests: the two-sample t test, tw test and another based on overdispersed logistic linear regression. Analysis of simulated and real datasets show that both the log-linear and logistic overdispersion methods generally perform better than the t and tw tests; the log-linear method is further found to have better performance than the logistic method, showing equal or higher statistical power over a range of parameter values and with different data distributions. Conclusion Overdispersed log-linear models provide an attractive and reliable framework for analyzing SAGE experiments involving multiple libraries. For convenience, the implementation of this method is available through a user-friendly web-interface available at http://www.cbcb.duke.edu/sage.
Multiple linear regression with some correlated errors: classical and robust methods.
Pires, Ana M; Rodrigues, Isabel M
2007-07-10
In this paper we consider classical and robust methods of estimation and diagnostics for the multiple linear regression model when some of the errors are correlated. This work was motivated by the analysis of a medical data set, from an observational study aimed at identifying factors affecting the outcome of a surgical method for the correction of scoliosis (abnormal lateral spinal curvature). There are 392 observations but some of them are on the same patient (double curves). It seems adequate to consider a multiple linear regression model but, since it is not desirable to discard the double curves, the assumption of non-correlated errors is clearly violated, and this is indeed confirmed by related diagnostics on the residuals (Durbin-Watson test). A more appropriate model retains the linear structure but allows for non-null correlation between the errors on the same patient. We propose two different procedures for the estimation of the parameters of the linear model and the correlation parameters: maximum likelihood assuming normal errors and a robustified version obtained by plugging-in results from robust linear regression. The latter procedure is designed to be resistant to outlying observations or error distributions with heavy tails and has produced the most satisfactory results for the analysed data set. Copyright 2006 John Wiley & Sons, Ltd.
National Research Council Canada - National Science Library
Lorenzo-Seva, Urbano; Ferrando, Pere J
2011-01-01
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors...
Nidumolu, U.B.; Keulen, van H.; Lubbers, M.T.M.H.; Mapfumo, P.
2007-01-01
An Interactive Multiple Goal Linear Programming (IMGLP) model is developed that considers objectives of multiple stakeholders, i.e. different farmer groups, district agricultural officers and agricultural scientists for agricultural land use analysis. The analysis focuses on crop selection;
Directory of Open Access Journals (Sweden)
Ousmane Coulibaly
2016-01-01
Full Text Available We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the solar declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Pô and 3.65% (Dédougou. The maximum value of the RMSD which is 312.36 kJ/m2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)
Eng, Ken; Chen, Yin-Yu; Kiang, Julie.E.
2009-01-01
Streamflow is not measured at every location in a stream network. Yet hydrologists, State and local agencies, and the general public still seek to know streamflow characteristics, such as mean annual flow or flood flows with different exceedance probabilities, at ungaged basins. The goals of this guide are to introduce and familiarize the user with the weighted multiple-linear regression (WREG) program, and to also provide the theoretical background for program features. The program is intended to be used to develop a regional estimation equation for streamflow characteristics that can be applied at an ungaged basin, or to improve the corresponding estimate at continuous-record streamflow gages with short records. The regional estimation equation results from a multiple-linear regression that relates the observable basin characteristics, such as drainage area, to streamflow characteristics.
Linking teleconnection patterns to European temperature – a multiple linear regression model
Henning W. Rust; Andy Richling; Peter Bissolli; Uwe Ulbrich
2015-01-01
The link between the indices of twelve atmospheric teleconnection patterns (mostly Northern Hemispheric) and gridded European temperature data is investigated by means of multiple linear regression models for each grid cell and month. Furthermore index-specific signals are calculated to estimate the contribution to temperature anomalies caused by each individual teleconnection pattern. To this extent, an observational product of monthly mean temperature (E-OBS), as well as monthly time series...
Tightness of M-estimators for multiple linear regression in time series
Johansen, Søren; Nielsen, Bent
2016-01-01
We show tightness of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semi-continuous and sufficiently large for large argument: Particular cases are the Huber-skip and quantile regression. Tightness requires an assumption on the frequency of small regressors. We show that this is satisfied for a variety of deterministic and stochastic regressors, including stationary an random walks regressors. The resul...
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...
Directory of Open Access Journals (Sweden)
Qiong Liu
2012-01-01
Full Text Available We study the following fourth-order elliptic equations: Δ2+Δ=(,,∈Ω,=Δ=0,∈Ω, where Ω⊂ℝ is a bounded domain with smooth boundary Ω and (, is asymptotically linear with respect to at infinity. Using an equivalent version of Cerami's condition and the symmetric mountain pass lemma, we obtain the existence of multiple solutions for the equations.
A Performance Study of Data Mining Techniques: Multiple Linear Regression vs. Factor Analysis
Taneja, Abhishek; Chauhan, R. K.
2011-01-01
The growing volume of data usually creates an interesting challenge for the need of data analysis tools that discover regularities in these data. Data mining has emerged as disciplines that contribute tools for data analysis, discovery of hidden knowledge, and autonomous decision making in many application domains. The purpose of this study is to compare the performance of two data mining techniques viz., factor analysis and multiple linear regression for different sample sizes on three uniqu...
Directory of Open Access Journals (Sweden)
He-Yau Kang
2016-12-01
Full Text Available Meeting the demand of energy is a challenge for many countries these days, and generating electricity from renewable resources has become a main trend for future economic development. The construction of a renewable energy plant is costly and timely; therefore, a good project management model is essential. In this paper, a fuzzy multiple objective linear programming (FMOLP model is constructed based on program evaluation and review technique (PERT first. With the consideration of the different degrees of importance of the multiple objectives, a fuzzy multiple weighted-objective linear programming (FMWOLP model is constructed next. Through each proposed model, a compromise solution can be devised to maximize the total degree of satisfaction while considering multiple objectives. The results can provide references for the management on what activities and how long these activities should be crashed, how much the total project cost should be, and how long the total project duration time should be. Finally, the proposed models are applied to a case study of a wind turbine construction in Taiwan.
Output regulation of discrete-time linear plants subject to state and input constraints
Shi, Guoyong; Saberi, Ali; Stoorvogel, Antonie Arij; Sannuti, Peddapullaiah
2003-01-01
Discrete-time output regulation of linear systems with state and/or input constraints on magnitude is considered. Structural properties of linear plants are identified under which the so-called constrained semi-global and global output regulation problems are solvable. As in the case of
Li, Yanming; Nan, Bin; Zhu, Ji
2015-06-01
We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.
hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.
Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Zhou, Manli; Zhou, Fengfeng
2017-01-01
Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variety of functions and a patient with multiple diseases. The majority of existing classification algorithms assumes each sample with only one class label, and the multi-label classification problem remains to be a challenge for biomedical researchers. This study proposes a novel multi-label learning algorithm, hMuLab, by integrating both feature-based and neighbor-based similarity scores. The multiple linear regression modeling techniques make hMuLab capable of producing multiple label assignments for a query sample. The comparison results over six commonly-used multi-label performance measurements suggest that hMuLab performs accurately and stably for the biomedical datasets, and may serve as a complement to the existing literature.
Zhou, Bin; Liu, Ke; Jiang, Yan; Wei, Jian-Chao; Chen, Pu-Yan
2011-07-30
Classical swine fever is a highly contagious disease of swine caused by classical swine fever virus, an OIE list A pathogen. Epitope-based vaccines is one of the current focuses in the development of new vaccines against classical swine fever virus (CSFV). Two B-cell linear epitopes rE2-ba from the E2 glycoprotein of CSFV, rE2-a (CFRREKPFPHRMDCVTTTVENED, aa844-865) and rE2-b (CKEDYRYAISSTNEIGLLGAGGLT, aa693-716), were constructed and heterologously expressed in Escherichia coli as multiple epitope vaccine. Fifteen 6-week-old specified-pathogen-free (SPF) piglets were intramuscularly immunized with epitopes twice at 2-week intervals. All epitope-vaccinated pigs could mount an anamnestic response after booster vaccination with neutralizing antibody titers ranging from 1:16 to 1:256. At this time, the pigs were subjected to challenge infection with a dose of 1 × 106 TCID50 virulent CSFV strain. After challenge infection, all of the rE2-ba-immunized pigs were alive and without symptoms or signs of CSF. In contrast, the control pigs continuously exhibited signs of CSF and had to be euthanized because of severe clinical symptoms at 5 days post challenge infection. The data from in vivo experiments shown that the multiple epitope rE2-ba shown a greater protection (similar to that of HCLV vaccine) than that of mono-epitope peptide(rE2-a or rE2-b). Therefore, The results demonstrated that this multiple epitope peptide expressed in a prokaryotic system can be used as a potential DIVA (differentiating infected from vaccinated animals) vaccine. The E.coli-expressed E2 multiple B-cell linear epitopes retains correct immunogenicity and is able to induce a protective immune response against CSFV infection.
Directory of Open Access Journals (Sweden)
Wei Jian-Chao
2011-07-01
Full Text Available Abstract Classical swine fever is a highly contagious disease of swine caused by classical swine fever virus, an OIE list A pathogen. Epitope-based vaccines is one of the current focuses in the development of new vaccines against classical swine fever virus (CSFV. Two B-cell linear epitopes rE2-ba from the E2 glycoprotein of CSFV, rE2-a (CFRREKPFPHRMDCVTTTVENED, aa844-865 and rE2-b (CKEDYRYAISSTNEIGLLGAGGLT, aa693-716, were constructed and heterologously expressed in Escherichia coli as multiple epitope vaccine. Fifteen 6-week-old specified-pathogen-free (SPF piglets were intramuscularly immunized with epitopes twice at 2-week intervals. All epitope-vaccinated pigs could mount an anamnestic response after booster vaccination with neutralizing antibody titers ranging from 1:16 to 1:256. At this time, the pigs were subjected to challenge infection with a dose of 1 × 106 TCID50 virulent CSFV strain. After challenge infection, all of the rE2-ba-immunized pigs were alive and without symptoms or signs of CSF. In contrast, the control pigs continuously exhibited signs of CSF and had to be euthanized because of severe clinical symptoms at 5 days post challenge infection. The data from in vivo experiments shown that the multiple epitope rE2-ba shown a greater protection (similar to that of HCLV vaccine than that of mono-epitope peptide(rE2-a or rE2-b. Therefore, The results demonstrated that this multiple epitope peptide expressed in a prokaryotic system can be used as a potential DIVA (differentiating infected from vaccinated animals vaccine. The E.coli-expressed E2 multiple B-cell linear epitopes retains correct immunogenicity and is able to induce a protective immune response against CSFV infection.
Parton, Chloe; Katz, Terri; Ussher, Jane M
2017-10-01
Multiple sclerosis causes physical and cognitive impairment that can impact women's experiences of motherhood. This study examined how women construct their maternal subjectivities, or sense of self as a mother, drawing on a framework of biographical disruption. A total of 20 mothers with a multiple sclerosis diagnosis took part in semi-structured interviews. Transcripts were analysed using thematic decomposition to identify subject positions that women adopted in relation to cultural discourses of gender, motherhood and illness. Three main subject positions were identified: 'The Failing Mother', 'Fear of Judgement and Burdening Others' and 'The Normal Mother'. Women's sense of self as the 'Failing Mother' was attributed to the impact of multiple sclerosis, contributing to biographical disruption and reinforced through 'Fear of Judgement and Burdening Others' within social interactions. In accounts of the 'Normal Mother', maternal subjectivity was renegotiated by adopting strategies to manage the limitations of multiple sclerosis on mothering practice. This allowed women to self-position as 'good' mothers. Health professionals can assist women by acknowledging the embodied impact of multiple sclerosis on maternal subjectivities, coping strategies that women employ to address potential biographical disruption, and the cultural context of mothering, which contributes to women's experience of subjectivity and well-being when living with multiple sclerosis.
Hu, L; Zhang, Z G; Mouraux, A; Iannetti, G D
2015-05-01
Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical
A note on the use of multiple linear regression in molecular ecology.
Frasier, Timothy R
2016-03-01
Multiple linear regression analyses (also often referred to as generalized linear models--GLMs, or generalized linear mixed models--GLMMs) are widely used in the analysis of data in molecular ecology, often to assess the relative effects of genetic characteristics on individual fitness or traits, or how environmental characteristics influence patterns of genetic differentiation. However, the coefficients resulting from multiple regression analyses are sometimes misinterpreted, which can lead to incorrect interpretations and conclusions within individual studies, and can propagate to wider-spread errors in the general understanding of a topic. The primary issue revolves around the interpretation of coefficients for independent variables when interaction terms are also included in the analyses. In this scenario, the coefficients associated with each independent variable are often interpreted as the independent effect of each predictor variable on the predicted variable. However, this interpretation is incorrect. The correct interpretation is that these coefficients represent the effect of each predictor variable on the predicted variable when all other predictor variables are zero. This difference may sound subtle, but the ramifications cannot be overstated. Here, my goals are to raise awareness of this issue, to demonstrate and emphasize the problems that can result and to provide alternative approaches for obtaining the desired information. © 2015 John Wiley & Sons Ltd.
Simplifying continuous monitoring of multiple-response/multiple-subject classroom interactions.
Skrtic, T M; Sepler, H J
1982-01-01
In order to facilitate the field monitoring of three subjects interacting according to one or more of 18 response categories, a modified version of several available, but oftentimes mechanically incompatible, observational procedures was designed. Its continuous recording strategy, sectioned into one-minute observational units, enabled researchers to derive highly representative behavior samples, and when accompanied by the specially tailored coding form and recording apparatus, observers achieved over 90% agreement across all reliability sessions. This procedure provides applied researchers with a simple, highly reliable, and adaptable observation tool for continuously and simultaneously monitoring the behaviors of one or more subjects.
Joshi, Deepti; St-Hilaire, André; Daigle, Anik; Ouarda, Taha B. M. J.
2013-04-01
SummaryThis study attempts to compare the performance of two statistical downscaling frameworks in downscaling hydrological indices (descriptive statistics) characterizing the low flow regimes of three rivers in Eastern Canada - Moisie, Romaine and Ouelle. The statistical models selected are Relevance Vector Machine (RVM), an implementation of Sparse Bayesian Learning, and the Automated Statistical Downscaling tool (ASD), an implementation of Multiple Linear Regression. Inputs to both frameworks involve climate variables significantly (α = 0.05) correlated with the indices. These variables were processed using Canonical Correlation Analysis and the resulting canonical variates scores were used as input to RVM to estimate the selected low flow indices. In ASD, the significantly correlated climate variables were subjected to backward stepwise predictor selection and the selected predictors were subsequently used to estimate the selected low flow indices using Multiple Linear Regression. With respect to the correlation between climate variables and the selected low flow indices, it was observed that all indices are influenced, primarily, by wind components (Vertical, Zonal and Meridonal) and humidity variables (Specific and Relative Humidity). The downscaling performance of the framework involving RVM was found to be better than ASD in terms of Relative Root Mean Square Error, Relative Mean Absolute Bias and Coefficient of Determination. In all cases, the former resulted in less variability of the performance indices between calibration and validation sets, implying better generalization ability than for the latter.
Yoo, Yun Joo; Sun, Lei; Poirier, Julia G; Paterson, Andrew D; Bull, Shelley B
2017-02-01
By jointly analyzing multiple variants within a gene, instead of one at a time, gene-based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster-specific effects in a quadratic sum of squares and cross-products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well-powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P-value, variance-component, and principal-component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene-specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome-wide analysis. The cluster construction of the MLC test statistics helps reveal within-gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations. © 2016 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.
Chao, Yi-Chun E; Zhao, Yue; Kupper, Lawrence L; Nylander-French, Leena A
2008-08-01
Multiple linear regression analysis is widely used in many scientific fields, including public health, to evaluate how an outcome or response variable is related to a set of predictors. As a result, researchers often need to assess "relative importance" of a predictor by comparing the contributions made by other individual predictors in a particular regression model. Hence, development of valid statistical methods to estimate the relative importance of a set of predictors is of great interest. In this research, the authors considered the relative importance of a predictor when defined by that portion of the squared multiple correlation explained by the contribution of each predictor in the final model of interest. Here, a number of suggested relative importance indices motivated by this definition are reviewed, including the squared zero-order correlation, squared semipartial correlation, Product Measure (i.e., Pratt's Index), General Dominance Index, and Johnson's Relative Weight. The authors compared these indices using data sets from an occupational health study in which human inhalation exposure to styrene was measured and from a laboratory animal study on risk factors for atherosclerosis, and statistical properties using bootstrap methods were examined. The analysis suggests that the General Dominance Index and Johnson's Relative Weight are preferred methods for quantifying the relative importance of predictors in a multiple linear regression model. Johnson's Relative Weight involves significantly less computational burden than the General Dominance Index when the number of predictors in the final model is large.
Directory of Open Access Journals (Sweden)
Massimiliano Ferraioli
2016-01-01
Full Text Available Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation bearings supporting the adjacent structures. In this situation, the conventional equivalent linear elastic analysis may have some problems of accuracy because this method is calibrated on single base-isolated structures. Moreover, the torsional characteristics of the combined system are significantly different from those of separate isolated buildings. A number of numerical simulations and parametric studies under earthquake excitations were performed. The accuracy of the dynamic response obtained by the equivalent linear elastic model was calculated by the magnitude of the error with respect to the corresponding response considering the nonlinear behaviour of the isolation system. The maximum displacements at the isolation level, the maximum interstorey drifts, and the peak absolute acceleration were selected as the most important response measures. The influence of mass eccentricity, torsion, and high-modes effects was finally investigated.
Stoorvogel, Antonie Arij; Saberi, Ali; Shi, Guoyong
This paper investigates time-invariant linear systems subject to input and state constraints. It is shown that the recoverable region (which is the largest domain of attraction that is theoretically achievable) can be semiglobally stabilized by continuous nonlinear feedbacks while satisfying the
Stoorvogel, Antonie Arij; Saberi, Ali; Shi, Guoyong
This paper investigates linear systems subject to input and state constraints. It is shown that the recoverable region (which is the largest domain of attraction that is theoretically achievable) can be semiglobally stabilized by continuous nonlinear feedbacks while satisfying the constraints.
Memory State Feedback RMPC for Multiple Time-Delayed Uncertain Linear Systems with Input Constraints
Directory of Open Access Journals (Sweden)
Wei-Wei Qin
2014-01-01
Full Text Available This paper focuses on the problem of asymptotic stabilization for a class of discrete-time multiple time-delayed uncertain linear systems with input constraints. Then, based on the predictive control principle of receding horizon optimization, a delayed state dependent quadratic function is considered for incorporating MPC problem formulation. By developing a memory state feedback controller, the information of the delayed plant states can be taken into full consideration. The MPC problem is formulated to minimize the upper bound of infinite horizon cost that satisfies the sufficient conditions. Then, based on the Lyapunov-Krasovskii function, a delay-dependent sufficient condition in terms of linear matrix inequality (LMI can be derived to design a robust MPC algorithm. Finally, the digital simulation results prove availability of the proposed method.
Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions
Belkhatir, Zehor
2017-06-28
This paper proposes an estimation algorithm for the characterization of multiple point inputs for linear fractional order systems. First, using polynomial modulating functions method and a suitable change of variables the problem of estimating the locations and the amplitudes of a multi-pointwise input is decoupled into two algebraic systems of equations. The first system is nonlinear and solves for the time locations iteratively, whereas the second system is linear and solves for the input’s amplitudes. Second, closed form formulas for both the time location and the amplitude are provided in the particular case of single point input. Finally, numerical examples are given to illustrate the performance of the proposed technique in both noise-free and noisy cases. The joint estimation of pointwise input and fractional differentiation orders is also presented. Furthermore, a discussion on the performance of the proposed algorithm is provided.
Directory of Open Access Journals (Sweden)
Avval Zhila Mohajeri
2015-01-01
Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.
Choi, Jae-Seok; Kim, Munchurl
2017-03-01
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower
Inference regarding multiple structural changes in linear models with endogenous regressors☆
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
An improved multiple linear regression and data analysis computer program package
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.
DEFF Research Database (Denmark)
D'Souza, Sonia; Rasmussen, John; Schwirtz, Ansgar
2012-01-01
and valuable ergonomic tool. Objective: To investigate age and gender effects on the torque-producing ability in the knee and elbow in older adults. To create strength scaled equations based on age, gender, upper/lower limb lengths and masses using multiple linear regression. To reduce the number of dependent...... parameters based on statistical redundancies, and then validate these equations. Methods: 283 subjects (141 males, 142 females) aged 50-59 years (54.9 +/- 2.9) , 60-69 years (65.4 +/- 2.9) and 70-79 years (73.7 +/- 2.7) were tested for maximal voluntary isometric torque of right knee extensors and elbow...... flexors. Results: Males were signifantly stronger than females across all age groups. Elbow peak torque (EPT) was better preserved from 60s to 70s whereas knee peak torque (KPT) reduced significantly (P
Ko, C. C.; Wen, J.; Chin, F.
1992-12-01
A new algorithm for separating and tracking multiple directional sources in a linear power-inversion array is proposed and investigated. In this algorithm, the sources are separated by using an adaptive beamformer whose responses consist of perfect steerable nulls. By using the LMS algorithm for adaptive processing of the beamformer outputs to minimize the array output power and examining the adaptive weights employed, these nulls can be adjusted to track the sources individually so that the beamformer outputs will be due to different sources in the steady state. With this algorithm, the problem of incidental cancellation is eliminated and the enhancement of multiple moving sources becomes a natural process. Also, since the sources are individually tracked and the beamformer is only updated occasionally when significant changes in the environment are detected, the algorithm possesses fast tracking behavior and its implementation complexity is comparable with that of beamformer-based adaptive arrays using the LMS algorithm.
Yanti, Y. R.; Amin, S. M.; Sulaiman, R.
2018-01-01
This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.
Brooks, Emily K; Staatz, Christine E; Tett, Susan E; Isbel, Nicole M; McWhinney, Brett
2018-02-14
Although multiple linear regression-based limited sampling strategies (LSS) have been published for enteric-coated mycophenolate sodium (EC-MS), none have been evaluated for the prediction of subsequent mycophenolic acid (MPA) exposure. This study aimed to examine the predictive performance of the published LSS for the estimation of future MPA area under the concentration-time curve from 0 to 12 hours (AUC0-12) in renal transplant recipients. Total MPA plasma concentrations were measured in twenty adult renal transplant patients on two occasions a week apart. All subjects received concomitant tacrolimus and were approximately one-month post transplant. Samples were taken at 0, 0.33, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 6, and 8 hours and 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 2, 3, 4, 6, 9, and 12 hours post dose on the first and second sampling occasion, respectively. Predicted MPA AUC0-12 was calculated using nineteen published LSS and data from the first or second sampling occasion for each patient and compared to the second occasion full MPA AUC0-12 calculated using the linear trapezoidal rule. Bias (median percentage prediction error [MPPE]) and imprecision (median absolute prediction error [MAPE]) were determined. MPPE and MAPE for the prediction of full MPA AUC0-12 were multiple linear regression-based LSS was not possible without concentrations up to at least 8 hours after the dose.
Transmedia Storytelling in Science Communication: One Subject, Multiple Media, Multiple Stories
Unger, M.; Moloney, K.
2012-12-01
Each communication medium has particular storytelling strengths. For example, video is particularly good at illustrating a progression of events, text at background and context, and games at describing systems. In what USC's Prof. Henry Jenkins described as "transmedia storytelling," multiple media are used simultaneously, in an expansive rather than repetitive way, to better tell a single, complex story. The audience is given multiple entry points to the story, and the story is exposed to diverse and dispersed audiences, ultimately engaging a broader public. We will examine the effectiveness of a transmedia approach to communicating scientific and other complex concepts to a broad and diverse audience. Using the recently developed Educational Visitor Center at the NCAR-Wyoming Supercomputing Center as a case study, we will evaluate the reach of various means of presenting information about the geosciences, climate change and computational science. These will include an assessment of video, mechanical and digital interactive elements, animated movie segments, web-based content, photography, scientific visualizations, printed material and docent-led activities.
Boulet, Sebastien; Boudot, Elsa; Houel, Nicolas
2016-05-03
Back pain is a common reason for consultation in primary healthcare clinical practice, and has effects on daily activities and posture. Relationships between the whole spine and upright posture, however, remain unknown. The aim of this study was to identify the relationship between each spinal curve and centre of pressure position as well as velocity for healthy subjects. Twenty-one male subjects performed quiet stance in natural position. Each upright posture was then recorded using an optoelectronics system (Vicon Nexus) synchronized with two force plates. At each moment, polynomial interpolations of markers attached on the spine segment were used to compute cervical lordosis, thoracic kyphosis and lumbar lordosis angle curves. Mean of centre of pressure position and velocity was then computed. Multiple stepwise linear regression analysis showed that the position and velocity of centre of pressure associated with each part of the spinal curves were defined as best predictors of the lumbar lordosis angle (R(2)=0.45; p=1.65*10-10) and the thoracic kyphosis angle (R(2)=0.54; p=4.89*10-13) of healthy subjects in quiet stance. This study showed the relationships between each of cervical, thoracic, lumbar curvatures, and centre of pressure's fluctuation during free quiet standing using non-invasive full spinal curve exploration. Copyright © 2016 Elsevier Ltd. All rights reserved.
Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong
2011-01-21
Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.
Research on the multiple linear regression in non-invasive blood glucose measurement.
Zhu, Jianming; Chen, Zhencheng
2015-01-01
A non-invasive blood glucose measurement sensor and the data process algorithm based on the metabolic energy conservation (MEC) method are presented in this paper. The physiological parameters of human fingertip can be measured by various sensing modalities, and blood glucose value can be evaluated with the physiological parameters by the multiple linear regression analysis. Five methods such as enter, remove, forward, backward and stepwise in multiple linear regression were compared, and the backward method had the best performance. The best correlation coefficient was 0.876 with the standard error of the estimate 0.534, and the significance was 0.012 (sig. regression equation was valid. The Clarke error grid analysis was performed to compare the MEC method with the hexokinase method, using 200 data points. The correlation coefficient R was 0.867 and all of the points were located in Zone A and Zone B, which shows the MEC method provides a feasible and valid way for non-invasive blood glucose measurement.
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.
[Multiple linear regression analysis of X-ray measurement and WOMAC scores of knee osteoarthritis].
Ma, Yu-Feng; Wang, Qing-Fu; Chen, Zhao-Jun; Du, Chun-Lin; Li, Jun-Hai; Huang, Hu; Shi, Zong-Ting; Yin, Yue-Shan; Zhang, Lei; A-Di, Li-Jiang; Dong, Shi-Yu; Wu, Ji
2012-05-01
To perform Multiple Linear Regression analysis of X-ray measurement and WOMAC scores of knee osteoarthritis, and to analyze their relationship with clinical and biomechanical concepts. From March 2011 to July 2011, 140 patients (250 knees) were reviewed, including 132 knees in the left and 118 knees in the right; ranging in age from 40 to 71 years, with an average of 54.68 years. The MB-RULER measurement software was applied to measure femoral angle, tibial angle, femorotibial angle, joint gap angle from antero-posterir and lateral position of X-rays. The WOMAC scores were also collected. Then multiple regression equations was applied for the linear regression analysis of correlation between the X-ray measurement and WOMAC scores. There was statistical significance in the regression equation of AP X-rays value and WOMAC scores (Pregression equation of lateral X-ray value and WOMAC scores (P>0.05). 1) X-ray measurement of knee joint can reflect the WOMAC scores to a certain extent. 2) It is necessary to measure the X-ray mechanical axis of knee, which is important for diagnosis and treatment of osteoarthritis. 3) The correlation between tibial angle,joint gap angle on antero-posterior X-ray and WOMAC scores is significant, which can be used to assess the functional recovery of patients before and after treatment.
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.
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.)
Directory of Open Access Journals (Sweden)
Jose Isagani Janairo
2011-08-01
Full Text Available The activity of a selected class of DPP4 inhibitors was preliminarily assessed using chemical descriptors derived AM1 optimized geometries. Using multiple linear regression model, it was found that ?E0, LUMO energy, area, molecular weight and ?H0 are the significant descriptors that can adequately assess the binding affinity of the compounds. The derived multiple linear regression (MLR model was validated using rigorous statistical analysis. The preliminary model suggests that bulky and electrophilic inhibitors are desired.
Zhan, Xinhua; Liang, Xiao; Xu, Guohua; Zhou, Lixiang
2013-08-01
Polycyclic aromatic hydrocarbons (PAHs) are contaminants that reside mainly in surface soils. Dietary intake of plant-based foods can make a major contribution to total PAH exposure. Little information is available on the relationship between root morphology and plant uptake of PAHs. An understanding of plant root morphologic and compositional factors that affect root uptake of contaminants is important and can inform both agricultural (chemical contamination of crops) and engineering (phytoremediation) applications. Five crop plant species are grown hydroponically in solutions containing the PAH phenanthrene. Measurements are taken for 1) phenanthrene uptake, 2) root morphology--specific surface area, volume, surface area, tip number and total root length and 3) root tissue composition--water, lipid, protein and carbohydrate content. These factors are compared through Pearson's correlation and multiple linear regression analysis. The major factors which promote phenanthrene uptake are specific surface area and lipid content. Copyright © 2013 Elsevier Ltd. All rights reserved.
Ghazali, Nurul Adyani; Ramli, Nor Azam; Yahaya, Ahmad Shukri; Yusof, Noor Faizah Fitri M D; Sansuddin, Nurulilyana; Al Madhoun, Wesam Ahmed
2010-06-01
Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO(2)) into ozone (O(3)) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O(3) in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O(3) concentration was tested. Results indicated that the presence of NO(2) and sunshine influence the concentration of O(3) in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani
2016-09-14
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN) of 71 pure hydrocarbons and 54 hydrocarbon blends were utilized as a data set to study the relationship between ignition quality and molecular structure. CN and DCN are functional equivalents and collectively referred to as D/CN, herein. The effect of molecular weight and weight percent of structural parameters such as paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic CH–CH2 groups, naphthenic CH–CH2 groups, and aromatic C–CH groups on D/CN was studied. A particular emphasis on the effect of branching (i.e., methyl substitution) on the D/CN was studied, and a new parameter denoted as the branching index (BI) was introduced to quantify this effect. A new formula was developed to calculate the BI of hydrocarbon fuels using 1H NMR spectroscopy. Multiple linear regression (MLR) modeling was used to develop an empirical relationship between D/CN and the eight structural parameters. This was then used to predict the DCN of many hydrocarbon fuels. The developed model has a high correlation coefficient (R2 = 0.97) and was validated with experimentally measured DCN of twenty-two real fuel mixtures (e.g., gasolines and diesels) and fifty-nine blends of known composition, and the predicted values matched well with the experimental data.
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.
Multiple regression technique for Pth degree polynominals with and without linear cross products
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.
Linking teleconnection patterns to European temperature – a multiple linear regression model
Directory of Open Access Journals (Sweden)
Henning W. Rust
2015-04-01
Full Text Available The link between the indices of twelve atmospheric teleconnection patterns (mostly Northern Hemispheric and gridded European temperature data is investigated by means of multiple linear regression models for each grid cell and month. Furthermore index-specific signals are calculated to estimate the contribution to temperature anomalies caused by each individual teleconnection pattern. To this extent, an observational product of monthly mean temperature (E-OBS, as well as monthly time series of teleconnection indices (CPC, NOAA for the period 1951–2010 are evaluated. The stepwise regression approach is used to build grid cell based models for each month on the basis of the five most important teleconnection indices (NAO, EA, EAWR, SCAND, POLEUR, which are motivated by an exploratory correlation analysis. The temperature links are dominated by NAO and EA in Northern, Western, Central and South Western Europe, by EAWR during summer/autumn in Russia/Fenno-Scandia and by SCAND in Russia/Northern Europe; POLEUR shows minor effects only. In comparison to the climatological forecast, the presented linear regression models improve the temperature modelling by 30–40 % with better results in winter and spring. They can be used to model the spatial distribution and structure of observed temperature anomalies, where two to three patterns are the main contributors. As an example the estimated temperature signals induced by the teleconnection indices is shown for February 2010.
Deformations of the vacuum solutions of general relativity subjected to linear constraints
Molina, C.
2013-12-01
The problem of deforming geometries is particularly important in the context of constructing new exact solutions of Einstein’s equation. This issue often appears when extensions of the general relativity are treated, for instance in brane world scenarios. In this paper we investigate spacetimes in which the energy-momentum tensor obeys a linear constraint. Extensions of the usual vacuum and electrovacuum solutions of general relativity are derived and an exact solution is presented. The classes of geometries obtained include a wide variety of compact objects, among them black holes and wormholes. The general metric derived in this work generalizes several solutions already published in the literature. Perturbations around the exact solution are also considered.
Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah
2018-01-01
This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…
Modelling bivariate astronomical data with multiple components and non-linear relationships
Koen, C.; Bere, A.
2017-11-01
A common approach towards modelling bivariate scatterplots is decomposition into Gaussian components, I.e. Gaussian mixture modelling. This implicitly assumes linear relationships between the variables within each of the components in the mixture. An alternative, namely dependence modelling by mixtures of copulas, is advocated in this paper. This approach allows separate modelling of the univariate marginal distributions and the dependence which can possibly be non-linear and/or asymmetric. It also accommodates the use of a variety of parametric families for modelling each component and for each variable. The variety of dependence structures can be extended by introducing rotated versions of the copulas. Gaussian mixture modelling on the one hand, and separate modelling of univariate marginal distributions and dependence on the other hand, are illustrated by application to pulsar period - period-derivative observations. Parameter estimation for mixtures of copulas is performed using the method of maximum likelihood and selected copula models are subjected to non-parametric goodness-of-fit testing.
Croft, Arthur C; Milam, Bryce; Meylor, Jade; Manning, Richard
2016-06-01
Because of previously published recommendations to modify the Neck Disability Index (NDI), we evaluated the responsiveness and dimensionality of the NDI within a population of adult whiplash-injured subjects. The purpose of the present study was to evaluate the responsiveness and dimensionality of the NDI within a population of adult whiplash-injured subjects. Subjects who had sustained whiplash injuries of grade 2 or higher completed an NDI questionnaire. There were 123 subjects (55% female, of which 36% had recovered and 64% had chronic symptoms. NDI subscales were analyzed using confirmatory factor analysis, considering only the subscales and, secondly, using sex as an 11th variable. The subscales were also tested with multiple linear regression modeling using the total score as a target variable. When considering only the 10 NDI subscales, only a single factor emerged, with an eigenvalue of 5.4, explaining 53.7% of the total variance. Strong correlation (> .55) (P Multiple linear regression modeling revealed high internal consistency with all coefficients reaching significance (P < .0001). The 4 NDI subscales exerting the greatest effect were, in decreasing order, Sleeping, Lifting, Headaches, and Pain Intensity. A 2-factor model of the NDI is not justified based on our results, and in this population of whiplash subjects, the NDI was unidimensional, demonstrating high internal consistency and supporting the original validation study of Vernon and Mior.
Uyak, Vedat; Ozdemir, Kadir; Toroz, Ismail
2007-06-01
Oxidation of raw water with chlorine results in formation of trihalomethanes (THM) and haloacetic acids (HAA). Factors affecting their concentrations have been found to be organic matter type and concentration, pH, temperature, chlorine dose, contact time and bromide concentration, but the mechanisms of their formation are still under investigation. Within this scope, chlorination experiments have been conducted with water reservoirs from Terkos, Buyukcekmece and Omerli lakes, Istanbul, with different water quality regarding bromide concentration and organic matter content. The factors studied were pH, contact time, chlorine dose, and specific ultraviolet absorbance (SUVA). The determination of disinfection by-products (DBP) was carried out by gas chromatography techniques. Statistical analysis of the results was focused on the development of multiple regression models for predicting the concentrations of total THM and total HAA based on the use of pH, contact time, chlorine dose, and SUVA. The developed models provided satisfactory estimations of the concentrations of the DBP and the model regression coefficients of THM and HAA are 0.88 and 0.61, respectively. Further, the Durbin-Watson values confirm the reliability of the two models. The results indicate that under these experimental conditions which indicate the variations of pH, chlorine dosages, contact time, and SUVA values, the formation of THM and HAA in water can be described by the multiple linear regression technique.
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
Multiple functional linear model for association analysis of RNA-seq with imaging.
Jiang, Junhai; Lin, Nan; Guo, Shicheng; Chen, Jinyun; Xiong, Momiao
2015-06-01
Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel disease susceptibility genes which cannot be identified if they are analyzed separately. A key issue to the success of imaging and genomic data analysis is how to reduce their dimensions. Most previous methods for imaging information extraction and RNA-seq data reduction do not explore imaging spatial information and often ignore gene expression variation at the genomic positional level. To overcome these limitations, we extend functional principle component analysis from one dimension to two dimensions (2DFPCA) for representing imaging data and develop a multiple functional linear model (MFLM) in which functional principal scores of images are taken as multiple quantitative traits and RNA-seq profile across a gene is taken as a function predictor for assessing the association of gene expression with images. The developed method has been applied to image and RNA-seq data of ovarian cancer and kidney renal clear cell carcinoma (KIRC) studies. We identified 24 and 84 genes whose expressions were associated with imaging variations in ovarian cancer and KIRC studies, respectively. Our results showed that many significantly associated genes with images were not differentially expressed, but revealed their morphological and metabolic functions. The results also demonstrated that the peaks of the estimated regression coefficient function in the MFLM often allowed the discovery of splicing sites and multiple isoforms of gene expressions.
Inviscid linear stability analysis of two fluid columns of different densities subject to gravity
Prathama, Aditya; Pantano, Carlos
2017-11-01
We investigate the inviscid linear stability of vertical interface between two fluid columns of different densities under the influence of gravity. In this flow arrangement, the two free streams are continuously accelerating, in contrast to the canonical Kelvin-Helmholtz or Rayleigh-Taylor instabilities whose base flows are stationary (or weakly time dependent). In these classical cases, the temporal evolution of the interface can be expressed as Fourier or Laplace solutions in time. This is not possible in our case; instead, we employ the initial value problem method to solve the equations analytically. The results, expressed in terms of the well-known parabolic cylinder function, indicate that the instability grows as the exponential of a quadratic function of time. The analysis shows that in this accelerating Kelvin-Helmholtz configuration, the interface is unconditionally unstable at all wave modes, despite the presence of surface tension. Department of Energy, National Nuclear Security Administration (Award No. DE-NA0002382) and the California Institute of Technology.
Arulsudar, N; Subramanian, N; Muthy, R S R
2005-08-05
We planned to optimize the effect of formulation variables on the percent drug entrapment (PDE) of the liposomes encapsulating leuprolide acetate by reverse phase evaporation method using Artificial neural network (ANN) and Multiple linear regression (MLR). Twenty seven formulations were prepared based on 3x3 factorial design. The volume of aqueous phase (X(1)), HSPC/DSPG [negative charge] (X(2)), and HSPC/Cholesterol (X(3)) were selected as the causal factors. Potential variables such as concentration of lipid: drug and hydration medium were kept constant in experimental design. The PDE (dependent variable) and the transformed values of independent variables were subjected to multiple regression analysis to establish a second order polynomial equation (full model). A set of PDE and causal factors was used as tutorial data for the ANN and fed into a computer. The feed forward back propagation (bp) method was optimized. The ANN model and MLR were validated for accurate prediction of PDE. To simplify the polynomial equation, F-statistic was applied to reduce polynomial equation (reduced model) by neglecting non-significant (Pexperimental data were compared with predicted data by paired "t" test, no statistically significant difference was observed. ANN showed less error compared to MLR. These findings demonstrate that the ANN model provides more accurate prediction and is quite useful in the optimization of pharmaceutical formulations when compared to multiple regression analysis method. The normalized error (NE) value observed with the optimal ANN model was 0.0211 while it was 0.0658 for the full model in the case of second-order polynomial equation composed of the combination of causal factors (X(1), X(2) and X(3)). Thus the derived equation, contour plots and ANN helps in predicting the values of the independent variables for maximum PDE in the preparation of leuprolide acetate liposomes by reverse phase evaporation technique.
Directory of Open Access Journals (Sweden)
Jesús Vega Encabo
2015-11-01
Full Text Available In this paper, I claim that subjectivity is a way of being that is constituted through a set of practices in which the self is subject to the dangers of fictionalizing and plotting her life and self-image. I examine some ways of becoming subject through narratives and through theatrical performance before others. Through these practices, a real and active subjectivity is revealed, capable of self-knowledge and self-transformation.
Liu, Qingshan; Wang, Jun
2013-05-01
This paper presents a one-layer projection neural network for solving nonsmooth optimization problems with generalized convex objective functions and subject to linear equalities and bound constraints. The proposed neural network is designed based on two projection operators: linear equality constraints, and bound constraints. The objective function in the optimization problem can be any nonsmooth function which is not restricted to be convex but is required to be convex (pseudoconvex) on a set defined by the constraints. Compared with existing recurrent neural networks for nonsmooth optimization, the proposed model does not have any design parameter, which is more convenient for design and implementation. It is proved that the output variables of the proposed neural network are globally convergent to the optimal solutions provided that the objective function is at least pseudoconvex. Simulation results of numerical examples are discussed to demonstrate the effectiveness and characteristics of the proposed neural network.
Anastasopoulos, D; Gianna, C C; Bronstein, A M; Gresty, M A
1996-08-01
The possibility of synergistic interaction between the canal and otolith components of the horizontal vestibulo-ocular reflex (VOR) was evaluated in human subjects by subtracting the response to pure angular rotation (AVOR) from the response to combined angular and translational motion (ALVOR) and comparing this difference with the VOR to isolated linear motion (LVOR). Assessments were made with target fixation at 60 cm and in darkness. Linear stimuli were acceleration steps attaining 0.25 g in less than 80 ms. To elicit responses to combined translational and angular head movements, the subjects were seated on a Barany chair with the head displaced forwards 40 cm from the axis of rotation. The chair was accelerated at approximately 300 deg/s2 to 127 deg/s peak angular velocity, the tangential acceleration of the head being comparable with that of isolated translation. Estimates of the contribution of smooth pursuit to responses in the light were made from comparisons of isolated pursuit of similar target trajectories. In the dark the slow phase eye movements evoked by combined canal-otolith stimuli were higher in magnitude by approximately a third than the sum of those produced by translation and rotation alone. In the light, the relative target displacement during isolated linear motion was similar to the difference in relative target displacements during eccentric and centred rotation. However, the gain of the translational component of compensatory eye movement during combined translational and angular motion was approximately unity, in contrast to the gain of the response to isolated linear motion, which was approximately a half. Pursuit performance was always poorer than target following during self-motion. The LVOR responses in the light were greater than the sum of the LVOR responses in the dark with pursuit eye movements. We conclude that, in response to transient motion, there is a synergistic enhancement of the translational VOR with concurrent canal
Smith, Paul F; Ganesh, Siva; Liu, Ping
2013-10-30
Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.
Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen
2012-06-01
To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.
Multivariate linear regression of high-dimensional fMRI data with multiple target variables.
Valente, Giancarlo; Castellanos, Agustin Lage; Vanacore, Gianluca; Formisano, Elia
2014-05-01
Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets. Copyright © 2013 Wiley Periodicals, Inc.
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.
On the Relationship Between Confidence Sets and Exchangeable Weights in Multiple Linear Regression.
Pek, Jolynn; Chalmers, R Philip; Monette, Georges
2016-01-01
When statistical models are employed to provide a parsimonious description of empirical relationships, the extent to which strong conclusions can be drawn rests on quantifying the uncertainty in parameter estimates. In multiple linear regression (MLR), regression weights carry two kinds of uncertainty represented by confidence sets (CSs) and exchangeable weights (EWs). Confidence sets quantify uncertainty in estimation whereas the set of EWs quantify uncertainty in the substantive interpretation of regression weights. As CSs and EWs share certain commonalities, we clarify the relationship between these two kinds of uncertainty about regression weights. We introduce a general framework describing how CSs and the set of EWs for regression weights are estimated from the likelihood-based and Wald-type approach, and establish the analytical relationship between CSs and sets of EWs. With empirical examples on posttraumatic growth of caregivers (Cadell et al., 2014; Schneider, Steele, Cadell & Hemsworth, 2011) and on graduate grade point average (Kuncel, Hezlett & Ones, 2001), we illustrate the usefulness of CSs and EWs for drawing strong scientific conclusions. We discuss the importance of considering both CSs and EWs as part of the scientific process, and provide an Online Appendix with R code for estimating Wald-type CSs and EWs for k regression weights.
Liu, Ke; Chen, Xiaojing; Li, Limin; Chen, Huiling; Ruan, Xiukai; Liu, Wenbin
2015-02-09
The successive projections algorithm (SPA) is widely used to select variables for multiple linear regression (MLR) modeling. However, SPA used only once may not obtain all the useful information of the full spectra, because the number of selected variables cannot exceed the number of calibration samples in the SPA algorithm. Therefore, the SPA-MLR method risks the loss of useful information. To make a full use of the useful information in the spectra, a new method named "consensus SPA-MLR" (C-SPA-MLR) is proposed herein. This method is the combination of consensus strategy and SPA-MLR method. In the C-SPA-MLR method, SPA-MLR is used to construct member models with different subsets of variables, which are selected from the remaining variables iteratively. A consensus prediction is obtained by combining the predictions of the member models. The proposed method is evaluated by analyzing the near infrared (NIR) spectra of corn and diesel. The results of C-SPA-MLR method showed a better prediction performance compared with the SPA-MLR and full-spectra PLS methods. Moreover, these results could serve as a reference for combination the consensus strategy and other variable selection methods when analyzing NIR spectra and other spectroscopic techniques. Copyright © 2014 Elsevier B.V. All rights reserved.
Kitamura, Takayuki; Ogawa, Makoto; Otsuji, Mikiya; Ohno, Nagara; Saito, Yuichiro; Yamada, Yoshitsugu
2008-12-01
Predictability of the extent of spinal anesthesia by plain bupivacaine has been controversial. Two hundred and twenty-eight patients undergoing elective surgery with spinal anesthesia were enrolled in this retrospective study. Using gender, age, height, body mass index (BMI), chosen spinal interspace for spinal tap (L2-3 or L3-4), and dose of plain bupivacaine as independent variables, we performed stepwise multiple linear regression analysis to examine predictability of the extent of sensory blockade produced by spinal anesthesia using plain bupivacaine. Following equation was obtained. Extent of sensory blockade = 14.9 + (male : 0.540, female: -0.540) -0.0774 x height + 0.124 x BMI + (L2-3 : 0.345, L3-4: -0.345): r2 = 0.0604. P values of gender, height and BMI were less than 0.05; however, r2 of each variable was very low. Results of this retrospective study imply the unpredictability of the extent of spinal anesthesia produced by plain bupivacaine.
MLR-tagging: informative SNP selection for unphased genotypes based on multiple linear regression.
He, Jingwu; Zelikovsky, Alexander
2006-10-15
The search for the association between complex diseases and single nucleotide polymorphisms (SNPs) or haplotypes has recently received great attention. For these studies, it is essential to use a small subset of informative SNPs accurately representing the rest of the SNPs. Informative SNP selection can achieve (1) considerable budget savings by genotyping only a limited number of SNPs and computationally inferring all other SNPs or (2) necessary reduction of the huge SNP sets (obtained, e.g. from Affymetrix) for further fine haplotype analysis. A novel informative SNP selection method for unphased genotype data based on multiple linear regression (MLR) is implemented in the software package MLR-tagging. This software can be used for informative SNP (tag) selection and genotype prediction. The stepwise tag selection algorithm (STSA) selects positions of the given number of informative SNPs based on a genotype sample population. The MLR SNP prediction algorithm predicts a complete genotype based on the values of its informative SNPs, their positions among all SNPs, and a sample of complete genotypes. An extensive experimental study on various datasets including 10 regions from HapMap shows that the MLR prediction combined with stepwise tag selection uses fewer tags than the state-of-the-art method of Halperin et al. (2005). MLR-Tagging software package is publicly available at http://alla.cs.gsu.edu/~software/tagging/tagging.html
Directory of Open Access Journals (Sweden)
Qiutong Jin
2016-06-01
Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.
Forecasting on the total volumes of Malaysia's imports and exports by multiple linear regression
Beh, W. L.; Yong, M. K. Au
2017-04-01
This study is to give an insight on the doubt of the important of macroeconomic variables that affecting the total volumes of Malaysia's imports and exports by using multiple linear regression (MLR) analysis. The time frame for this study will be determined by using quarterly data of the total volumes of Malaysia's imports and exports covering the period between 2000-2015. The macroeconomic variables will be limited to eleven variables which are the exchange rate of US Dollar with Malaysia Ringgit (USD-MYR), exchange rate of China Yuan with Malaysia Ringgit (RMB-MYR), exchange rate of European Euro with Malaysia Ringgit (EUR-MYR), exchange rate of Singapore Dollar with Malaysia Ringgit (SGD-MYR), crude oil prices, gold prices, producer price index (PPI), interest rate, consumer price index (CPI), industrial production index (IPI) and gross domestic product (GDP). This study has applied the Johansen Co-integration test to investigate the relationship among the total volumes to Malaysia's imports and exports. The result shows that crude oil prices, RMB-MYR, EUR-MYR and IPI play important roles in the total volumes of Malaysia's imports. Meanwhile crude oil price, USD-MYR and GDP play important roles in the total volumes of Malaysia's exports.
Directory of Open Access Journals (Sweden)
Adi Syahputra
2014-03-01
Full Text Available Quantitative structure activity relationship (QSAR for 21 insecticides of phthalamides containing hydrazone (PCH was studied using multiple linear regression (MLR, principle component regression (PCR and artificial neural network (ANN. Five descriptors were included in the model for MLR and ANN analysis, and five latent variables obtained from principle component analysis (PCA were used in PCR analysis. Calculation of descriptors was performed using semi-empirical PM6 method. ANN analysis was found to be superior statistical technique compared to the other methods and gave a good correlation between descriptors and activity (r2 = 0.84. Based on the obtained model, we have successfully designed some new insecticides with higher predicted activity than those of previously synthesized compounds, e.g.2-(decalinecarbamoyl-5-chloro-N’-((5-methylthiophen-2-ylmethylene benzohydrazide, 2-(decalinecarbamoyl-5-chloro-N’-((thiophen-2-yl-methylene benzohydrazide and 2-(decaline carbamoyl-N’-(4-fluorobenzylidene-5-chlorobenzohydrazide with predicted log LC50 of 1.640, 1.672, and 1.769 respectively.
Multiple linear and principal component regressions for modelling ecotoxicity bioassay response.
Gomes, Ana I; Pires, José C M; Figueiredo, Sónia A; Boaventura, Rui A R
2014-01-01
The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response. With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.
Directory of Open Access Journals (Sweden)
Rachid Darnag
2017-02-01
Full Text Available Support vector machines (SVM represent one of the most promising Machine Learning (ML tools that can be applied to develop a predictive quantitative structure–activity relationship (QSAR models using molecular descriptors. Multiple linear regression (MLR and artificial neural networks (ANNs were also utilized to construct quantitative linear and non linear models to compare with the results obtained by SVM. The prediction results are in good agreement with the experimental value of HIV activity; also, the results reveal the superiority of the SVM over MLR and ANN model. The contribution of each descriptor to the structure–activity relationships was evaluated.
Modeling of Soil Aggregate Stability using Support Vector Machines and Multiple Linear Regression
Directory of Open Access Journals (Sweden)
Ali Asghar Besalatpour
2016-02-01
Full Text Available Introduction: Soil aggregate stability is a key factor in soil resistivity to mechanical stresses, including the impacts of rainfall and surface runoff, and thus to water erosion (Canasveras et al., 2010. Various indicators have been proposed to characterize and quantify soil aggregate stability, for example percentage of water-stable aggregates (WSA, mean weight diameter (MWD, geometric mean diameter (GMD of aggregates, and water-dispersible clay (WDC content (Calero et al., 2008. Unfortunately, the experimental methods available to determine these indicators are laborious, time-consuming and difficult to standardize (Canasveras et al., 2010. Therefore, it would be advantageous if aggregate stability could be predicted indirectly from more easily available data (Besalatpour et al., 2014. The main objective of this study is to investigate the potential use of support vector machines (SVMs method for estimating soil aggregate stability (as quantified by GMD as compared to multiple linear regression approach. Materials and Methods: The study area was part of the Bazoft watershed (31° 37′ to 32° 39′ N and 49° 34′ to 50° 32′ E, which is located in the Northern part of the Karun river basin in central Iran. A total of 160 soil samples were collected from the top 5 cm of soil surface. Some easily available characteristics including topographic, vegetation, and soil properties were used as inputs. Soil organic matter (SOM content was determined by the Walkley-Black method (Nelson & Sommers, 1986. Particle size distribution in the soil samples (clay, silt, sand, fine sand, and very fine sand were measured using the procedure described by Gee & Bauder (1986 and calcium carbonate equivalent (CCE content was determined by the back-titration method (Nelson, 1982. The modified Kemper & Rosenau (1986 method was used to determine wet-aggregate stability (GMD. The topographic attributes of elevation, slope, and aspect were characterized using a 20-m
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 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.
Analysis of oil-pipeline distribution of multiple products subject to delivery time-windows
Jittamai, Phongchai
This dissertation defines the operational problems of, and develops solution methodologies for, a distribution of multiple products into oil pipeline subject to delivery time-windows constraints. A multiple-product oil pipeline is a pipeline system composing of pipes, pumps, valves and storage facilities used to transport different types of liquids. Typically, products delivered by pipelines are petroleum of different grades moving either from production facilities to refineries or from refineries to distributors. Time-windows, which are generally used in logistics and scheduling areas, are incorporated in this study. The distribution of multiple products into oil pipeline subject to delivery time-windows is modeled as multicommodity network flow structure and mathematically formulated. The main focus of this dissertation is the investigation of operating issues and problem complexity of single-source pipeline problems and also providing solution methodology to compute input schedule that yields minimum total time violation from due delivery time-windows. The problem is proved to be NP-complete. The heuristic approach, a reversed-flow algorithm, is developed based on pipeline flow reversibility to compute input schedule for the pipeline problem. This algorithm is implemented in no longer than O(T·E) time. This dissertation also extends the study to examine some operating attributes and problem complexity of multiple-source pipelines. The multiple-source pipeline problem is also NP-complete. A heuristic algorithm modified from the one used in single-source pipeline problems is introduced. This algorithm can also be implemented in no longer than O(T·E) time. Computational results are presented for both methodologies on randomly generated problem sets. The computational experience indicates that reversed-flow algorithms provide good solutions in comparison with the optimal solutions. Only 25% of the problems tested were more than 30% greater than optimal values and
Zainudin, Suhaila; Arif, Shereena M.
2017-01-01
Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767
Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M
2017-01-01
Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.
Wang, J; Wang, F; Liu, Y; Xu, J; Lin, H; Jia, B; Zuo, W; Jiang, Y; Hu, L; Lin, F
2016-01-01
Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose prediction model tailored to overweight patients. A total of 346 overweight Chinese people patients ages 18-81 years were involved in this study. Their levels of fasting glucose (fs-GLU), blood lipids, and hepatic and renal functions were measured and analyzed by multiple linear regression (MLR). Based the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tansig as the transfer function of the hidden layers nodes, and purelin for the output layer nodes, with training goal of 0.5×10(-5). There was significant correlation between fs-GLU with age, BMI, and blood biochemical indexes (P<0.05). The results of MLR analysis indicated that age, fasting alanine transaminase (fs-ALT), blood urea nitrogen (fs-BUN), total protein (fs-TP), uric acid (fs-BUN), and BMI are 6 independent variables related to fs-GLU. Based on these parameters, the BP-ANN model was performed well and reached high prediction accuracy when training 1 000 epoch (R=0.9987). The level of fs-GLU was predictable using the proposed BP-ANN model based on 6 related parameters (age, fs-ALT, fs-BUN, fs-TP, fs-UA and BMI) in overweight patients. © Georg Thieme Verlag KG Stuttgart · New York.
Liu, Pudong; Shi, Runhe; Wang, Hong; Bai, Kaixu; Gao, Wei
2014-10-01
Leaf pigments are key elements for plant photosynthesis and growth. Traditional manual sampling of these pigments is labor-intensive and costly, which also has the difficulty in capturing their temporal and spatial characteristics. The aim of this work is to estimate photosynthetic pigments at large scale by remote sensing. For this purpose, inverse model were proposed with the aid of stepwise multiple linear regression (SMLR) analysis. Furthermore, a leaf radiative transfer model (i.e. PROSPECT model) was employed to simulate the leaf reflectance where wavelength varies from 400 to 780 nm at 1 nm interval, and then these values were treated as the data from remote sensing observations. Meanwhile, simulated chlorophyll concentration (Cab), carotenoid concentration (Car) and their ratio (Cab/Car) were taken as target to build the regression model respectively. In this study, a total of 4000 samples were simulated via PROSPECT with different Cab, Car and leaf mesophyll structures as 70% of these samples were applied for training while the last 30% for model validation. Reflectance (r) and its mathematic transformations (1/r and log (1/r)) were all employed to build regression model respectively. Results showed fair agreements between pigments and simulated reflectance with all adjusted coefficients of determination (R2) larger than 0.8 as 6 wavebands were selected to build the SMLR model. The largest value of R2 for Cab, Car and Cab/Car are 0.8845, 0.876 and 0.8765, respectively. Meanwhile, mathematic transformations of reflectance showed little influence on regression accuracy. We concluded that it was feasible to estimate the chlorophyll and carotenoids and their ratio based on statistical model with leaf reflectance data.
Directory of Open Access Journals (Sweden)
Faridah Hani Mohamed Salleh
2017-01-01
Full Text Available Gene regulatory network (GRN reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C as a direct interaction (A → C. Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.
Fushimi, Akihiro; Kawashima, Hiroto; Kajihara, Hideo
Understanding the contribution of each emission source of air pollutants to ambient concentrations is important to establish effective measures for risk reduction. We have developed a source apportionment method based on an atmospheric dispersion model and multiple linear regression analysis (MLR) in conjunction with ambient concentrations simultaneously measured at points in a grid network. We used a Gaussian plume dispersion model developed by the US Environmental Protection Agency called the Industrial Source Complex model (ISC) in the method. Our method does not require emission amounts or source profiles. The method was applied to the case of benzene in the vicinity of the Keiyo Central Coastal Industrial Complex (KCCIC), one of the biggest industrial complexes in Japan. Benzene concentrations were simultaneously measured from December 2001 to July 2002 at sites in a grid network established in the KCCIC and the surrounding residential area. The method was used to estimate benzene emissions from the factories in the KCCIC and from automobiles along a section of a road, and then the annual average contribution of the KCCIC to the ambient concentrations was estimated based on the estimated emissions. The estimated contributions of the KCCIC were 65% inside the complex, 49% at 0.5-km sites, 35% at 1.5-km sites, 20% at 3.3-km sites, and 9% at a 5.6-km site. The estimated concentrations agreed well with the measured values. The estimated emissions from the factories and the road were slightly larger than those reported in the first Pollutant Release and Transfer Register (PRTR). These results support the reliability of our method. This method can be applied to other chemicals or regions to achieve reasonable source apportionments.
Bajpai, R P; Drexel, M
2008-12-01
Spontaneous photon signals from four sites of a human subject suffering from multiple sclerosis were detected in 3600 bins of 50 milliseconds by a photo multiplier sensitive in 160-630 nm, before and after a session of colorpuncture treatment. Measurements were made in 22 sessions over a period of 9 months. Each signal was analyzed to determine if it was a quantum signal in a squeezed state. The analysis first generates 10 signals of bin sizes (50 to 500 milliseconds at 50 millisecond intervals) by merging the counts at contiguous bins of the observed signal and then estimates three squeezed state parameters (r, theta and phi) in these ten signals and nine other combinations of signals. All estimations yield r=2.72.10(-10), theta = 101.91 degrees and phi = 69.53 degrees for TolX=10(-8) in every signal of a healthy subject. These are normal values of the parameters. Other values of parameters in a signal of any estimation indicate some ailment. The deviation from the squeezed state description of a signal is quantified by a new property, "coherency index", which appears to be a good indicator of health. A session of colorpuncture treatment changed coherency indices of signals from different sides and provided relief to the subject suffering from multiple sclerosis. The changes in coherency indices and relief were temporary. Changes in coherency indices lasting for longer periods occurred after many sessions of treatment.
Gong, Jing-Feng; Chan, Philip C. H.
2008-02-01
In this paper, we investigate the linearity of undoped body multi-gate independent FinFET (MIGFET) experimentally. The MIGFET device with sub-50 nm body thickness is fabricated on SOI wafers. The device transconductance and its high order derivatives under different bias conditions are measured. RF two-tone inter-modulation distortion measurements are performed. Both the DC and RF measurements demonstrate that the properly biased asymmetric MIGFET provides better linearity performance than that of symmetric MIGFET biased at the conventional moderate inversion linearity "sweet spot". The improved linearity is explained.
Directory of Open Access Journals (Sweden)
Arun Kumar Gupta
2014-01-01
Full Text Available The present paper deals with the free transverse vibration of orthotropic thin trapezoidal plate of parabolically varying thickness in x-direction subjected to linear temperature distribution in x-direction through a numerical method. The deflection function is defined by the product of the equations of the prescribed continuous piecewise boundary shape. Rayleigh-Ritz method is used to evaluate the fundamental frequencies. The equations of motion, governing the free transverse vibrations of orthotropic thin trapezoidal plates, are derived with boundary condition CSCS. Frequency corresponding to the first two modes of vibration is calculated for the orthotropic thin trapezoidal plate having CSCS edges for different values of thermal gradient, taper constant, and aspect ratio. The proposed method is applied to solve orthotropic thin trapezoidal plate of variable thickness with C-S-C-S boundary conditions. Results are shown by figures for different values of thermal gradient, taper constant, and aspect ratio for the first two modes of vibrations.
Prior, J. G.; Berry, D.; Cochrane, G. M.
1980-01-01
In normal subjects, receiving multiple dosing regimens with Slophyllin and Phyllocontin in does calculated to give either 4 mg/kg or 6mg/kg theophylline free acid twice daily, serum theophylline concentrations were frequently less than 8 mg/l. Accumulation of the serum theophylline trough concentration occurred during the first 3 days of multiple dosing, and was followed by subsequent stabilization or even decline in serum theophylline trough concentrations. Side effects were noted with both Slophyllin and Phyllocontin, but only on the higher dosage regimens; they occurred within 24--48 hr of starting the drug, and tended to diminish if dosing was continued. The accumulation effect of serum theophylline concentrations may explain the timing of adverse effects, and should be avoided by starting methylxanthine therapy at a low dose. This may be increased after a few days. Further dosage adjustment may be necessary in some patients and should be facilitated by measurement of serum theophylline trough concentrations. PMID:7465472
Prasad, C. B.; Mei, Chuh
1987-01-01
Multiple-mode nonlinear analysis is carried out for beams subjected to acoustic excitation. Effects of both nonlinear damping and large-deflection are included in the analysis in an attempt to explain the experimental phenomena of aircraft panels excited at high sound pressure levels; that is the broadening of the strain response peaks and the increase of modal frequency. An amplitude dependent nonlinear damping model is used in the anlaysis to study the effects and interactions of multiple modes, nonlinear stiffness and nonlinear damping on the random response of beams. Mean square maximum deflection, mean square maximum strain, and spectral density function of maximum strain for simple supported and clamped beams are obtained. It is shown analytically that nonlinear damping contributes significantly to the broadening of the response peak and to the mean square deflection and strain.
Cass, Robert T; Brooks, Carter D; Havrilla, Nancy A; Tack, Kenneth J; Borin, Marie T; Young, Don; Bruss, Jon B
2011-12-01
ACHN-490 is an aminoglycoside with activity against multidrug-resistant pathogens, including those resistant to currently used aminoglycosides. Two randomized, double-blind, placebo-controlled clinical studies investigated the pharmacokinetics (PK), safety, and tolerability of ACHN-490 injection in healthy subjects. Study 1 used a parallel-group design with escalating single (SD) and multiple doses (MD). Study 2 explored a longer duration of the highest dose tolerated in the first study. Subjects were randomly assigned to receive either ACHN-490 injection or a placebo administered by a 10-min intravenous infusion. Study 1 enrolled 39 subjects (30 active and 9 placebo) and consisted of a single dose of 1 mg/kg body weight followed by ascending SD and MD cohorts of 4, 7, 11, and 15 mg/kg for 10, 10, 5, and 3 days, respectively. Study 2 enrolled 8 subjects (6 active and 2 placebo) who received 15 mg/kg for 5 days. Safety was assessed from adverse event (AE) reporting, standard clinical laboratory procedures, and testing for renal, cochlear, and vestibular function. ACHN-490 exhibited linear and dose-proportional PK, with agreement between the studies for PK parameters assessed. The 15-mg/kg dose did not accumulate with repeated dosing over 5 days. Mean steady-state (±standard deviation) area under the concentration-time curve from 0 to 24 h (AUC(0-24)), maximum concentration of drug in serum (C(max)), half-life (t(1/2)), clearance, and volume of distribution at steady state (V(ss)) for the 15-mg/kg, day 5 dose were 239 ± 45 h·mg/liter, 113 ± 17 mg/liter, 3 ± 0.3 h, 1.1 ± 0.1 ml/min/kg, and 0.24 ± 0.04 liters/kg, respectively. AEs were mild to moderate and rapidly resolved. No evidence of nephrotoxicity or ototoxicity was observed.
Gong, Qi; Schaubel, Douglas E
2018-01-22
Mean survival time is often of inherent interest in medical and epidemiologic studies. In the presence of censoring and when covariate effects are of interest, Cox regression is the strong default, but mostly due to convenience and familiarity. When survival times are uncensored, covariate effects can be estimated as differences in mean survival through linear regression. Tobit regression can validly be performed through maximum likelihood when the censoring times are fixed (ie, known for each subject, even in cases where the outcome is observed). However, Tobit regression is generally inapplicable when the response is subject to random right censoring. We propose Tobit regression methods based on weighted maximum likelihood which are applicable to survival times subject to both fixed and random censoring times. Under the proposed approach, known right censoring is handled naturally through the Tobit model, with inverse probability of censoring weighting used to overcome random censoring. Essentially, the re-weighting data are intended to represent those that would have been observed in the absence of random censoring. We develop methods for estimating the Tobit regression parameter, then the population mean survival time. A closed form large-sample variance estimator is proposed for the regression parameter estimator, with a semiparametric bootstrap standard error estimator derived for the population mean. The proposed methods are easily implementable using standard software. Finite-sample properties are assessed through simulation. The methods are applied to a large cohort of patients wait-listed for kidney transplantation. Copyright © 2018 John Wiley & Sons, Ltd.
Multiple skin neoplasms in subjects under 40 years of age in Goiania, Brazil
Pereira, Samir; Curado, Maria Paula; Ribeiro, Ana Maria Quinteiro
2015-01-01
OBJECTIVE To describe the trend for malignant skin neoplasms in subjects under 40 years of age in a region with high ultraviolet radiation indices. METHODS A descriptive epidemiological study on melanoma and nonmelanoma skin cancers that was conducted in Goiania, Midwest Brazil, with 1,688 people under 40 years of age, between 1988 and 2009. Cases were obtained from Registro de Câncer de Base Populacional de Goiânia (Goiania’s Population-Based Cancer File). Frequency, trends, and incidence of cases with single and multiple lesions were analyzed; transplants and genetic skin diseases were found in cases with multiple lesions. RESULTS Over the period, 1,995 skin cancer cases were observed to found, of which 1,524 (90.3%) cases had single lesions and 164 (9.7%) had multiple lesions. Regarding single lesions, incidence on men was observed to have risen from 2.4 to 3.1/100,000 inhabitants; it differed significantly for women, shifting from 2.3 to 5.3/100,000 (Annual percentage change – [APC] 3.0%, p = 0.006). Regarding multiple lesions, incidence on men was observed to have risen from 0.30 to 0.98/100,000 inhabitants; for women, it rose from 0.43 to 1.16/100,000 (APC 8.6%, p = 0.003). Genetic skin diseases or transplants were found to have been correlated with 10.0% of cases with multiple lesions – an average of 5.1 lesions per patient. The average was 2.5 in cases without that correlation. CONCLUSIONS Skin cancer on women under 40 years of age has been observed to be increasing for both cases with single and multiple lesions. It is not unusual to find multiple tumors in young people – in most cases, they are not associated with genetic skin diseases or transplants. It is necessary to avoid excessive exposure to ultraviolet radiation from childhood. PMID:26465667
Directory of Open Access Journals (Sweden)
Rohan PATEL
2012-03-01
Full Text Available Polyethylene glycol (PEG is the most common preservative in use for bulking and maintaining structural integrity in waterlogged wood. Conservators therefore have a need to be able to determine PEG concentrations in wood in a non-destructive manner. We present a study highlighting the application of infrared spectroscopy coupled with multivariate analysis techniques to predict the concentration of polyethylene glycol 400 (PEG-400 and water simultaneously. This technique uses attenuated total reflectance (ATR spectroscopy andunconstrained stepwise multiple linear regression (SMLR analysis for prediction of multiple components in archaeological wood. Using this model we have calculated the concentration of PEG-400 and water in treated archaeological waterlogged wood samples.
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.
Directory of Open Access Journals (Sweden)
Roshan Lal
2013-01-01
Full Text Available The present work analyses the buckling and vibration behaviour of non-homogeneous rectangular plates of uniform thickness on the basis of classical plate theory when the two opposite edges are simply supported and are subjected to linearly varying in-plane force. For non-homogeneity of the plate material it is assumed that young's modulus and density of the plate material vary exponentially along axial direction. The governing partial differential equation of motion of such plates has been reduced to an ordinary differential equation using the sine function for mode shapes between the simply supported edges. This resulting equation has been solved numerically employing differential quadrature method for three different combinations of clamped, simply supported and free boundary conditions at the other two edges. The effect of various parameters has been studied on the natural frequencies for the first three modes of vibration. Critical buckling loads have been computed. Three dimensional mode shapes have been presented. Comparison has been made with the known results.
Energy Technology Data Exchange (ETDEWEB)
Wiesner, W.; Steinbrich, W. [Institute of Diagnostic Radiology, University Hospital of Basel (Switzerland); Wetzel, S.G.; Radue, E.W. [Institute of Neuroradiology, University Hospital Basel (Switzerland); Kappos, L.; Hoshi, M.M. [Department of Neurology, University Hospital of Basel (Switzerland); Witte, U. [Section of Logopedia, University Hospital of Basel (Switzerland)
2002-04-01
The purpose of this study was to evaluate if subjective symptoms indicating an impaired deglutition correlate with videofluoroscopic findings in patients with multiple sclerosis (MS). Videofluoroscopic examinations of 18 MS patients were analyzed by a radiologist and a logopedist and compared with the symptoms of these patients. Four patients complained about permanent dysphagia. Six patients reported mild and intermittent difficulties in swallowing, but were asymptomatic at the time of videofluoroscopy. Eight patients had no symptoms regarding their deglutition. All patients (n=4) who complained of permanent dysphagia showed aspiration. All patients (n=6) with mild and intermittent difficulties in swallowing showed undercoating of the epiglottis and/or laryngeal penetration. Of those 8 patients without any swallowing symptoms, only 2 had a normal videofluoroscopy. Swallowing abnormalities seem to be much more frequent in patients with MS than generally believed and they may easily be missed clinically as long as the patients do not aspirate. (orig.)
Directory of Open Access Journals (Sweden)
Nengjun Yi
2011-12-01
Full Text Available Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The proposed hierarchical generalized linear models introduce a group effect and a genetic score (i.e., a linear combination of main-effect predictors for genetic variants for each group of variants, and jointly they estimate the group effects and the weights of the genetic scores. This framework includes various previous methods as special cases, and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance. Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models, leading to the development of stable and flexible tools. The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/.
Yi, Nengjun; Liu, Nianjun; Zhi, Degui; Li, Jun
2011-12-01
Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The proposed hierarchical generalized linear models introduce a group effect and a genetic score (i.e., a linear combination of main-effect predictors for genetic variants) for each group of variants, and jointly they estimate the group effects and the weights of the genetic scores. This framework includes various previous methods as special cases, and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance. Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models, leading to the development of stable and flexible tools. The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/).
Directory of Open Access Journals (Sweden)
V.C. Kunz
2012-05-01
Full Text Available The objectives of this study were to evaluate and compare the use of linear and nonlinear methods for analysis of heart rate variability (HRV in healthy subjects and in patients after acute myocardial infarction (AMI. Heart rate (HR was recorded for 15 min in the supine position in 10 patients with AMI taking β-blockers (aged 57 ± 9 years and in 11 healthy subjects (aged 53 ± 4 years. HRV was analyzed in the time domain (RMSSD and RMSM, the frequency domain using low- and high-frequency bands in normalized units (nu; LFnu and HFnu and the LF/HF ratio and approximate entropy (ApEn were determined. There was a correlation (P < 0.05 of RMSSD, RMSM, LFnu, HFnu, and the LF/HF ratio index with the ApEn of the AMI group on the 2nd (r = 0.87, 0.65, 0.72, 0.72, and 0.64 and 7th day (r = 0.88, 0.70, 0.69, 0.69, and 0.87 and of the healthy group (r = 0.63, 0.71, 0.63, 0.63, and 0.74, respectively. The median HRV indexes of the AMI group on the 2nd and 7th day differed from the healthy group (P < 0.05: RMSSD = 10.37, 19.95, 24.81; RMSM = 23.47, 31.96, 43.79; LFnu = 0.79, 0.79, 0.62; HFnu = 0.20, 0.20, 0.37; LF/HF ratio = 3.87, 3.94, 1.65; ApEn = 1.01, 1.24, 1.31, respectively. There was agreement between the methods, suggesting that these have the same power to evaluate autonomic modulation of HR in both AMI patients and healthy subjects. AMI contributed to a reduction in cardiac signal irregularity, higher sympathetic modulation and lower vagal modulation.
Roerdink, J.B.T.M.
1981-01-01
The cumulant expansion for linear stochastic differential equations is extended to the general case in which the coefficient matrix, the inhomogeneous part and the initial condition are all random and, moreover, statistically interdependent. The expansion now involves not only the autocorrelation
Atanasova, I; Bozhinova, K; Terziivanov, D
1999-06-01
To assess the average bioequivalence of two oral dosage forms of fluconazole--test (Fungolon, Antibiotic Co.) and reference (Diflucan, Pfizer)--in 18 healthy volunteers in a multiple dose-balanced, two-period, crossover study design. The dosage regimen consisted of seven days treatment (first day 100 mg and 50 mg thereafter for six days given orally) and a washout period of two weeks between different treatments. Plasma samples were taken at regular time intervals according to the study protocol for measuring of plasma fluconazole concentrations. The primary and secondary parameters AUC(168-192), Cav, %PTF, Cmax, %Swing, %AUCF, 100 Cmax/AUC, T above Cav, and Tmax were estimated. The point estimates--geometric means of the ratios test (T)/reference (R) and the 90% confidence intervals (CI) for the ratios of expected medians (T)/(R), assuming a multiplicative model, estimated by parametric and nonparametric analysis--were in the defined ranges for accepting of bioequivalence for two of the primary metrics. The point estimates and the 90% CIs after parametric analysis of AUC(168-192) were 1.00 (0.98-1.02) and for the metric %PTF exceeded the accepted range for bioequivalence after parametric analysis the point estimate and 90% CI were 0.93 and (0.799-1.08). The two preparations were considered to be bioequivalent in the rate and extent of absorption with significant variability across subjects.
Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras
Morris, Mark; Sellers, William I.
2015-01-01
Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints. PMID:25780778
Tomas-Fernandez, Xavier; Warfield, Simon K
2015-06-01
White matter (WM) lesions are thought to play an important role in multiple sclerosis (MS) disease burden. Recent work in the automated segmentation of white matter lesions from magnetic resonance imaging has utilized a model in which lesions are outliers in the distribution of tissue signal intensities across the entire brain of each patient. However, the sensitivity and specificity of lesion detection and segmentation with these approaches have been inadequate. In our analysis, we determined this is due to the substantial overlap between the whole brain signal intensity distribution of lesions and normal tissue. Inspired by the ability of experts to detect lesions based on their local signal intensity characteristics, we propose a new algorithm that achieves lesion and brain tissue segmentation through simultaneous estimation of a spatially global within-the-subject intensity distribution and a spatially local intensity distribution derived from a healthy reference population. We demonstrate that MS lesions can be segmented as outliers from this intensity model of population and subject. We carried out extensive experiments with both synthetic and clinical data, and compared the performance of our new algorithm to those of state-of-the art techniques. We found this new approach leads to a substantial improvement in the sensitivity and specificity of lesion detection and segmentation.
Bolaños, Marcos E; Bernat, Edward M; Aviyente, Selin
2011-01-01
The functional connectivity of the human brain may be described by modeling interactions among its neural assemblies as a graph composed of vertices and edges. It has recently been shown that functional brain networks belong to a class of scale-free complex networks for which graphs have helped define an association between function and topology. These networks have been shown to possess a heterogenous structure composed of clusters, dense regions of strongly associated nodes, which represent multivariate relationships among nodes. Network clustering algorithms classify the nodes based on a similarity measure representing the bivariate relationships and similar to unsupervised learning is performed without a priori information. In this paper, we propose a method for partitioning a set of networks representing different subjects and reveal a community structure common to multiple subjects. We apply this community identifying algorithm to functional brain networks during a cognitive control task, in particular the error-related negativity (ERN), to evaluate how the brain organizes itself during error-monitoring.
Directory of Open Access Journals (Sweden)
Ehsan Hejazi
2014-01-01
Full Text Available Objective. The aim of the present study was to compare the serum levels of total antioxidant status (TAS and 25(OH D3 and dietary intake of multiple sclerosis (MS patients with those of normal subjects. Method. Thirty-seven MS patients (31 women and the same number of healthy matched controls were compared for their serum levels and dietary intake of 25(OH D3 and TAS. Sun exposure and the intake of antioxidants and vitamin D rich foods were estimated through face-to-face interview and food frequency questionnaire. Results. Dietary intake of antioxidants and vitamin D rich foods, vitamin C, vitamin A, and folate was not significantly different between the two groups. There were also no significant differences in the mean levels of 25(OH D3 and TAS between the study groups. Both groups had low serum levels of 25(OH D3 and total antioxidants. Conclusion. No significant differences were detected in serum levels and dietary intake of vitamin D and antioxidants between MS patients and healthy controls. All subjects had low antioxidant status and vitamin D levels.
Tomas-Fernandez, Xavier; Warfield, Simon K.
2015-01-01
White matter (WM) lesions are thought to play an important role in multiple sclerosis (MS) disease burden. Recent work in the automated segmentation of white matter lesions from MRI has utilized a model in which lesions are outliers in the distribution of tissue signal intensities across the entire brain of each patient. However, the sensitivity and specificity of lesion detection and segmentation with these approaches have been inadequate. In our analysis, we determined this is due to the substantial overlap between the whole brain signal intensity distribution of lesions and normal tissue. Inspired by the ability of experts to detect lesions based on their local signal intensity characteristics, we propose a new algorithm that achieves lesion and brain tissue segmentation through simultaneous estimation of a spatially global within-the-subject intensity distribution and a spatially local intensity distribution derived from a healthy reference population. We demonstrate that MS lesions can be segmented as outliers from this intensity model of population and subject (MOPS). We carried out extensive experiments with both synthetic and clinical data, and compared the performance of our new algorithm to those of state-of-the art techniques. We found this new approach leads to a substantial improvement in the sensitivity and specificity of lesion detection and segmentation. PMID:25616008
Directory of Open Access Journals (Sweden)
López Rodrigo
2008-05-01
Full Text Available Abstract Background The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. Results We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. Conclusion The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable.
Yang, Zhirong; Oja, Erkki
2011-12-01
Multiplicative updates have been widely used in approximative nonnegative matrix factorization (NMF) optimization because they are convenient to deploy. Their convergence proof is usually based on the minimization of an auxiliary upper-bounding function, the construction of which however remains specific and only available for limited types of dissimilarity measures. Here we make significant progress in developing convergent multiplicative algorithms for NMF. First, we propose a general approach to derive the auxiliary function for a wide variety of NMF problems, as long as the approximation objective can be expressed as a finite sum of monomials with real exponents. Multiplicative algorithms with theoretical guarantee of monotonically decreasing objective function sequence can thus be obtained. The solutions of NMF based on most commonly used dissimilarity measures such as α- and β-divergence as well as many other more comprehensive divergences can be derived by the new unified principle. Second, our method is extended to a nonseparable case that includes e.g., γ-divergence and Rényi divergence. Third, we develop multiplicative algorithms for NMF using second-order approximative factorizations, in which each factorizing matrix may appear twice. Preliminary numerical experiments demonstrate that the multiplicative algorithms developed using the proposed procedure can achieve satisfactory Karush-Kuhn-Tucker optimality. We also demonstrate NMF problems where algorithms by the conventional method fail to guarantee descent at each iteration but those by our principle are immune to such violation.
Directory of Open Access Journals (Sweden)
Suchuan Zhong
2016-01-01
Full Text Available The stochastic resonance (SR characteristics of a generalized Langevin linear system driven by a multiplicative noise and a periodically modulated noise are studied (the two noises are correlated. In this paper, we consider a generalized Langevin equation (GLE driven by an internal noise with long-memory and long-range dependence, such as fractional Gaussian noise (fGn and Mittag-Leffler noise (M-Ln. Such a model is appropriate to characterize the chemical and biological solutions as well as to some nanotechnological devices. An exact analytic expression of the output amplitude is obtained. Based on it, some characteristic features of stochastic resonance phenomenon are revealed. On the other hand, by the use of the exact expression, we obtain the phase diagram for the resonant behaviors of the output amplitude versus noise intensity under different values of system parameters. These useful results presented in this paper can give the theoretical basis for practical use and control of the SR phenomenon of this mathematical model in future works.
Inverse estimation of multiple muscle activations based on linear logistic regression.
Sekiya, Masashi; Tsuji, Toshiaki
2017-07-01
This study deals with a technology to estimate the muscle activity from the movement data using a statistical model. A linear regression (LR) model and artificial neural networks (ANN) have been known as statistical models for such use. Although ANN has a high estimation capability, it is often in the clinical application that the lack of data amount leads to performance deterioration. On the other hand, the LR model has a limitation in generalization performance. We therefore propose a muscle activity estimation method to improve the generalization performance through the use of linear logistic regression model. The proposed method was compared with the LR model and ANN in the verification experiment with 7 participants. As a result, the proposed method showed better generalization performance than the conventional methods in various tasks.
DEFF Research Database (Denmark)
Dimitriou, Michalis; Kounalakis, Tsampikos; Vidakis, Nikolaos
2013-01-01
This paper presents a complete system for multiple object detection and classification in a 3D scene using an RGB-D sensor such as the Microsoft Kinect sensor. Successful multiple object detection and classification are crucial features in many 3D computer vision applications. The main goal......, connected components detection and filtering approaches, in order to design a complete image processing algorithm for efficient object detection of multiple individual objects in a single scene, even in complex scenes with many objects. Besides, we apply the Linear Spatial Pyramid Matching (LSPM) [1] method...... proposed by Jianchao Yang et al for the efficient classification of the detected objects. Experimental results are presented for both detection and classification, showing the efficiency of the proposed design....
Chan, Chung-hong; Ng, Daniel K
2007-08-01
It is common for apnea-hypopnea index (AHI) to be used as an outcome variable in ordinary least squares linear regression. However, the distribution of AHI is not tested. The assumption of ordinary least squares linear regression may be violated. The distribution of AHI from a pediatric sleep laboratory was assessed by Kolomgorov-Smirnov test. Transformation of AHI was attempted. In addition, we fitted an ordinary linear regression model (OLSM) and negative binomial regression model (NBRM) of the relationship between body mass index and the rate of apnea and hypopnea events. OLSM and NBRM were evaluated by residuals analysis. AHI from the studied population deviated significantly from normal distribution. Commonly used transformation algorithm could not transform AHI to normal distribution. In addition, OLSM violated the underlying statistical assumptions of homogeneity of variance and normality of error. NBRM, on the other hand, was not restricted by these assumptions. The current study suggested AHI is not likely to be normally distributed and its distribution cannot be transformed to normal. Negative binomial regression of the total number of apnea and hypopnea with an offset of log TST should be used in data analysis. 2007 Wiley-Liss, Inc.
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.
Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression
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…
Approximate solution of the non-linear diffusion equation of multiple orders
Directory of Open Access Journals (Sweden)
Wu Fei
2016-01-01
Full Text Available In this paper, fractional diffusion equation of multiple orders is approximately solved. The equation is given in the equivalent integral form. The Adomian polynomial is adopted and analytical solutions are obtained. The result contains two parameters that can have more space for fitting the experiment data.
DEFF Research Database (Denmark)
Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.
Geometrically non-linear multi-degree-of-freedom (MDOF) systems subject to random excitation are considered. New semi-analytical approximate forward difference equations for the lower order non-stationary statistical moments of the response are derived from the stochastic differential equations...... of motion, and, the accuracy of these equations is numerically investigated. For stationary excitations, the proposed method computes the stationary statistical moments of the response from the solution of non-linear algebraic equations....
Directory of Open Access Journals (Sweden)
Nyberg Fred
2008-11-01
Full Text Available Abstract Background The inappropriate use of anabolic androgenic steroids (AAS was originally a problem among athletes but AAS are now often used in nonsport situations and by patients attending regular addiction clinics. The aim of this study was to improve understanding of the development of multiple drug use in patients seeking treatment at an addiction clinic for AAS-related problems. Methods We interviewed six patients (four men and two women with experience of AAS use who were attending an addiction clinic for what they believed were AAS-related problems. The patients were interviewed in-depth about their life stories, with special emphasis on social background, substance use, the development of total drug use and subjective experienced psychological and physical side effects. Results There was significant variation in the development of drug use in relation to social background, onset of drug use, relationship to AAS use and experience of AAS effects. All patients had initially experienced positive effects from AAS but, over time, the negative experiences had outweighed the positive effects. All patients were dedicated to excess training and took AAS in combination with gym training, indicating that the use of these drugs is closely related to this form of training. Use of multiple drugs was common either in parallel with AAS use or serially. Conclusion The study shows the importance of understanding how AAS use can develop either with or without the concomitant use of other drugs of abuse. The use of AAS can, however, progress to the use of other drugs. The study also indicates the importance of obtaining accurate, comprehensive information about the development of AAS use in designing treatment programmes and prevention strategies in this area.
Siragusa, Enrico; Haiminen, Niina; Utro, Filippo; Parida, Laxmi
2017-10-09
Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions. An incremental gap-filling version of previously introduced SimBA-LD is here demonstrated to accurately fit the target distributions, allowing efficient large scale simulations. SimBA-hap accuracy and efficiency is demonstrated by simulating tetraploid populations with varying numbers of founder haplotypes, we evaluate both a linear time greedy algoritm and an optimal solution based on mixed-integer programming. SimBA is available on http://researcher.watson.ibm.com/project/5669.
Optical System Of The Powerful Multiple Beam L-band Klystron For Linear Collider
Larionov, A
2004-01-01
An optical system reported here was proposed and designed for Toshiba MBK (E3736). Toshiba MBK is the 10MW L-band multiple beam klystron being developed for TESLA (XFEL) project. The key features of this device are following. A new compact scheme of confined flow focusing, which allows using ring shape cavities at the klystron, operating on the fundamental mode. Low cathodes loading (2
Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf
2015-10-01
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. © The Author 2014. Published by Oxford University Press.
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.
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.
Ji, Yanju; Huang, Wanyu; Yu, Mingmei; Guan, Shanshan; Wang, Yuan; Zhu, Yu
2017-01-01
This article studies full-waveform associated identification method of airborne time-domain electromagnetic method (ATEM) 3-d anomalies based on multiple linear regression analysis method. By using convolution algorithm, full-waveform theoretical responses are computed to derive sample library including switch-off-time period responses and off-time period responses. Extract full-waveform attributes from theoretical responses to derive linear regression equations which are used to identify the geological parameters. In order to improve the precision ulteriorly, we optimize the identification method by separating the sample library into different groups and identify the parameter respectively. Performance of full-waveform associated identification method with field data of wire-loop test experiments with ATEM system in Daedao of Changchun proves that the full-waveform associated identification method is feasible practically.
Frequency and Severity of Trauma in Fishes Subjected to Multiple-pass Depletion Electrofishing
Panek, Frank; Densmore, Christine L.
2013-01-01
The incidence and severity of trauma associated with multiple-pass electrofishing and the effects on short-term (30-d) survival and growth of Rainbow Trout Oncorhynchus mykiss, Brook Trout Salvelinus fontinalis, and five representative co-inhabiting nontarget or bycatch species were examined. Fish were held in four rectangular fiberglass tanks (190 × 66 cm) equipped with electrodes, a gravel–cobble stream substrate, and continuous water flow. Fish were exposed to one, two, or three electroshocks (100-V, 60-Hz pulsed DC) spaced 1 h apart or were held as a control. The heterogeneous field produced a mean (±SD) voltage gradient of 0.23 ± 0.024 V/cm (range = 0.20–0.30 V/cm) with a duty cycle of 30% and a 5-s exposure. Radiographs of 355 fish were examined for evidence of spinal injuries, and necropsies were performed on 303 fish to assess hemorrhagic trauma in soft tissue. Using linear regression, we demonstrated significant relationships between the number of electrical shocks and the frequency and severity of hemorrhagic and spinal trauma in each of the nontarget species (Potomac Sculpin Cottus girardi, Channel Catfish Ictalurus punctatus, Fathead Minnow Pimephales promelas, Green Sunfish Lepomis cyanellus, and Largemouth Bass Micropterus salmoides). Most of the injuries in these species were either minor or moderate. Rainbow Trout and Brook Trout generally sustained the highest incidence and severity of injuries, but those injuries were generally independent of the number of treatments. The 30-d postshock survival for the trout species was greater than 94%; survival for the bycatch species ranged from 80% (Fathead Minnow) to 100% (Green Sunfish and Channel Catfish). There were no significant differences in 30-d postshock condition factors despite observations of altered feeding behavior lasting several days to 1 week posttreatment in several of the study species.
Cruwys, Tegan; Steffens, Niklas K; Haslam, S Alexander; Haslam, Catherine; Jetten, Jolanda; Dingle, Genevieve A
2016-12-01
In this research, we introduce Social Identity Mapping (SIM) as a method for visually representing and assessing a person's subjective network of group memberships. To provide evidence of its utility, we report validating data from three studies (two longitudinal), involving student, community, and clinical samples, together comprising over 400 participants. Results indicate that SIM is easy to use, internally consistent, with good convergent and discriminant validity. Each study also illustrates the ways that SIM can be used to address a range of novel research questions. Study 1 shows that multiple positive group memberships are a particularly powerful predictor of well-being. Study 2 shows that social support is primarily given and received within social groups and that only in-group support is beneficial for well-being. Study 3 shows that improved mental health following a social group intervention is attributable to an increase in group compatibility. In this way, the studies demonstrate the capacity for SIM to make a contribution both to the development of social-psychological theory and to its practical application. © 2016 The British Psychological Society.
Hsu, Ching-Chi; Lin, Jinn; Chao, Ching-Kong
2011-12-01
Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process. Copyright Â© 2010 Elsevier Ireland Ltd. All rights reserved.
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 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.
Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation
Directory of Open Access Journals (Sweden)
Chunqing Li
2012-01-01
Full Text Available The computer simulation of the membrane bioreactor MBR has become the research focus of the MBR simulation. In order to compensate for the defects, for example, long test period, high cost, invisible equipment seal, and so forth, on the basis of conducting in-depth study of the mathematical model of the MBR, combining with neural network theory, this paper proposed a three-dimensional simulation system for MBR wastewater treatment, with fast speed, high efficiency, and good visualization. The system is researched and developed with the hybrid programming of VC++ programming language and OpenGL, with a multifactor linear regression model of affecting MBR membrane fluxes based on neural network, applying modeling method of integer instead of float and quad tree recursion. The experiments show that the three-dimensional simulation system, using the above models and methods, has the inspiration and reference for the future research and application of the MBR simulation technology.
Classification of the ionic composition of the irrigation water using multiple linear regression
Maia, Celsemy E.; Morais, Elís R.C. de; Oliveira, Maurício de
2001-01-01
Objetivou-se, com o presente trabalho, desenvolver uma metodologia para classificação da composição iônica da água de irrigação, através da regressão linear múltipla, tendo-se, como variável dependente, a condutividade elétrica e, como variáveis independentes, as concentrações de cátions e ânions da água de irrigação, classificada de acordo com o peso de cada íon no modelo estatístico. A fonte secundária de dados para a pesquisa foi o Banco de Dados do Laboratório de Análise de Água e Fertili...
A Versatile Multiple Target Detection System Based on DNA Nano-assembled Linear FRET Arrays.
Li, Yansheng; Du, Hongwu; Wang, Wenqian; Zhang, Peixun; Xu, Liping; Wen, Yongqiang; Zhang, Xueji
2016-05-27
DNA molecules have been utilized both as powerful synthetic building blocks to create nanoscale architectures and as inconstant programmable templates for assembly of biosensors. In this paper, a versatile, scalable and multiplex detection system is reported based on an extending fluorescent resonance energy transfer (FRET) cascades on a linear DNA assemblies. Seven combinations of three kinds of targets are successfully detected through the changes of fluorescence spectra because of the three-steps FRET or non-FRET continuity mechanisms. This nano-assembled FRET-based nanowire is extremely significant for the development of rapid, simple and sensitive detection system. The method used here could be extended to a general platform for multiplex detection through more-step FRET process.
Mohammadi, Alireza; Kargar, Mahmoud; Hesami, Ehsan
2018-02-06
Spatial disorientation is a hallmark of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease. Our aim was to use virtual reality to determine the allocentric and egocentric memory deficits of subjects with single-domain aMCI (aMCIsd) and multiple-domain aMCI (aMCImd). For this purpose, we introduced an advanced virtual reality navigation task (VRNT) to distinguish these deficits in mild Alzheimer's disease (miAD), aMCIsd, and aMCImd. The VRNT performance of 110 subjects, including 20 with miAD, 30 with pure aMCIsd, 30 with pure aMCImd, and 30 cognitively normal controls was compared. Our newly developed VRNT consists of a virtual neighbourhood (allocentric memory) and virtual maze (egocentric memory). Verbal and visuospatial memory impairments were also examined with Rey Auditory-Verbal Learning Test and Rey-Osterrieth Complex Figure Test, respectively. We found that miAD and aMCImd subjects were impaired in both allocentric and egocentric memory, but aMCIsd subjects performed similarly to the normal controls on both tasks. The miAD, aMCImd, and aMCIsd subjects performed worse on finding the target or required more time in the virtual environment than the aMCImd, aMCIsd, and normal controls, respectively. Our findings indicated the aMCImd and miAD subjects, as well as the aMCIsd subjects, were more impaired in egocentric orientation than allocentric orientation. We concluded that VRNT can distinguish aMCImd subjects, but not aMCIsd subjects, from normal elderly subjects. The VRNT, along with the Rey Auditory-Verbal Learning Test and Rey-Osterrieth Complex Figure Test, can be used as a valid diagnostic tool for properly distinguishing different forms of aMCI. © 2018 Japanese Psychogeriatric Society.
Lorenzo-Seva, Urbano; Ferrando, Pere J
2011-03-01
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.
Linear and nonlinear frequency- and time-domain spectroscopy with multiple frequency combs
Bennett, Kochise; Rouxel, Jeremy R.; Mukamel, Shaul
2017-09-01
Two techniques that employ equally spaced trains of optical pulses to map an optical high frequency into a low frequency modulation of the signal that can be detected in real time are compared. The development of phase-stable optical frequency combs has opened up new avenues to metrology and spectroscopy. The ability to generate a series of frequency spikes with precisely controlled separation permits a fast, highly accurate sampling of the material response. Recently, pairs of frequency combs with slightly different repetition rates have been utilized to down-convert material susceptibilities from the optical to microwave regime where they can be recorded in real time. We show how this one-dimensional dual comb technique can be extended to multiple dimensions by using several combs. We demonstrate how nonlinear susceptibilities can be quickly acquired using this technique. In a second class of techniques, sequences of ultrafast mode locked laser pulses are used to recover pathways of interactions contributing to nonlinear susceptibilities by using a photo-acoustic modulation varying along the sequences. We show that these techniques can be viewed as a time-domain analog of the multiple frequency comb scheme.
An adaptive algorithm for separating and tracking multiple directional sources in linear arrays
Ko, C. C.; Chin, Francois; Foo, S. S.
1992-03-01
A new algorithm for spatially filtering out, enhancing, and tracking individual directional sources in an adaptive array is proposed and investigated. In this algorithm, the sources are separated by using an adaptive beamformer whose outputs are processed by employing the LMS algorithm to track distinct sources individually. From the LMS weights employed, the source locations can be estimated and whenever significant changes in these are detected, the beamformer is updated so that its outputs will be due to different sources in the steady state. With this algorithm, the problems of look direction errors in look-direction constrained arrays and of large signal power in power inversion arrays are eliminated, and the enhancement of multiple moving sources becomes a natural process. Furthermore, because the sources are individually tracked and the beamformer is only updated occasionally, the algorithm possesses fast tracking behavior, and its implementation complexity is comparable to that of beamformer-based adaptive arrays using the LMS algorithm.
Multiple linear regression solvatochromic analysis of donar-acceptor imidazole derivatives.
Jayabharathi, J; Thanikachalam, V; Kalaiarasi, V; Ramanathan, P
2015-01-01
Catalytic synthesis of some polysubstituted imidazoles under solvent-free condition is reported and their characterization has been carried out spectral techniques. Electronic spectral studies reveal that their solvatochromic behavior depends both the polarity of the medium and hydrogen bonding properties of the solvents. Specific hydrogen bonding interaction in polar solvents modulated the order of the two close lying lowest singlet states. The solvent effect on absorption and emission spectral results has been analyzed by multiple parametric regression analysis. Solvatochromic effects on the emission spectral position indicate the charge transfer (CT) character of the emitting singlet states both in a polar and a non polar environment. The fluorescence decays for the imidazoles fit satisfactorily to a bi exponential kinetics. These observations are in consistent with quantum chemical calculations.
Directory of Open Access Journals (Sweden)
R. Muralidaran
2014-03-01
Full Text Available The influence of evolutionary algorithms enhanced its scope of getting its existence in almost every complex optimization problems. In this paper, cuckoo search algorithm, an algorithm based on the brood parasite behavior along with Levy weights has been proposed for the radiation pattern correction of a linear array of isotropic antennas with uniform spacing when failed with more than one antenna element. Even though deterioration produced by the failure of antenna elements results in various undesirable effects, consideration in this paper is given to the correction of side lobe level and null placement at two places. Various articles in the past have already shown that the idea to correct the radiation pattern is to alter the amplitude weights of the remaining unfailed elements, instead of replacing the faulty elements. This approach is made use of modifying the current excitations of unfailed elements using cuckoo search algorithm such that the resulting radiation pattern is similar to the unfailed original pattern in terms of side lobe level and null placement at two places. Examples shown in this paper demonstrate the effectiveness of this algorithm in achieving the desired objectives.
Robinson, John E.
2014-01-01
The Federal Aviation Administration's Next Generation Air Transportation System will combine advanced air traffic management technologies, performance-based procedures, and state-of-the-art avionics to maintain efficient operations throughout the entire arrival phase of flight. Flight deck Interval Management (FIM) operations are expected to use sophisticated airborne spacing capabilities to meet precise in-trail spacing from top-of-descent to touchdown. Recent human-in-the-loop simulations by the National Aeronautics and Space Administration have found that selection of the assigned spacing goal using the runway schedule can lead to premature interruptions of the FIM operation during periods of high traffic demand. This study compares three methods for calculating the assigned spacing goal for a FIM operation that is also subject to time-based metering constraints. The particular paradigms investigated include: one based upon the desired runway spacing interval, one based upon the desired meter fix spacing interval, and a composite method that combines both intervals. These three paradigms are evaluated for the primary arrival procedures to Phoenix Sky Harbor International Airport using the entire set of Rapid Update Cycle wind forecasts from 2011. For typical meter fix and runway spacing intervals, the runway- and meter fix-based paradigms exhibit moderate FIM interruption rates due to their inability to consider multiple metering constraints. The addition of larger separation buffers decreases the FIM interruption rate but also significantly reduces the achievable runway throughput. The composite paradigm causes no FIM interruptions, and maintains higher runway throughput more often than the other paradigms. A key implication of the results with respect to time-based metering is that FIM operations using a single assigned spacing goal will not allow reduction of the arrival schedule's excess spacing buffer. Alternative solutions for conducting the FIM operation
Zhang, Yanyan; Ma, Haile; Wang, Bei; Qu, Wenjuan; Wali, Asif; Zhou, Cunshan
2016-08-01
Ultrasound pretreatment of wheat gluten (WG) before enzymolysis can improve the angiotensin converting enzyme (ACE) inhibitory activity of the hydrolysates by alerting the structure of substrate proteins. Establishment of a relationship between the structure of WG and ACE inhibitory activity of the hydrolysates to judge the end point of the ultrasonic pretreatment is vital. The results of stepwise multiple linear regression (MLR) showed that the contents of free sulfhydryl, α-helix, disulfide bond, surface hydrophobicity and random coil were significantly correlated to ACE Inhibitory activity of the hydrolysate, with the standard partial regression coefficients were 3.729, -0.676, -0.252, 0.022 and 0.156, respectively. The R(2) of this model was 0.970. External validation showed that the stepwise MLR model could well predict the ACE inhibitory activity of hydrolysate based on the content of free sulfhydryl, α-helix, disulfide bond, surface hydrophobicity and random coil of WG before hydrolysis. A stepwise multiple linear regression model describing the quantitative relationships between the structure of WG and the ACE Inhibitory activity of the hydrolysates was established. This model can be used to predict the endpoint of the ultrasonic pretreatment. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Energy Technology Data Exchange (ETDEWEB)
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 and 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.
Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O
2016-06-01
The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.
A Multiple Processing Resource Explanation of the Subjective Dimensions of Operator Workload.
1984-02-01
Arabie, P. (1979). Auditory versus phonetic accounts of observed confusions between consonant phonemes. Journal of the Acoustal Society of America, 66, 46...similarity. Scaling and clustering analyses of the similarity data produced subjective dimensions/ clusters of workload that were explained in terms of...by subjects and rated according to workload similarity. Scaling and clustering analyses of the similarity data produced subjective dimensions/ clusters
Li, Haiyan; Butler, Kathleen; Yang, Li; Yang, Zhenghua; Teng, Renli
2012-02-01
dosing regimens. Both parent and metabolite exhibited linear and predictable pharmacokinetics with single and multiple dosing as mean minimum plasma concentration (C(min)), C(max) and area under the plasma concentration-time curve from time zero to infinity (AUC(∞)) were approximately 2-fold higher with ticagrelor 180 mg (e.g. multiple-dosing, geometric mean [% coefficient of variation]: C(max) 1973 [27] and AUC(∞) 18 035 [46]) versus 90 mg (e.g. multiple dosing: C(max) 915 [32] and AUC(∞) 7168 [35]) dosing regimens. Overall, ticagrelor was generally well tolerated in healthy Chinese subjects. Two subjects discontinued in the ticagrelor 90 mg group due to elevated serum levels of ALT and AST. Mild ticagrelor-associated adverse events were seen: bleeding events (90 mg: epistaxis n = 1; 180 mg: gingival bleeding n = 1) and dyspnoea (180 mg: n = 3). In healthy Chinese subjects, ticagrelor and AR-C124910XX pharmacokinetics were linear and predictable. Although ticagrelor and AR-C124910XX exposure at steady state were found to be slightly higher in Chinese subjects, these results were broadly similar to previous data in Caucasian subjects. Overall, ticagrelor was well tolerated in healthy Chinese subjects. ClinicalTrials.gov identifier: NCT00721448.
The BL-QMR algorithm for non-Hermitian linear systems with multiple right-hand sides
Energy Technology Data Exchange (ETDEWEB)
Freund, R.W. [AT& T Bell Labs., Murray Hill, NJ (United States)
1996-12-31
Many applications require the solution of multiple linear systems that have the same coefficient matrix, but differ in their right-hand sides. Instead of applying an iterative method to each of these systems individually, it is potentially much more efficient to employ a block version of the method that generates iterates for all the systems simultaneously. However, it is quite intricate to develop robust and efficient block iterative methods. In particular, a key issue in the design of block iterative methods is the need for deflation. The iterates for the different systems that are produced by a block method will, in general, converge at different stages of the block iteration. An efficient and robust block method needs to be able to detect and then deflate converged systems. Each such deflation reduces the block size, and thus the block method needs to be able to handle varying block sizes. For block Krylov-subspace methods, deflation is also crucial in order to delete linearly and almost linearly dependent vectors in the underlying block Krylov sequences. An added difficulty arises for Lanczos-type block methods for non-Hermitian systems, since they involve two different block Krylov sequences. In these methods, deflation can now occur independently in both sequences, and consequently, the block sizes in the two sequences may become different in the course of the iteration, even though they were identical at the beginning. We present a block version of Freund and Nachtigal`s quasi-minimal residual method for the solution of non-Hermitian linear systems with single right-hand sides.
National Research Council Canada - National Science Library
Wikil Kwak; Susan Eldridge; Yong Shi; Gang Kou
2009-01-01
Our study proposes a multiple criteria linear programming (MCLP) and other data mining methods to predict material weaknesses in a firm's internal control system after the Sarbanes-Oxley Act (SOX) using 2003-2004 U.S. data...
Independent component model for cognitive functions of multiple subjects using [15O]H2O PET images.
Park, Hae-Jeong; Kim, Jae-Jin; Youn, Tak; Lee, Dong Soo; Lee, Myung Chul; Kwon, Jun Soo
2003-04-01
An independent component model of multiple subjects' positron emission tomography (PET) images is proposed to explore the overall functional components involved in a task and to explain subject specific variations of metabolic activities under altered experimental conditions utilizing the Independent component analysis (ICA) concept. As PET images represent time-compressed activities of several cognitive components, we derived a mathematical model to decompose functional components from cross-sectional images based on two fundamental hypotheses: (1) all subjects share basic functional components that are common to subjects and spatially independent of each other in relation to the given experimental task, and (2) all subjects share common functional components throughout tasks which are also spatially independent. The variations of hemodynamic activities according to subjects or tasks can be explained by the variations in the usage weight of the functional components. We investigated the plausibility of the model using serial cognitive experiments of simple object perception, object recognition, two-back working memory, and divided attention of a syntactic process. We found that the independent component model satisfactorily explained the functional components involved in the task and discuss here the application of ICA in multiple subjects' PET images to explore the functional association of brain activations. Copyright 2003 Wiley-Liss, Inc.
Directory of Open Access Journals (Sweden)
Lili Tian
2016-09-01
Full Text Available Based on the relationship between gratitude and general subjective well-being, and Basic Psychological Needs Theory (BPNT; Ryan & Deci, 2000, the present study's aim was to use structural equation modeling to test the multiple mediational roles of the satisfaction of three basic psychological needs at school in accounting for the association between gratitude and subjective well-being in school (school satisfaction, school affect in adolescents. A total of 881 Chinese adolescents (427 males; Mean age = 12.97 completed a multi-measure questionnaire tapping the targeted variables. Results indicated that gratitude related statistically significantly to adolescents’ subjective well-being in school. Furthermore, a multiple-mediators analysis indicated that competence and relatedness needs satisfaction at school mediated the relation between gratitude and subjective well-being in school. Lastly, a multiple-mediators analysis also indicated that gratitude related to subjective well-being in school indirectly through autonomy needs satisfaction at school. Limitations and practical applications of the study were discussed.
Lunøe, Kristoffer; Martínez-Sierra, Justo Giner; Gammelgaard, Bente; Alonso, J Ignacio García
2012-03-01
The analytical methodology for the in vivo study of selenium metabolism using two enriched selenium isotopes has been modified, allowing for the internal correction of spectral interferences and mass bias both for total selenium and speciation analysis. The method is based on the combination of an already described dual-isotope procedure with a new data treatment strategy based on multiple linear regression. A metabolic enriched isotope ((77)Se) is given orally to the test subject and a second isotope ((74)Se) is employed for quantification. In our approach, all possible polyatomic interferences occurring in the measurement of the isotope composition of selenium by collision cell quadrupole ICP-MS are taken into account and their relative contribution calculated by multiple linear regression after minimisation of the residuals. As a result, all spectral interferences and mass bias are corrected internally allowing the fast and independent quantification of natural abundance selenium ((nat)Se) and enriched (77)Se. In this sense, the calculation of the tracer/tracee ratio in each sample is straightforward. The method has been applied to study the time-related tissue incorporation of (77)Se in male Wistar rats while maintaining the (nat)Se steady-state conditions. Additionally, metabolically relevant information such as selenoprotein synthesis and selenium elimination in urine could be studied using the proposed methodology. In this case, serum proteins were separated by affinity chromatography while reverse phase was employed for urine metabolites. In both cases, (74)Se was used as a post-column isotope dilution spike. The application of multiple linear regression to the whole chromatogram allowed us to calculate the contribution of bromine hydride, selenium hydride, argon polyatomics and mass bias on the observed selenium isotope patterns. By minimising the square sum of residuals for the whole chromatogram, internal correction of spectral interferences and mass
Ng, Kar Yong; Awang, Norhashidah
2018-01-06
Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
Yu, Donghai; Du, Ruobing; Xiao, Ji-Chang
2016-07-05
Ninety-six acidic phosphorus-containing molecules with pKa 1.88 to 6.26 were collected and divided into training and test sets by random sampling. Structural parameters were obtained by density functional theory calculation of the molecules. The relationship between the experimental pKa values and structural parameters was obtained by multiple linear regression fitting for the training set, and tested with the test set; the R(2) values were 0.974 and 0.966 for the training and test sets, respectively. This regression equation, which quantitatively describes the influence of structural parameters on pKa , and can be used to predict pKa values of similar structures, is significant for the design of new acidic phosphorus-containing extractants. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Akbari, Somaye; Zebardast, Tannaz; Zarghi, Afshin; Hajimahdi, Zahra
2017-01-01
COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R 2 ) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q 2 ) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.
Singh, S.; Jaishi, H. P.; Tiwari, R. P.; Tiwari, R. C.
2017-07-01
This paper reports the analysis of soil radon data recorded in the seismic zone-V, located in the northeastern part of India (latitude 23.73N, longitude 92.73E). Continuous measurements of soil-gas emission along Chite fault in Mizoram (India) were carried out with the replacement of solid-state nuclear track detectors at weekly interval. The present study was done for the period from March 2013 to May 2015 using LR-115 Type II detectors, manufactured by Kodak Pathe, France. In order to reduce the influence of meteorological parameters, statistical analysis tools such as multiple linear regression and artificial neural network have been used. Decrease in radon concentration was recorded prior to some earthquakes that occurred during the observation period. Some false anomalies were also recorded which may be attributed to the ongoing crustal deformation which was not major enough to produce an earthquake.
Fragkaki, A G; Tsantili-Kakoulidou, A; Angelis, Y S; Koupparis, M; Georgakopoulos, C
2009-11-20
A quantitative structure-retention relationship (QSRR) study has been performed to correlate relative retention times (RRTs) of trimethylsilylated (TMS) anabolic androgenic steroids (AAS) with their molecular characteristics, encoded by the respective descriptors, for the prediction of RRTs of novel molecules, using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). The elucidation of similarities and dissimilarities among the data structures was carried out using principal component analysis (PCA). Successful models were established using multiple linear regression (MLR) and partial least squares (PLS) techniques as a function of topological, three-dimensional (3D) and physicochemical descriptors. The models are useful for the estimation of RRTs of designer steroids for which no analytical data is available.
Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena
2013-01-01
The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.
Seaman, Shaun R; Bartlett, Jonathan W; White, Ian R
2012-04-10
Multiple imputation is often used for missing data. When a model contains as covariates more than one function of a variable, it is not obvious how best to impute missing values in these covariates. Consider a regression with outcome Y and covariates X and X2. In 'passive imputation' a value X* is imputed for X and then X2 is imputed as (X*)2. A recent proposal is to treat X2 as 'just another variable' (JAV) and impute X and X2 under multivariate normality. We use simulation to investigate the performance of three methods that can easily be implemented in standard software: 1) linear regression of X on Y to impute X then passive imputation of X2; 2) the same regression but with predictive mean matching (PMM); and 3) JAV. We also investigate the performance of analogous methods when the analysis involves an interaction, and study the theoretical properties of JAV. The application of the methods when complete or incomplete confounders are also present is illustrated using data from the EPIC Study. JAV gives consistent estimation when the analysis is linear regression with a quadratic or interaction term and X is missing completely at random. When X is missing at random, JAV may be biased, but this bias is generally less than for passive imputation and PMM. Coverage for JAV was usually good when bias was small. However, in some scenarios with a more pronounced quadratic effect, bias was large and coverage poor. When the analysis was logistic regression, JAV's performance was sometimes very poor. PMM generally improved on passive imputation, in terms of bias and coverage, but did not eliminate the bias. Given the current state of available software, JAV is the best of a set of imperfect imputation methods for linear regression with a quadratic or interaction effect, but should not be used for logistic regression.
Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam
2016-01-01
Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors . A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r(2), concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained.
Rastija, Vesna; Masand, Vijay H
2014-01-01
In order to find a thriving quantitative structure-activity relationship for antitrypanosomal activities (against Trypanosma brucei rhodesiense) of polyphenols that belong to different structural groups, multiple linear regression (MLR) and artificial neural networks (ANN) were employed. The analysis was performed on two different-sized training sets (59% and 78% molecules in the training set), resulting in relatively successful MLR and ANN models for the data set containing the smaller training set. The best MLR model obtained using the five descriptors (R3m(+), GAP, DISPv, HATS2m, JGI2) was able to account only for 74% of the variance of antitrypanosomal activities of the training set and achieved a high internal, but low external prediction. Nonlinearities of the best ANN model compared with the linear model improved the coefficient of determination to 98.6%, and showed a better external predictive ability. The obtained models displayed relevance of the distance between oxygen atoms in molecules of polyphenols, as well as stability of molecules, measured by the difference between the energy of the highest occupied molecular orbital and the energy of the lowest unoccupied molecular orbital (GAP) for their activity.
Haler, Jean R. N.; Far, Johann; Aqil, Abdelhafid; Claereboudt, Jan; Tomczyk, Nick; Giles, Kevin; Jérôme, Christine; De Pauw, Edwin
2017-08-01
Ion mobility-mass spectrometry (IM-MS) has emerged as a powerful separation and identification tool to characterize synthetic polymer mixtures and topologies (linear, cyclic, star-shaped,…). Electrospray coupled to IM-MS already revealed the coexistence of several charge state-dependent conformations for a single charge state of biomolecules with strong intramolecular interactions, even when limited resolving power IM-MS instruments were used. For synthetic polymers, the sample's polydispersity allows the observation of several chain lengths. A unique collision cross-section (CCS) trend is usually observed when increasing the degree of polymerization (DP) at constant charge state, allowing the deciphering of different polymer topologies. In this paper, we report multiple coexisting CCS trends when increasing the DP at constant charge state for linear poly(acrylamide) PAAm in the gas phase. This is similar to observations on peptides and proteins. Biomolecules show in addition population changes when collisionally heating the ions. In the case of synthetic PAAm, fragmentation occurred before reaching the energy for conformation conversion. These observations, which were made on two different IM-MS instruments (SYNAPT G2 HDMS and high resolution multi-pass cyclic T-Wave prototype from Waters), limit the use of ion mobility for synthetic polymer topology interpretations to polymers where unique CCS values are observed for each DP at constant charge state. [Figure not available: see fulltext.
Jäntschi, Lorentz; Bálint, Donatella; Bolboacă, Sorana D
2016-01-01
Multiple linear regression analysis is widely used to link an outcome with predictors for better understanding of the behaviour of the outcome of interest. Usually, under the assumption that the errors follow a normal distribution, the coefficients of the model are estimated by minimizing the sum of squared deviations. A new approach based on maximum likelihood estimation is proposed for finding the coefficients on linear models with two predictors without any constrictive assumptions on the distribution of the errors. The algorithm was developed, implemented, and tested as proof-of-concept using fourteen sets of compounds by investigating the link between activity/property (as outcome) and structural feature information incorporated by molecular descriptors (as predictors). The results on real data demonstrated that in all investigated cases the power of the error is significantly different by the convenient value of two when the Gauss-Laplace distribution was used to relax the constrictive assumption of the normal distribution of the error. Therefore, the Gauss-Laplace distribution of the error could not be rejected while the hypothesis that the power of the error from Gauss-Laplace distribution is normal distributed also failed to be rejected.
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available We consider the problem of minimizing a convex separable logarithmic function over a region defined by a convex inequality constraint or linear equality constraint, and two-sided bounds on the variables (box constraints. Such problems are interesting from both theoretical and practical point of view because they arise in some mathematical programming problems as well as in various practical problems such as problems of production planning and scheduling, allocation of resources, decision making, facility location problems, and so forth. Polynomial algorithms are proposed for solving problems of this form and their convergence is proved. Some examples and results of numerical experiments are also presented.
Energy Technology Data Exchange (ETDEWEB)
Joeres, A.P.W.; Heverhagen, J.T.; Bonel, H. [Inselspital - University Hospital Bern (Switzerland). Univ. Inst. of Diagnostic, Interventional and Pediatric Radiology; Exadaktylos, A. [Inselspital - University Hospital Bern (Switzerland). Dept. of Emergency Medicine; Klink, T. [Inselspital - University Hospital Bern (Switzerland). Univ. Inst. of Diagnostic, Interventional and Pediatric Radiology; Wuerzburg Univ. (Germany). Inst. of Diagnostic and Interventional Radiology
2016-02-15
The purpose of this study was to evaluate the diagnostic accuracy of full-body linear X-ray scanning (LS) in multiple trauma patients in comparison to 128-multislice computed tomography (MSCT). 106 multiple trauma patients (female: 33; male: 73) were retrospectively included in this study. All patients underwent LS of the whole body, including extremities, and MSCT covering the neck, thorax, abdomen, and pelvis. The diagnostic accuracy of LS for the detection of fractures of the truncal skeleton and pneumothoraces was evaluated in comparison to MSCT by two observers in consensus. Extremity fractures detected by LS were documented. The overall sensitivity of LS was 49.2%, the specificity was 93.3%, the positive predictive value was 91%, and the negative predictive value was 57.5%. The overall sensitivity for vertebral fractures was 16.7%, and the specificity was 100%. The sensitivity was 48.7% and the specificity 98.2% for all other fractures. Pneumothoraces were detected in 12 patients by CT, but not by LS.40 extremity fractures were detected by LS, of which 4 fractures were dislocated, and 2 were fully covered by MSCT. The diagnostic accuracy of LS is limited in the evaluation of acute trauma of the truncal skeleton. LS allows fast whole-body X-ray imaging, and may be valuable for detecting extremity fractures in trauma patients in addition to MSCT.
Indian Academy of Sciences (India)
bDepartment of Chemistry, Islamic Azad University-North Tehran Branch, Tehran, Iran. cLaboratory of ... The hierarchical clustering method was used to classify the dataset into training and test subsets. The important ... QSAR; hierarchical clustering; genetic algorithms; Prolylcarboxypeptidase (PrCP). 1. Introduction.
Multiple linear regression analysis
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.
Papuć, Ewa; Stelmasiak, Zbigniew
2012-05-01
Quality of life (QoL) has presently a firmly established position as an important endpoint in medical care. Multiple sclerosis (MS) is a chronic neurological disease with considerable effect on patients' QoL. QoL of MS patients from many European countries has already been assessed but little is known on health-related QoL of Polish subjects with MS. Few studies have taken into consideration multiple predictors of QoL. The aim of this study was to elicit the most relevant factors that determine QoL of Polish group of MS patients. Socio-demographic and clinical factors as well as the influence of disability level were analyzed in this study. 173 MS patients and 86 healthy controls underwent assessment using the Mini Mental Status Examination, WHOQOL-100, Beck Depression Inventory and Fatigue Severity Scale. Data were analyzed by a stepwise linear regression analysis. MS patients had significantly worse global QoL and worse QoL in physical and psychological health domains, lower level of independence, worse social relations and were less satisfied with the surrounding environment they lived in compared with healthy controls (p<0.05). MS subjects had also higher level of depression and fatigue compared to healthy controls (p<0.05). The study determined that the strongest predictors of global QoL of Polish MS patients were depression, disability level and fatigue. Copyright © 2011 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Micaletti, R. C.; Cakmak, A. S.; Nielsen, Søren R. K.
structural properties. The resulting state-space formulation is a system of ordinary stochastic differential equations with random coefficient and deterministic initial conditions which are subsequently transformed into ordinary stochastic differential equations with deterministic coefficients and random...... initial conditions. This transformation facilitates the derivation of differential equations which govern the evolution of the unconditional statistical moments of response. Primary consideration is given to linear systems and systems with odd polynomial nonlinearities, for in these cases...... there is a significant reduction in the number of equations to be solved. The method is illustrated for a five-story shear-frame structure with nonlinear interstory restoring forces and random damping and stiffness properties. The results of the proposed method are compared to those estimated by extensive Monte Carlo...
de Hoon, Jan; Van Hecken, Anne; Vandermeulen, Corinne; Yan, Lucy; Smith, Brian; Chen, Jiyun Sunny; Bautista, Edgar; Hamilton, Lisa; Waksman, Javier; Vu, Thuy; Vargas, Gabriel
2017-07-24
Monoclonal antibodies (mAbs) targeting calcitonin gene-related peptide (CGRP) signaling are being explored as prophylactic treatments for migraine. Erenumab (AMG 334) is the first potent, selective, and competitive human mAb antagonist of the CGRP receptor. We report the data from two phase I studies assessing the safety, pharmacokinetics (PK), and pharmacodynamics of single and multiple administrations of erenumab in healthy subjects and patients with migraine. The results indicate that the PK profile of erenumab is nonlinear from 1 mg to 70 mg and the linear portion of the clearance from 70 mg to 210 mg is consistent with other human immunoglobulin G2 antibodies. Single doses of erenumab resulted in >75% inhibition of capsaicin-induced dermal blood flow, with no apparent dose-dependency for erenumab ≥21 mg. Erenumab was generally well tolerated, with an acceptable safety profile, supporting further clinical development of erenumab for migraine prevention. © 2017 American Society for Clinical Pharmacology and Therapeutics.
Directory of Open Access Journals (Sweden)
Elizabeth Vaquera
2011-12-01
Full Text Available Using data from a random representative survey of South Florida immigrants (n=1,268, our research examines different facets of transnationalism and how they relate to a typically overlooked component of immigrant incorporation–subjective well-being. We examine separately the affective and evaluative components of immigrants’ well-being in their country of reception—the United States—by differentiating between self-reported emotional well-being and self-reported satisfaction with life in the U.S. Findings support that the kinds and frequency of connections that immigrants maintain with the home country are important factors for understanding immigrants’ subjective well-being.
Bishop, Malachy; Frain, Michael P.; Tschopp, Molly K.
2008-01-01
Self-management has been shown to increase perceived control over both illness and nonillness aspects of life among people with chronic conditions but has not received significant research attention among persons with multiple sclerosis (MS). Based on relationships proposed in the illness intrusiveness and disability centrality models, this study…
Kokaly, R.F.; Clark, R.N.
1999-01-01
We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.30 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.We develop a new method for estimating the biochemistry of plant material using
Single and multiple cardiovascular biomarkers in subjects without a previous cardiovascular event
DEFF Research Database (Denmark)
Pareek, Manan; Bhatt, Deepak L; Vaduganathan, Muthiah
2017-01-01
population-based cohort study of 1324 subjects without a previous cardiovascular event, who underwent baseline echocardiography and biomarker assessment between 2002 and 2006. The clinical endpoint was the composite of myocardial infarction, invasively treated stable/unstable ischemic heart disease, heart...
Multiple environments: South Indian children’s environmental subjectivities in formation
de Hoop, E.
2017-01-01
This article explores the formation of South Indian children’s (11–15 years old) environmental subjectivities based on five months of qualitative fieldwork with children in their school and non-school lives. By doing so, this paper aims to widen the scope of the existing literature on children’s
Oguntunde, Philip G; Lischeid, Gunnar; Dietrich, Ottfried
2017-10-14
This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease (P yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.
Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried
2017-10-01
This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease (P 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.
Martin, L; Mezcua, M; Ferrer, C; Gil Garcia, M D; Malato, O; Fernandez-Alba, A R
2013-01-01
The main objective of this work was to establish a mathematical function that correlates pesticide residue levels in apple juice with the levels of the pesticides applied on the raw fruit, taking into account some of their physicochemical properties such as water solubility, the octanol/water partition coefficient, the organic carbon partition coefficient, vapour pressure and density. A mixture of 12 pesticides was applied to an apple tree; apples were collected after 10 days of application. After harvest, apples were treated with a mixture of three post-harvest pesticides and the fruits were then processed in order to obtain apple juice following a routine industrial process. The pesticide residue levels in the apple samples were analysed using two multi-residue methods based on LC-MS/MS and GC-MS/MS. The concentration of pesticides was determined in samples derived from the different steps of processing. The processing factors (the coefficient between residue level in the processed commodity and the residue level in the commodity to be processed) obtained for the full juicing process were found to vary among the different pesticides studied. In order to investigate the relationships between the levels of pesticide residue found in apple juice samples and their physicochemical properties, principal component analysis (PCA) was performed using two sets of samples (one of them using experimental data obtained in this work and the other including the data taken from the literature). In both cases the correlation was found between processing factors of pesticides in the apple juice and the negative logarithms (base 10) of the water solubility, octanol/water partition coefficient and organic carbon partition coefficient. The linear correlation between these physicochemical properties and the processing factor were established using a multiple linear regression technique.
Kim, Won Soo; Park, In Ki; Park, Young Kee; Chun, Yeoun Sook
2017-01-01
Multiple-pinhole (MPH) glasses are currently sold in many countries with unproven advertisements; however, their objective and subjective effects have not been investigated. Therefore, to investigate the effects of MPH glasses excluding the single-pinhole (SPH) effect, we compared the visual functional changes, reading speed, and ocular discomfort after reading caused by MPH and SPH glasses. Healthy 36 participants with a mean age of 33.1 years underwent examinations of pupil size, visual acu...
Jiao, Hui-Wen; Sun, Lu-Ning; Li, Yue-Qi; Yu, Lei; Zhang, Hong-Wen; Wang, Mei-Feng; Yu, Li-Yuan; Yuan, Zi-Qing-Yun; Xie, Li-Jun; Chen, Juan; Meng, Ling; Zhang, Xue-Hui; Wang, Yong-Qing
2018-03-01
The objective of this study was to evaluate the safety, pharmacokinetics, and pharmacodynamics of S-(-)-pantoprazole (PPZ) sodium injections following single and multiple intravenous doses in healthy Chinese subjects. The dosage groups were set as followed: 20 mg of single and multiple intravenous administration of S-(-)-PPZ, 40 mg of single and multiple intravenous administration of S-(-)-PPZ or pantoprazole, and 80 mg of single dosage group of S-(-)-PPZ. Subjects were sampled for pharmacokinetic analysis and were monitored for 24-h intragastric pH prior to and 48-h intragastric pH after administration for the pharmacodynamic study. The pharmacokinetic and pharmacodynamic parameters were compared between S-(-)-PPZ and PPZ. Safety was evaluated on the basis of adverse events, vital signs, laboratory tests, and physical examination. All adverse events were mild and of limited duration. Maximum plasma concentration and area under the concentration-time curve for S-(-)-PPZ were dose proportional over the range of 20-80 mg following a single intravenous administration. Elimination rate constant and half-life observed statistical difference from a single dose to multiple doses in 40 mg of S-(-)-PPZ groups. After administration of a single dose, the mean 24-h intragastric pH value was observed higher in 80-mg group than in 40- and 20-mg groups. Slightly increase of intragastric pH was found after a single dose of 40 mg S-(-)-PPZ than 40 mg PPZ; however, the differences were not statistically significant. Twice daily of 40 mg S-(-)-PPZ sodium injections is effective in achieving satisfying acid inhibition. Compared with plasma R-(+)-PPZ levels, most subjects presented more potent and prolonged suppression of gastric acid of S-(-)-PPZ, while a few subjects showed faster metabolic rate of S-(-)-PPZ in vivo.
On strength design using free material subjected to multiple load cases
DEFF Research Database (Denmark)
Pedersen, Pauli; Pedersen, Niels Leergaard
2013-01-01
Multiple load cases and the consideration of strength is a reality that most structural designs are exposed to. Improved possibility to produce specific materials, say by fiber lay-up, put focus on research on free material optimization. A formulation for such design problems together with a prac......Multiple load cases and the consideration of strength is a reality that most structural designs are exposed to. Improved possibility to produce specific materials, say by fiber lay-up, put focus on research on free material optimization. A formulation for such design problems together...... with a practical recursive design procedure is presented and illustrated with examples. The presented finite element analysis involve many elements as well as many load cases. Separating the local amount of material from a description with unit trace for the local anisotropy, gives the free materials formulation...
Tian, Lili; Pi, Luyang; Huebner, E. S.; Du, Minmin
2016-01-01
Based on the relation between gratitude and general subjective well-being (SWB), and Basic Psychological Needs Theory (Ryan and Deci, 2000), the present study’s aim was to use structural equation modeling to test the multiple mediational roles of the satisfaction of three basic psychological needs at school in accounting for the association between gratitude and SWB in school (school satisfaction, school affect) in adolescents. A total of 881 Chinese adolescents (427 males; Mean age = 12.97) completed a multi-measure questionnaire that tapped the targeted variables. Findings revealed that gratitude related significantly, positively to adolescents’ SWB in school. Moreover, a multiple-mediators analysis suggested that relatedness and competence needs satisfaction at school mediated the relation between gratitude and SWB in school. Lastly, a multiple-mediators analysis also indicated that autonomy needs satisfaction mediated the relation between relatedness and competence needs and SWB in school. Limitations and practical applications of the study were discussed. PMID:27708601
Tian, Lili; Pi, Luyang; Huebner, E S; Du, Minmin
2016-01-01
Based on the relation between gratitude and general subjective well-being (SWB), and Basic Psychological Needs Theory (Ryan and Deci, 2000), the present study's aim was to use structural equation modeling to test the multiple mediational roles of the satisfaction of three basic psychological needs at school in accounting for the association between gratitude and SWB in school (school satisfaction, school affect) in adolescents. A total of 881 Chinese adolescents (427 males; Mean age = 12.97) completed a multi-measure questionnaire that tapped the targeted variables. Findings revealed that gratitude related significantly, positively to adolescents' SWB in school. Moreover, a multiple-mediators analysis suggested that relatedness and competence needs satisfaction at school mediated the relation between gratitude and SWB in school. Lastly, a multiple-mediators analysis also indicated that autonomy needs satisfaction mediated the relation between relatedness and competence needs and SWB in school. Limitations and practical applications of the study were discussed.
Yadav, Amit; Panda, Sarat Kumar; Dey, Tanish
2017-11-01
Present analysis deals with nonlinear flexural-torsional vibration and dynamic instability of thin-walled stiffener beam with open section subjected to harmonic in-plane loading. The static and dynamic components of the applied harmonic in-plane loading are assumed to vary uniformly. A set of nonlinear partial differential equations (PDEs) describing the vibration of system is derived. Using Galerkin's method, these partial differential equations are reduced into coupled Mathieu equations. The steady state response of the system is determined by solving the condition for a non-trivial solution. The principal regions of parametric resonance are determined using the method suggested by Bolotin. The numerical results are presented to investigate the effect of aspect ratios, boundary conditions and static load factor on the frequency-amplitude responses and instability regions.
Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming
2017-10-01
Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.
Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil
2017-07-01
The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.
Linard, Joshua I.
2013-01-01
Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.
Directory of Open Access Journals (Sweden)
Fereshteh Shiri
2010-08-01
Full Text Available In the present work, support vector machines (SVMs and multiple linear regression (MLR techniques were used for quantitative structure–property relationship (QSPR studies of retention time (tR in standardized liquid chromatography–UV–mass spectrometry of 67 mycotoxins (aflatoxins, trichothecenes, roquefortines and ochratoxins based on molecular descriptors calculated from the optimized 3D structures. By applying missing value, zero and multicollinearity tests with a cutoff value of 0.95, and genetic algorithm method of variable selection, the most relevant descriptors were selected to build QSPR models. MLRand SVMs methods were employed to build QSPR models. The robustness of the QSPR models was characterized by the statistical validation and applicability domain (AD. The prediction results from the MLR and SVM models are in good agreement with the experimental values. The correlation and predictability measure by r2 and q2 are 0.931 and 0.932, repectively, for SVM and 0.923 and 0.915, respectively, for MLR. The applicability domain of the model was investigated using William’s plot. The effects of different descriptors on the retention times are described.
Shabri, Ani; Samsudin, Ruhaidah
2014-01-01
Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.
Doytchinova, Irini A; Flower, Darren R
2007-01-01
The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.
Olaya-Abril, Alfonso; Parras-Alcántara, Luis; Lozano-García, Beatriz; Obregón-Romero, Rafael
2017-08-15
Over time, the interest on soil studies has increased due to its role in carbon sequestration in terrestrial ecosystems, which could contribute to decreasing atmospheric CO 2 rates. In many studies, independent variables were related to soil organic carbon (SOC) alone, however, the contribution degree of each variable with the experimentally determined SOC content were not considered. In this study, samples from 612 soil profiles were obtained in a natural protected (Red Natura 2000) of Sierra Morena (Mediterranean area, South Spain), considering only the topsoil 0-25cm, for better comparison between results. 24 independent variables were used to define it relationship with SOC content. Subsequently, using a multiple linear regression analysis, the effects of these variables on the SOC correlation was considered. Finally, the best parameters determined with the regression analysis were used in a climatic change scenario. The model indicated that SOC in a future scenario of climate change depends on average temperature of coldest quarter (41.9%), average temperature of warmest quarter (34.5%), annual precipitation (22.2%) and annual average temperature (1.3%). When the current and future situations were compared, the SOC content in the study area was reduced a 35.4%, and a trend towards migration to higher latitude and altitude was observed. Copyright © 2017 Elsevier B.V. All rights reserved.
Archer, Cherie; Morris, Libby; George, Stacey
2014-01-01
It is acknowledged in the literature that the physical and cognitive effects of the degenerative neurological condition of multiple sclerosis can impact upon driver safety. The aim of this study was to identify the experiences and needs of people with multiple sclerosis in relation to driver assessment and rehabilitation. Focus group discussions were conducted with people with multiple sclerosis (MS) who were: currently driving; no longer licensed or no longer driving and health professionals. The four themes that emerged from the data were: (1) from self-management to formal assessment - a journey of uncertainty and emotional dilemmas; (2) lost independence with grieving and adjustment by self and family; (3) alternative transport is challenging and unsatisfactory; (4) gaps in information and services exist. The results of this study highlight the need for ongoing support in relation to driving for people with MS, ranging from support for self-management, driving assessment and retraining, and preparation for loss of license. Standardised information needs to be developed and health professionals and licensing authorities require knowledge and skills to ensure driver assessment and rehabilitation processes and resources can better meet the needs of people with MS. There is a need for health professionals to examine driving in people with MS in a holistic manner taking into account the context for the person and the supports available. Self-management and self-assessment emerged as a preferred approach for the participants in this study, indicating that health professionals may need to engage with the process. Tools to support self-assessment of driving abilities for people with MS require further research. Indicators for review and formal assessment of driving abilities is needed. Alternative forms of transport require further investigation and improvement for people with MS.
Formation Control and Obstacle Avoidance for Multiple Robots Subject to Wheel-Slip
Directory of Open Access Journals (Sweden)
Cai Ze-Su
2012-11-01
Full Text Available An adaptive formation control law for non-holonomic dynamic robots based on an artificial potential function method in the presence of lateral slip and parametric uncertainties is presented to organize multiple robots into formation. It is formulated to achieve the smooth control of the translational and rotational motion of a group of mobile robots while keeping a prescribed formation and avoiding inter-robot and obstacle collisions. In order to improve the formation control method effectively and reduce the distortion shape, the virtual leader-following method is proposed for every robot and an improved optimal assignment algorithm is used to solve multi-targets optimal assignment for the formation problem. Simulation results are provided to validate the theoretical results.
Herrig, Ilona M; Böer, Simone I; Brennholt, Nicole; Manz, Werner
2015-11-15
Since rivers are typically subject to rapid changes in microbiological water quality, tools are needed to allow timely water quality assessment. A promising approach is the application of predictive models. In our study, we developed multiple linear regression (MLR) models in order to predict the abundance of the fecal indicator organisms Escherichia coli (EC), intestinal enterococci (IE) and somatic coliphages (SC) in the Lahn River, Germany. The models were developed on the basis of an extensive set of environmental parameters collected during a 12-months monitoring period. Two models were developed for each type of indicator: 1) an extended model including the maximum number of variables significantly explaining variations in indicator abundance and 2) a simplified model reduced to the three most influential explanatory variables, thus obtaining a model which is less resource-intensive with regard to required data. Both approaches have the ability to model multiple sites within one river stretch. The three most important predictive variables in the optimized models for the bacterial indicators were NH4-N, turbidity and global solar irradiance, whereas chlorophyll a content, discharge and NH4-N were reliable model variables for somatic coliphages. Depending on indicator type, the extended mode models also included the additional variables rainfall, O2 content, pH and chlorophyll a. The extended mode models could explain 69% (EC), 74% (IE) and 72% (SC) of the observed variance in fecal indicator concentrations. The optimized models explained the observed variance in fecal indicator concentrations to 65% (EC), 70% (IE) and 68% (SC). Site-specific efficiencies ranged up to 82% (EC) and 81% (IE, SC). Our results suggest that MLR models are a promising tool for a timely water quality assessment in the Lahn area. Copyright © 2015 Elsevier Ltd. All rights reserved.
Curthoys, I S; Haslwanter, T; Black, R A; Burgess, A M; Halmagyi, G M; Topple, A N; Todd, M J
1998-12-01
Dual search coils were used to record horizontal, vertical and torsional eye movement components of one eye during nystagmus caused by off-center yaw rotation (yaw centrifugation). Both normal healthy human subjects (n=7) and patients with only one functioning labyrinth (n=12) were studied in order to clarify how the concomitant linear acceleration affected the nystagmus response. Each subject was seated with head erect on the arm of a fixed-chair human centrifuge, 1 m away from the center of the rotation, and positioned to be facing along a radius; either towards (facing-in) or away from (facing-out) the center of rotation. Both yaw right and yaw left angular accelerations of 10 degrees s(-2) from 0 to 200 degrees/s were studied. During rotation a centripetal linear acceleration (increasing from 0 to 1.24xg units) was directed along the subject's naso-occipital axis resulting in a shift of the resultant angle of the gravitoinertial acceleration (GIA) of 51 degrees in the subject's pitch plane and an increase in the total GIA magnitude from 1.0 to 1.59xg. In normal subjects during the angular acceleration off-center there were, in addition to the horizontal eye velocity components, torsional and vertical eye velocities present. The magnitude of these additional components, although small, was larger than observed during similar experiments with on-center angular acceleration (Haslwanter et al. 1996), and the change in these components is attributed to the additional effect of the linear acceleration stimulation. In the pitch plane the average size of the shift of the axis of eye velocity (AEV) during the acceleration was about 8 degrees for a 51 degrees shift of the GIA (around 16% of the GIA shift) so that the AEV-GIA alignment was inadequate. There was a very marked difference in the size of the AEV shift depending on whether the person was facing-in [AEV shift forward (i.e. non-compensatory) of about 4 degrees] or facing-out [AEV shift forward (i.e. compensatory
Nordborg, Magnus; Innan, Hideki
2003-03-01
A stochastic model for the genealogy of a sample of recombining sequences containing one or more sites subject to selection in a subdivided population is described. Selection is incorporated by dividing the population into allelic classes and then conditioning on the past sizes of these classes. The past allele frequencies at the selected sites are thus treated as parameters rather than as random variables. The purpose of the model is not to investigate the dynamics of selection, but to investigate effects of linkage to the selected sites on the genealogy of the surrounding chromosomal region. This approach is useful for modeling strong selection, when it is natural to parameterize the past allele frequencies at the selected sites. Several models of strong balancing selection are used as examples, and the effects on the pattern of neutral polymorphism in the chromosomal region are discussed. We focus in particular on the statistical power to detect balancing selection when it is present.
Directory of Open Access Journals (Sweden)
Carmine Berlingieri
2016-12-01
Full Text Available Pain is a common disabling symptom in patients with Multiple Sclerosis (MS. It has been indicated that pain prevalence in MS patients is between 29–86 %. It is evident that most MS patients requiring treatment will be also searching pain related treatments to assist in day to day activities. Neuropathic pain is a difficult symptom and is generally inadequately relieved even though different rehabilitative approaches may be used. Neuromuscular Taping inducing micro-movements by stimulating receptors in the skin has been described in literature as a possible intervention in neurological and orthopedic rehabilitation improving mobility and in pain reduction. The aim of this preliminary report was to analyze the effect and to evaluate the possible applications of Neuromuscular Taping (NMT in patients with MS in order to reduce pain in comparison to the Transcutaneous Electrical Nerve Stimulation (TENS and to physical rehabilitation treatment alone. We observed that NMT together with standard physical rehabilitation was able to reduce neuropathic pain to greater lengths, with statistically significant differences between pre and post treatment, compared to the other treatments evaluated. This study showed increased efficacy in pain reduction when NMT was applied to standard physical treatment in long standing pain conditions. Neuromuscular Taping may constitute a low cost treatment strategy for neuropathic pain conditions in MS.
Subjective, but not objective, lingering effects of multiple past concussions in adolescents.
Brooks, Brian L; McKay, Carly D; Mrazik, Martin; Barlow, Karen M; Meeuwisse, Willem H; Emery, Carolyn A
2013-09-01
The existing literature on lingering effects from concussions in children and adolescents is limited and mixed, and there are no clear answers for patients, clinicians, researchers, or policy makers. The purpose of this study was to examine whether there are lingering effects of past concussions in adolescent athletes. Participants in this study included 643 competitive Bantam and Midget hockey players (most elite 20% by division of play) between 13 and 17 years of age (mean age=15.5, SD=1.2). Concussion history at baseline assessment was retrospectively documented using a pre-season questionnaire (PSQ), which was completed at home by parents and players in advance of baseline testing. Players with English as a second language, self-reported attention or learning disorders, a concussion within 6 months of baseline, or suspected invalid test profiles were excluded from these analyses. Demographically adjusted standard scores for the five composites/domains and raw symptom ratings from the brief Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) computerized battery were analyzed. Adolescent athletes with one or two or more prior concussions did not have significantly worse neurocognitive functioning on ImPACT than did those with no previous concussions. There were significantly more symptoms reported in those with two or more prior concussions than in those with no or one prior concussion. Adolescents with multiple previous concussions had higher levels of baseline symptoms, but there were not group differences in neurocognitive functioning using this brief computerized battery.
Norgaard, Trine; Moldrup, P; Ferré, T P A; Katuwal, S; Olsen, P; de Jonge, L W
2014-09-01
Water-dispersible soil colloids (WDC) act as carriers for sorbing chemicals in macroporous soils and hence constitute a significant risk for the aquatic environment. The prediction of WDC readily available for facilitated chemical transport is an unsolved challenge. This study identifies key parameters and predictive indicators for assessing field-scale variation of WDC. Samples representing three measurement scales (1- to 2-mm aggregates, intact 100-cm rings, and intact 6283 cm columns) were retrieved from the topsoil of a 1.69-ha agricultural field in a 15-m by 15-m grid to determine colloid dispersibility, mobilization, and transport. The amount of WDC was determined using (i) a laser diffraction method on 1- to 2-mm aggregates and (ii) an end-over-end shaking method on 100-cm intact rings. The accumulated amount of colloids leached from 20-cm by 20-cm intact columns was determined as a measure of the integrated colloid mobilization and transport. The WDC and the accumulated colloid transport were higher in samples from the northern part of the field. Using multiple linear regression (MLR) analyses, WDC or amount of colloids transported were predicted at the three measurement scales from 24 measured, geo-referenced parameters to identify parameters that could serve as indicator parameters for screening for colloid dispersibility, mobilization, and transport. The MLR analyses were performed at each sample scale using all, only northern, and only southern field locations. Generally, the predictive power of the regression models was best on the smallest 1- to 2-mm aggregate scale. Overall, our results suggest that different drivers controlled colloid dispersibility and transport at the three measurement scales and in the two subareas of the field. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
DeForest, David K; Brix, Kevin V; Tear, Lucinda M; Adams, William J
2018-01-01
The bioavailability of aluminum (Al) to freshwater aquatic organisms varies as a function of several water chemistry parameters, including pH, dissolved organic carbon (DOC), and water hardness. We evaluated the ability of multiple linear regression (MLR) models to predict chronic Al toxicity to a green alga (Pseudokirchneriella subcapitata), a cladoceran (Ceriodaphnia dubia), and a fish (Pimephales promelas) as a function of varying DOC, pH, and hardness conditions. The MLR models predicted toxicity values that were within a factor of 2 of observed values in 100% of the cases for P. subcapitata (10 and 20% effective concentrations [EC10s and EC20s]), 91% of the cases for C. dubia (EC10s and EC20s), and 95% (EC10s) and 91% (EC20s) of the cases for P. promelas. The MLR models were then applied to all species with Al toxicity data to derive species and genus sensitivity distributions that could be adjusted as a function of varying DOC, pH, and hardness conditions (the P. subcapitata model was applied to algae and macrophytes, the C. dubia model was applied to invertebrates, and the P. promelas model was applied to fish). Hazardous concentrations to 5% of the species or genera were then derived in 2 ways: 1) fitting a log-normal distribution to species-mean EC10s for all species (following the European Union methodology), and 2) fitting a triangular distribution to genus-mean EC20s for animals only (following the US Environmental Protection Agency methodology). Overall, MLR-based models provide a viable approach for deriving Al water quality guidelines that vary as a function of DOC, pH, and hardness conditions and are a significant improvement over bioavailability corrections based on single parameters. Environ Toxicol Chem 2018;37:80-90. © 2017 SETAC. © 2017 SETAC.
Bonellie, Sandra R
2012-10-01
To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother. Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.
Lin, Wang; Qiao, Ni
2008-03-01
In this note, the periodic and chaotic responses of two single-degree-of-freedom (SDOF) models are investigated and some interesting results obtained. The first model (original model) has been developed by Narayanan and Sekar [Periodic and chaotic responses of an SDOF system with piecewise linear stiffness subjected to combined harmonic and flow induced excitations, Journal of Sound and Vibration 184 (2) (1997) 281-298] and the second one corresponds to a modified system. The original model, involving a one-sided clearance ( y0) between the mass and the linear spring, is subjected to combined harmonic ( F cos ωt) and flow-induced excitations. Narayanan and Sekar (1997) has shown that periodic, quasi-periodic and chaotic motions of this original model may occur in a range of flow velocities for the case: y0=0 and F≠0. In the present work, numerical calculations are carried out for several other important cases of the original system, showing some interesting, and sometimes unexpected results. The modified model, in particular, involving both-sided clearances, is analyzed numerically subsequently. The effect of flow velocity, clearances on the global dynamics of this modified system is discussed finally.
Directory of Open Access Journals (Sweden)
Tovar Juscelino
2012-04-01
Full Text Available Abstract Background Different foods can modulate cardiometabolic risk factors in persons already affected by metabolic alterations. The objective of this study was to assess, in healthy overweight individuals, the impact of a diet combining multiple functional concepts on risk markers associated with cardiometabolic diseases (CMD. Methods Fourty-four healthy women and men (50-73 y.o, BMI 25-33, fasting glycemia ≤ 6.1 mmol/L participated in a randomized crossover intervention comparing a multifunctional (active diet (AD with a control diet (CD devoid of the "active" components. Each diet was consumed during 4 wk with a 4 wk washout period. AD included the following functional concepts: low glycemic impact meals, antioxidant-rich foods, oily fish as source of long-chain omega-3 fatty acids, viscous dietary fibers, soybean and whole barley kernel products, almonds, stanols and a probiotic strain (Lactobacillus plantarum Heal19/DSM15313. Results Although the aim was to improve metabolic markers without promoting body weight loss, minor weight reductions were observed with both diets (0.9-1.8 ± 0.2%; P P P P = 0.0056, LDL/HDL (-27 ± 2%; P P 1c (-2 ± 0.4%; P = 0.0013, hs-CRP (-29 ± 9%; P = 0.0497 and systolic blood pressure (-8 ± 1%¸ P = 0.0123. The differences remained significant after adjustment for weight change. After AD, the Framingham cardiovascular risk estimate was 30 ± 4% (P P Conclusion The improved biomarker levels recorded in healthy individuals following the multifunctional regime suggest preventive potential of this dietary approach against CMD.
Allore, Heather; Tinetti, Mary E; Araujo, Katy L B; Hardy, Susan; Peduzzi, Peter
2005-02-01
Many important physiologic and clinical predictors are continuous. Clinical investigators and epidemiologists' interest in these predictors lies, in part, in the risk they pose for adverse outcomes, which may be continuous as well. The relationship between continuous predictors and a continuous outcome may be complex and difficult to interpret. Therefore, methods to detect levels of a predictor variable that predict the outcome and determine the threshold for clinical intervention would provide a beneficial tool for clinical investigators and epidemiologists. We present a case study using regression tree methodology to predict Social and Productive Activities score at 3 years using five modifiable impairments. The predictive ability of regression tree methodology was compared with multiple linear regression using two independent data sets, one for development and one for validation. The regression tree approach and the multiple linear regression model provided similar fit (model deviances) on the development cohort. In the validation cohort, the deviance of the multiple linear regression model was 31% greater than the regression tree approach. Regression tree analysis developed a better model of impairments predicting Social and Productive Activities score that may be more easily applied in research settings than multiple linear regression alone.
Safari, A.; Sharifi, M. A.; Amjadiparvar, B.
2010-05-01
The GRACE mission has substantiated the low-low satellite-to-satellite tracking (LL-SST) concept. The LL-SST configuration can be combined with the previously realized high-low SST concept in the CHAMP mission to provide a much higher accuracy. The line of sight (LOS) acceleration difference between the GRACE satellite pair is the mostly used observable for mapping the global gravity field of the Earth in terms of spherical harmonic coefficients. In this paper, mathematical formulae for LOS acceleration difference observations have been derived and the corresponding linear system of equations has been set up for spherical harmonic up to degree and order 120. The total number of unknowns is 14641. Such a linear equation system can be solved with iterative solvers or direct solvers. However, the runtime of direct methods or that of iterative solvers without a suitable preconditioner increases tremendously. This is the reason why we need a more sophisticated method to solve the linear system of problems with a large number of unknowns. Multiplicative variant of the Schwarz alternating algorithm is a domain decomposition method, which allows it to split the normal matrix of the system into several smaller overlaped submatrices. In each iteration step the multiplicative variant of the Schwarz alternating algorithm solves linear systems with the matrices obtained from the splitting successively. It reduces both runtime and memory requirements drastically. In this paper we propose the Multiplicative Schwarz Alternating Algorithm (MSAA) for solving the large linear system of gravity field recovery. The proposed algorithm has been tested on the International Association of Geodesy (IAG)-simulated data of the GRACE mission. The achieved results indicate the validity and efficiency of the proposed algorithm in solving the linear system of equations from accuracy and runtime points of view. Keywords: Gravity field recovery, Multiplicative Schwarz Alternating Algorithm, Low
Niino, Masaaki; Mifune, Nobuhiro; Kohriyama, Tatsuo; Mori, Masahiro; Ohashi, Takashi; Kawachi, Izumi; Shimizu, Yuko; Fukaura, Hikoaki; Nakashima, Ichiro; Kusunoki, Susumu; Miyamoto, Katsuichi; Yoshida, Kazuto; Kanda, Takashi; Nomura, Kyoichi; Yamamura, Takashi; Yoshii, Fumihito; Kira, Jun-ichi; Nakane, Shunya; Yokoyama, Kazumasa; Matsui, Makoto; Miyazaki, Yusei; Kikuchi, Seiji
2014-01-06
Cognitive impairment could affect quality of life for patients with multiple sclerosis (MS), and cognitive function may be correlated with several factors such as depression and fatigue. This study aimed to evaluate cognitive function in Japanese patients with MS and the association between cognitive function and apathy, fatigue, and depression. The Brief Repeatable Battery of Neuropsychological tests (BRB-N) was performed in 184 Japanese patients with MS and 163 healthy controls matched for age, gender, and education. The Apathy Scale (AS), Fatigue Questionnaire (FQ), and Beck Depression Inventory Second Edition (BDI-II) were used to evaluate apathy, fatigue, and depression, respectively. Student's t-test was used to compare MS patients and healthy controls. Correlations between two factors were assessed using the Pearson correlation test, and multiple regression analysis was used to evaluate how much each factor affected the BRB-N score. In all BRB-N tests, patients with MS scored significantly lower than controls, and the effect size of symbol digit modalities test was the highest among the 9 tests of the BRB-N. Patients with MS had higher AS (p depression in Japanese patients with MS. Despite the association between cognitive variables and depression/apathy, cognitive function was impaired beyond the effect of depression and apathy. However, subjective fatigue is not related with cognitive impairment. Taken together, this suggests that different therapeutic approaches are needed to improve subjective fatigue and cognition, and thereby quality of life, in patients with MS.
Directory of Open Access Journals (Sweden)
Katrin eHanken
2014-12-01
Full Text Available In multiple sclerosis (MS patients, fatigue is rated as one of the most common and disabling symptoms. However, the pathophysiology underlying this fatigue is not yet clear. Several lines of evidence suggest that immunological factors, such as elevated levels of proinflammatory cytokines, may contribute to subjective fatigue in MS patients. Proinflammatory cytokines represent primary mediators of immune-to-brain-communication, modulating changes in the neurophysiology of the central nervous system. Recently, we proposed a model arguing that fatigue in MS patients is a subjective feeling which is related to inflammation. Moreover, it implies that fatigue can be measured behaviorally only by applying specific cognitive tasks related to alertness and vigilance. In the present review we focus on the subjective feeling of MS-related fatigue. We examine the hypothesis that the subjective feeling of MS-related fatigue may be a variant of inflammation-induced sickness behavior, resulting from cytokine-mediated activity changes within brain areas involved in interoception and homeostasis including the insula, the anterior cingulate and the hypothalamus. We first present studies demonstrating a relationship between proinflammatory cytokines and subjective fatigue in healthy individuals, in people with inflammatory disorders, and particularly in MS patients. Subsequently, we discuss studies analyzing the impact of anti-inflammatory treatment on fatigue. In the next part of this review we present studies on the transmission and neural representation of inflammatory signals, with a special focus on possible neural concomitants of inflammation-induced fatigue. We also present two of our studies on the relationship between local gray and white matter atrophy and fatigue in MS patients. Finally, we discuss some implications of our findings and future perspectives.
Directory of Open Access Journals (Sweden)
Kirsch Lee E
2009-12-01
Full Text Available Abstract Background The population pharmacokinetics of artesunate (AS and its active metabolite dihydroartemisinin (DHA were studied in healthy subjects receiving single- or multiple-dosing of AS orally either in combination with pyronaridine (PYR or as a monotherapy with or without food. Methods Data from 118 concentration-time profiles arising from 91 healthy Korean subjects were pooled from four Phase I clinical studies. Subjects received 2-5 mg/kg of single- and multiple-dosing of oral AS either in combination with PYR or as a monotherapy with or without food. Plasma AS and DHA were measured simultaneously using a validated liquid chromatography- mass spectrometric method with a lower limit of quantification of 1 ng/mL for both AS and DHA. Nonlinear mixed-effect modelling was used to obtain the pharmacokinetic and variability (inter-individual and residual variability parameter estimates. Results A novel parent-metabolite pharmacokinetic model consisting of a dosing compartment, a central compartment for AS, a central compartment and a peripheral compartment for DHA was developed. AS and DHA data were modelled simultaneously assuming stoichiometric conversion to DHA. AS was rapidly absorbed with a population estimate of absorption rate constant (Ka of 3.85 h-1. The population estimates of apparent clearance (CL/F and volume of distribution (V2/F for AS were 1190 L/h with 36.2% inter-individual variability (IIV and 1210 L with 57.4% IIV, respectively. For DHA, the population estimates of apparent clearance (CLM/F and central volume of distribution (V3/F were 93.7 L/h with 28% IIV and 97.1 L with 30% IIV, respectively. The population estimates of apparent inter-compartmental clearance (Q/F and peripheral volume of distribution (V4/F for DHA were 5.74 L/h and 18.5 L, respectively. Intake of high-fat and high-caloric meal prior to the drug administration resulted in 84% reduction in Ka. Body weight impacted CLM/F, such that a unit change in
Clement, Dominic; Gruber, Nicolas
2017-04-01
Major progress has been made by the international community (e.g., GO-SHIP, IOCCP, IMBER/SOLAS carbon working groups) in recent years by collecting and providing homogenized datasets for carbon and other biogeochemical variables in the surface ocean (SOCAT) and interior ocean (GLODAPv2). Together with previous efforts, this has enabled the community to develop methods to assess changes in the ocean carbon cycle through time. Of particular interest is the determination of the decadal change in the anthropogenic CO2 inventory solely based on in-situ measurements from at least two time periods in the interior ocean. However, all such methods face the difficulty of a scarce dataset in both space and time, making the use of appropriate interpolation techniques in time and space a crucial element of any method. Here we present a new method based on the parameter C*, whose variations reflect the total change in dissolved inorganic carbon (DIC) driven by the exchange of CO2 across the air-sea interface. We apply the extended Multiple Linear Regression method (Friis et al., 2005) on C* in order (1) to calculate the change in anthropogenic CO2 from the original DIC/C* measurements, and (2) to interpolate the result onto a spatial grid using other biogeochemical variables (T,S,AOU, etc.). These calculations are made on isopycnal slabs across whole ocean basins. In combination with the transient steady state assumption (Tanhua et al., 2007) providing a temporal correction factor, we address the spatial and temporal interpolation challenges. Using synthetic data from a hindcast simulation with a global ocean biogeochemistry model (NCAR-CCSM with BEC), we tested the method for robustness and accuracy in determining ΔCant. We will present data-based results for all ocean basins, with the most recent estimate of an global uptake of 32±6 Pg C between 1994 and 2007, indicating an uptake rate 2.5±0.5 Pg C yr-1 for this time period. These results are compared with regional and
Huang, Yimei; Zhao, Bo; Chetty, Indrin J; Brown, Stephen; Gordon, James; Wen, Ning
2016-04-01
To evaluate the overall positioning accuracy of image-guided intracranial radiosurgery across multiple linear accelerator platforms. A computed tomography scan with a slice thickness of 1.0 mm was acquired of an anthropomorphic head phantom in a BrainLAB U-frame mask. The phantom was embedded with three 5-mm diameter tungsten ball bearings, simulating a central, a left, and an anterior cranial lesion. The ball bearings were positioned to radiation isocenter under ExacTrac X-ray or cone-beam computed tomography image guidance on 3 Linacs: (1) ExacTrac X-ray localization on a Novalis Tx; (2) cone-beam computed tomography localization on the Novalis Tx; (3) cone-beam computed tomography localization on a TrueBeam; and (4) cone-beam computed tomography localization on an Edge. Each ball bearing was positioned 5 times to the radiation isocenter with different initial setup error following the 4 image guidance procedures on the 3 Linacs, and the mean (µ) and one standard deviation (σ) of the residual error were compared. Averaged overall 3 ball bearing locations, the vector length of the residual setup error in mm (µ ± σ) was 0.6 ± 0.2, 1.0 ± 0.5, 0.2 ± 0.1, and 0.3 ± 0.1 on ExacTrac X-ray localization on a Novalis Tx, cone-beam computed tomography localization on the Novalis Tx, cone-beam computed tomography localization on a TrueBeam, and cone-beam computed tomography localization on an Edge, with their range in mm being 0.4 to 1.1, 0.4 to 1.9, 0.1 to 0.5, and 0.2 to 0.6, respectively. The congruence between imaging and radiation isocenters in mm was 0.6 ± 0.1, 0.7 ± 0.1, 0.3 ± 0.1, and 0.2 ± 0.1, for the 4 systems, respectively. Targeting accuracy comparable to frame-based stereotactic radiosurgery can be achieved with image-guided intracranial stereotactic radiosurgery treatment. © The Author(s) 2015.
Lötsch, Jörn; Thrun, Michael; Lerch, Florian; Brunkhorst, Robert; Schiffmann, Susanne; Thomas, Dominique; Tegder, Irmgard; Geisslinger, Gerd; Ultsch, Alfred
2017-06-07
Lipid metabolism has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid research. We used unsupervised machine-learning to analyze lipid marker serum concentrations, pursuing the hypothesis that for the most relevant markers the emerging data structures will coincide with the diagnosis of MS. Machine learning was implemented as emergent self-organizing feature maps (ESOM) combined with the U*-matrix visualization technique. The data space consisted of serum concentrations of three main classes of lipid markers comprising eicosanoids ( d = 11 markers), ceramides ( d = 10), and lyosophosphatidic acids ( d = 6). They were analyzed in cohorts of MS patients ( n = 102) and healthy subjects ( n = 301). Clear data structures in the high-dimensional data space were observed in eicosanoid and ceramides serum concentrations whereas no clear structure could be found in lysophosphatidic acid concentrations. With ceramide concentrations, the structures that had emerged from unsupervised machine-learning almost completely overlapped with the known grouping of MS patients versus healthy subjects. This was only partly provided by eicosanoid serum concentrations. Thus, unsupervised machine-learning identified distinct data structures of bioactive lipid serum concentrations. These structures could be superimposed with the known grouping of MS patients versus healthy subjects, which was almost completely possible with ceramides. Therefore, based on the present analysis, ceramides are first-line candidates for further exploration as drug-gable targets or biomarkers in MS.
Chen, Hai-Feng
2009-08-01
Oil/water partition coefficient (log P) is one of the key points for lead compound to be drug. In silico log P models based solely on chemical structures have become an important part of modern drug discovery. Here, we report support vector machines, radial basis function neural networks, and multiple linear regression methods to investigate the correlation between partition coefficient and physico-chemical descriptors for a large data set of compounds. The correlation coefficient r(2) between experimental and predicted log P for training and test sets by support vector machines, radial basis function neural networks, and multiple linear regression is 0.92, 0.90, and 0.88, respectively. The results show that non-linear support vector machines derives statistical models that have better prediction ability than those of radial basis function neural networks and multiple linear regression methods. This indicates that support vector machines can be used as an alternative modeling tool for quantitative structure-property/activity relationships studies.
Directory of Open Access Journals (Sweden)
Maria Åström
2012-06-01
Full Text Available The possible effects of different organisations of the science curriculum in schools participating in PISA 2003 are tested with a hierarchical linear model (HLM of two levels. The analysis is based on science results. Swedish schools are free to choose how they organise the science curriculum. They may choose to work subject-specifically (with Biology, Chemistry and Physics, integrated (with Science or to mix these two. In this study, all three ways of organising science classes in compulsory school are present to some degree. None of the different ways of organising science education displayed statistically significant better student results in scientific literacy as measured in PISA 2003. The HLM model used variables of gender, country of birth, home language, preschool attendance, an economic, social and cultural index as well as the teaching organisation.
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
Linearly constrained minimax optimization
DEFF Research Database (Denmark)
Madsen, Kaj; Schjær-Jacobsen, Hans
1978-01-01
We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...
Uys, Marinda; Pottas, Lidia; Vinck, Bart; van Dijk, Catherine
2012-12-01
To date, the main direction in frequency-lowering hearing aid studies has been in relation to speech perception abilities. With improvements in hearing aid technology, interest in musical perception as a dimension that could improve hearing aid users' quality of life has grown. The purpose of this study was to determine the influence of non-linear frequency compression (NFC) on hearing aid users' subjective impressions of listening to music. DESIGN & SAMPLE: A survey research design was implemented to elicit participants' (N=40) subjective impressions of musical stimuli with and without NFC. The use of NFC significantly improved hearing aid users' perception of the musical qualities of overall fidelity, tinniness and reverberance. Although participants preferred to listen to the loudness, fullness, crispness, naturalness and pleasantness of music with the use of NFC, these benefits were not significant. The use of NFC can increase hearing aid users' enjoyment and appreciation of music. Given that a relatively large percentage of hearing aid users express a loss of enjoyment of music, audiologists should not ignore the possible benefits of NFC, especially if one takes into account that previous research indicates speech perception benefits with this technology.
Directory of Open Access Journals (Sweden)
Marinda Uys
2012-12-01
Full Text Available Objective: To date, the main direction in frequency-lowering hearing aid studies has been in relation to speech perception abilities. With improvements in hearing aid technology, interest in musical perception as a dimension that could improve hearing aid users’ quality of life has grown. The purpose of this study was to determine the influence of non-linear frequency compression (NFC on hearing aid users’ subjective impressions of listening to music. Design & sample: A survey research design was implemented to elicit participants’ (N=40 subjective impressions of musical stimuli with and without NFC. Results: The use of NFC significantly improved hearing aid users’ perception of the musical qualities of overall fidelity, tinniness and reverberance. Although participants preferred to listen to the loudness, fullness, crispness, naturalness and pleasantness of music with the use of NFC, these benefits were not significant. Conclusion: The use of NFC can increase hearing aid users’ enjoyment and appreciation of music. Given that a relatively large percentage of hearing aid users express a loss of enjoyment of music, audiologists should not ignore the possible benefits of NFC, especially if one takes into account that previous research indicates speech perception benefits with this technology.
Lin, Sue-Jin; Lam, Janet; Beveridge, Samantha; Vavasour, Irene; Traboulsee, Anthony; Li, David K B; MacKay, Alex; McKeown, Martin; Kosaka, Brenda
2017-01-01
The authors explored the relations between clinical/demographic characteristics and performance on a neuropsychological battery (eight tests) in a cohort (N=46) of multiple sclerosis (MS) subjects. Findings resulted from a secondary analysis of a study examining the relationships between imaging biomarkers in MS and cognitive tasks of executive functioning. The objective was to determine whether the overlapping test results could be judiciously combined and associated with clinical/demographic variables. Canonical-correlation analysis (CCA) was utilized, and it was found that differences between performance on untimed tests, and the sum of performance on timed Trail-Making Tests, Parts A and B, best matched clinical/demographic variables, and gender was the most important feature.
Stoll, R R
1968-01-01
Linear Algebra is intended to be used as a text for a one-semester course in linear algebra at the undergraduate level. The treatment of the subject will be both useful to students of mathematics and those interested primarily in applications of the theory. The major prerequisite for mastering the material is the readiness of the student to reason abstractly. Specifically, this calls for an understanding of the fact that axioms are assumptions and that theorems are logical consequences of one or more axioms. Familiarity with calculus and linear differential equations is required for understand
Allenby, Reg
1995-01-01
As the basis of equations (and therefore problem-solving), linear algebra is the most widely taught sub-division of pure mathematics. Dr Allenby has used his experience of teaching linear algebra to write a lively book on the subject that includes historical information about the founders of the subject as well as giving a basic introduction to the mathematics undergraduate. The whole text has been written in a connected way with ideas introduced as they occur naturally. As with the other books in the series, there are many worked examples.Solutions to the exercises are available onlin
Directory of Open Access Journals (Sweden)
Vivienne R. Johnson
2015-12-01
Full Text Available Predicting the effects of anthropogenic CO2 emissions on coastal ecosystems requires an understanding of the responses of algae, since these are a vital functional component of shallow-water habitats. We investigated microphytobenthic assemblages on rock and sandy habitats along a shallow subtidal pCO2 gradient near volcanic seeps in the Mediterranean Sea. Field studies of natural pCO2 gradients help us understand the likely effects of ocean acidification because entire communities are subjected to a realistic suite of environmental stressors such as over-fishing and coastal pollution. Temperature, total alkalinity, salinity, light levels and sediment properties were similar at our study sites. On sand and on rock, benthic diatom abundance and the photosynthetic standing crop of biofilms increased significantly with increasing pCO2. There were also marked shifts in diatom community composition as pCO2 levels increased. Cyanobacterial abundance was only elevated at extremely high levels of pCO2 (>1400 μatm. This is the first demonstration of the tolerance of natural marine benthic microalgae assemblages to elevated CO2 in an ecosystem subjected to multiple environmental stressors. Our observations indicate that Mediterranean coastal systems will alter as pCO2 levels continue to rise, with increased photosynthetic standing crop and taxonomic shifts in microalgal assemblages.
Directory of Open Access Journals (Sweden)
Christian Wolf
Full Text Available Lymphocyte inhibition by antagonism of α4 integrins is a validated therapeutic approach for relapsing multiple sclerosis (RMS.Investigate the effect of CDP323, an oral α4-integrin inhibitor, on lymphocyte biomarkers in RMS.Seventy-one RMS subjects aged 18-65 years with Expanded Disability Status Scale scores ≤6.5 were randomized to 28-day treatment with CDP323 100 mg twice daily (bid, 500 mg bid, 1000 mg once daily (qd, 1000 mg bid, or placebo.Relative to placebo, all dosages of CDP323 significantly decreased the capacity of lymphocytes to bind vascular adhesion molecule-1 (VCAM-1 and the expression of α4-integrin on VCAM-1-binding cells. All but the 100-mg bid dosage significantly increased total lymphocytes and naive B cells, memory B cells, and T cells in peripheral blood compared with placebo, and the dose-response relationship was shown to be linear. Marked increases were also observed in natural killer cells and hematopoietic progenitor cells, but only with the 500-mg bid and 1000-mg bid dosages. There were no significant changes in monocytes. The number of samples for regulator and inflammatory T cells was too small to draw any definitive conclusions.CDP323 at daily doses of 1000 or 2000 mg induced significant increases in total lymphocyte count and suppressed VCAM-1 binding by reducing unbound very late antigen-4 expression on lymphocytes.ClinicalTrials.gov NCT00726648.
Fragkaki, A G; Farmaki, E; Thomaidis, N; Tsantili-Kakoulidou, A; Angelis, Y S; Koupparis, M; Georgakopoulos, C
2012-09-21
The comparison among different modelling techniques, such as multiple linear regression, partial least squares and artificial neural networks, has been performed in order to construct and evaluate models for prediction of gas chromatographic relative retention times of trimethylsilylated anabolic androgenic steroids. The performance of the quantitative structure-retention relationship study, using the multiple linear regression and partial least squares techniques, has been previously conducted. In the present study, artificial neural networks models were constructed and used for the prediction of relative retention times of anabolic androgenic steroids, while their efficiency is compared with that of the models derived from the multiple linear regression and partial least squares techniques. For overall ranking of the models, a novel procedure [Trends Anal. Chem. 29 (2010) 101-109] based on sum of ranking differences was applied, which permits the best model to be selected. The suggested models are considered useful for the estimation of relative retention times of designer steroids for which no analytical data are available. Copyright © 2012 Elsevier B.V. All rights reserved.
Bakker, Dewi P; Busscher, Henk J; van Zanten, Joyce; de Vries, Jacob; Klijnstra, Job W; van der Mei, Henny C
Many studies have shown relationships of substratum hydrophobicity, charge or roughness with bacterial adhesion, although bacterial adhesion is governed by interplay of different physico-chemical properties and multiple regression analysis would be more suitable to reveal mechanisms of bacterial
Bakker, D.P.; Busscher, H.J.; Zanten, J. van; Vries, J. de; Klijnstra, J.W.; Mei, H.C. van der
2004-01-01
Many studies have shown relationships of substratum hydrophobicity, charge or roughness with bacterial adhesion, although bacterial adhesion is governed by interplay of different physico-chemical properties and multiple regression analysis would be more suitable to reveal mechanisms of bacterial
Bazzoli, Caroline; Retout, Sylvie; Mentré, France
2009-06-30
We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic-pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation-maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first-order linearization estimation methods implemented in the NONMEM software (first-order (FO), first-order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite. Copyright (c) 2009 John Wiley & Sons, Ltd.
Energy Technology Data Exchange (ETDEWEB)
Valsasina, P.; Agosta, F.; Filippi, M. [Scientific Institute Ospedale San Raffaele, Neuroimaging Research Unit, Milan (Italy); Caputo, D. [Scientific Institute Fondazione Don Gnocchi, Department of Neurology, Milan (Italy); Stroman, P.W. [Queen' s University, Department of Diagnostic Radiology, Centre for Neuroscience Studies, Kingston, ON (Canada)
2008-10-15
Functional MRI (fMRI) of the spinal cord is able to provide maps of neuronal activity. Spinal fMRI data have been analyzed in previous studies by calculating the cross-correlation (CC) between the stimulus and the time course of every voxel and, more recently, by using the general linear model (GLM). The aim of this study was to compare three different approaches (CC analysis, GLM and independent component analysis (ICA)) for analyzing fMRI scans of the cervical spinal cord. We analyzed spinal fMRI data from healthy subjects during a proprioceptive and a tactile stimulation by using two model-based approaches, i.e., CC analysis between the stimulus shape and the time course of every voxel, and the GLM. Moreover, we applied independent component analysis, a model-free approach which decomposes the data in a set of source signals. All methods were able to detect cervical cord areas of activity corresponding to the expected regions of neuronal activations. Model-based approaches (CC and GLM) revealed similar patterns of activity. ICA could identify a component correlated to fMRI stimulation, although with a lower statistical threshold than model-based approaches, and many components, consistent across subjects, which are likely to be secondary to noise present in the data. Model-based approaches seem to be more robust for estimating task-related activity, whereas ICA seems to be useful for eliminating noise components from the data. Combined use of ICA and GLM might improve the reliability of spinal fMRI results. (orig.)
Parente, Daniel J; Ray, J Christian J; Swint-Kruse, Liskin
2015-12-01
As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions. © 2015 Wiley Periodicals, Inc.
Parente, Daniel J.; Ray, J. Christian J.; Swint-Kruse, Liskin
2015-01-01
As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for co-evolution between pairs of positions. Co-evolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of co-evolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded co-evolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; “central” positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise co-evolution scores: Instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints – detectable by divergent algorithms – that occur at key protein locations. Finally, we discuss the fact that multiple patterns co-exist in evolutionary data that, together, give rise to emergent protein functions. PMID:26503808
Edwards, Harold M
1995-01-01
In his new undergraduate textbook, Harold M Edwards proposes a radically new and thoroughly algorithmic approach to linear algebra Originally inspired by the constructive philosophy of mathematics championed in the 19th century by Leopold Kronecker, the approach is well suited to students in the computer-dominated late 20th century Each proof is an algorithm described in English that can be translated into the computer language the class is using and put to work solving problems and generating new examples, making the study of linear algebra a truly interactive experience Designed for a one-semester course, this text adopts an algorithmic approach to linear algebra giving the student many examples to work through and copious exercises to test their skills and extend their knowledge of the subject Students at all levels will find much interactive instruction in this text while teachers will find stimulating examples and methods of approach to the subject
İnal, Mikail; Tan, Sinan; Yumusak, Erhan M; Şahan, Mehmet Hamdi; Alpua, Murat; Örnek, Kemal
2017-01-31
Our aim was to evaluate the elasticity features of the optic nerve using strain (SE) and shear wave elastography (SWE) in multiple sclerosis (MS) patients in comparison with healthy subjects. One hundred and seven optic nerves from 54 MS patients and 118 optic nerves from 59 healthy subjects were examined prospectively by SE and SWE. Optic nerves were divided into three types in accordance to the elasticity designs, as follows: type 1 predominantly blue (hardest tissue); type 2 predominantly blue/green (hard tissue); and type 3 predominantly green (intermediate tissue). Quantitative measurements of optic nerve hardness with SWE were analyzed in kilopascals. Elastographic images from healthy volunteers showed mostly type 3 optic nerves (61.9%); type 2 was also found (38.1%), but type 1 was not observed. Elastographic examination of MS patients showed mostly type 2 optic nerves (88%), while some type 1 (4.6%) and type 3 optic nerves (6.5%) were rarely observed. There was a statistically significant difference in terms of elasticity patterns between patients and healthy volunteers (p<0.001). Statistically significant differences were observed between patients and healthy volunteers in the analysis of SWE values (10.381±3.48 kPa and 33.87±11.64 p<0.001). The receiver operating characteristic curve analysis was perfect (0.993; 95% confidence interval [CI]=0.971-0.999), and a cut-off value of 18.3 kPa shear had very high sensitivity and specificity for the patient group. No significant differences were observed between patients with and without previous optic neuritis. SE and SWE examination findings concerning the optic nerve in MS patients demonstrated remarkable differences according to the healthy group.
Zhang, Tingting; Pham, Minh; Sun, Jianhui; Yan, Guofen; Li, Huazhang; Sun, Yinge; Gonzalez, Marlen Z; Coan, James A
2017-12-26
The focus of this paper is on evaluating brain responses to different stimuli and identifying brain regions with different responses using multi-subject, stimulus-evoked functional magnetic resonance imaging (fMRI) data. To jointly model many brain voxels' responses to designed stimuli, we present a new low-rank multivariate general linear model (LRMGLM) for stimulus-evoked fMRI data. The new model not only is flexible to characterize variation in hemodynamic response functions (HRFs) across different regions and stimulus types, but also enables information "borrowing" across voxels and uses much fewer parameters than typical nonparametric models for HRFs. To estimate the proposed LRMGLM, we introduce a new penalized optimization function, which leads to temporally and spatially smooth HRF estimates. We develop an efficient optimization algorithm to minimize the optimization function and identify the voxels with different responses to stimuli. We show that the proposed method can outperform several existing voxel-wise methods by achieving both high sensitivity and specificity. We apply the proposed method to the fMRI data collected in an emotion study, and identify anterior dACC to have different responses to a designed threat and control stimuli. Copyright © 2017. Published by Elsevier Inc.
Sole, Marla A.
2016-01-01
Open-ended questions that can be solved using different strategies help students learn and integrate content, and provide teachers with greater insights into students' unique capabilities and levels of understanding. This article provides a problem that was modified to allow for multiple approaches. Students tended to employ high-powered, complex,…
DEFF Research Database (Denmark)
Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.
2000-01-01
Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets...
Qin, Caiyan; Zhang, Chaoning; Lu, H.
2017-01-01
Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three) permanent magnet
Directory of Open Access Journals (Sweden)
Zhiwei Chen
2014-01-01
Full Text Available Many long-span bridges have been built throughout the world in recent years but they are often subject to multiple types of dynamic loads, especially those located in wind-prone regions and carrying both trains and road vehicles. To ensure the safety and functionality of these bridges, dynamic responses of long-span bridges are often required for bridge assessment. Given that there are several limitations for the assessment based on field measurement of dynamic responses, a promising approach is based on numerical simulation technologies. This paper provides a detailed review of key issues involved in dynamic response analysis of long-span multiload bridges based on numerical simulation technologies, including dynamic interactions between running trains and bridge, between running road vehicles and bridge, and between wind and bridge, and in the wind-vehicle-bridge coupled system. Then a comprehensive review is conducted for engineering applications of newly developed numerical simulation technologies to safety assessment of long-span bridges, such as assessment of fatigue damage and assessment under extreme events. Finally, the existing problems and promising research efforts for the numerical simulation technologies and their applications to assessment of long-span multiload bridges are explored.
Directory of Open Access Journals (Sweden)
Emiliano Santarnecchi
2015-01-01
Full Text Available In ten healthy subjects and in ten patients suffering from Multiple Sclerosis (MS, we investigated the cortical functional changes induced by a standard fatiguing repetitive tapping task. The Cortical Silent Period (CSP, an intracortical, mainly GABAB-mediated inhibitory phenomenon, was recorded by two different hand muscles, one acting as prime mover of the fatiguing index-thumb tapping task (First Dorsal Interosseous, FDI and the other one not involved in the task but sharing largely overlapping central, spinal, and peripheral innervation (Abductor Digiti Minimi, ADM. At baseline, the CSP was shorter in patients than in controls. As fatigue developed, CSP changes involved both the “fatigued” FDI and the “unfatigued” ADM muscles, suggesting a cortical spread of central fatigue mechanisms. Chronic therapy with amantadine annulled differences in CSP duration between controls and patients, possibly through restoration of more physiological levels of intracortical inhibition in the motor cortex. These inhibitory changes correlated with the improvement of fatigue scales. The CSP may represent a suitable marker of neurophysiological mechanisms accounting for central fatigue generation either in controls or in MS patients, involving corticospinal neural pools supplying not only the fatigued muscle but also adjacent muscles sharing an overlapping cortical representation.
Santarnecchi, Emiliano; Rossi, Simone; Bartalini, Sabina; Cincotta, Massimo; Giovannelli, Fabio; Tatti, Elisa; Ulivelli, Monica
2015-01-01
In ten healthy subjects and in ten patients suffering from Multiple Sclerosis (MS), we investigated the cortical functional changes induced by a standard fatiguing repetitive tapping task. The Cortical Silent Period (CSP), an intracortical, mainly GABAB-mediated inhibitory phenomenon, was recorded by two different hand muscles, one acting as prime mover of the fatiguing index-thumb tapping task (First Dorsal Interosseous, FDI) and the other one not involved in the task but sharing largely overlapping central, spinal, and peripheral innervation (Abductor Digiti Minimi, ADM). At baseline, the CSP was shorter in patients than in controls. As fatigue developed, CSP changes involved both the "fatigued" FDI and the "unfatigued" ADM muscles, suggesting a cortical spread of central fatigue mechanisms. Chronic therapy with amantadine annulled differences in CSP duration between controls and patients, possibly through restoration of more physiological levels of intracortical inhibition in the motor cortex. These inhibitory changes correlated with the improvement of fatigue scales. The CSP may represent a suitable marker of neurophysiological mechanisms accounting for central fatigue generation either in controls or in MS patients, involving corticospinal neural pools supplying not only the fatigued muscle but also adjacent muscles sharing an overlapping cortical representation.
2017-01-01
Multiple-pinhole (MPH) glasses are currently sold in many countries with unproven advertisements; however, their objective and subjective effects have not been investigated. Therefore, to investigate the effects of MPH glasses excluding the single-pinhole (SPH) effect, we compared the visual functional changes, reading speed, and ocular discomfort after reading caused by MPH and SPH glasses. Healthy 36 participants with a mean age of 33.1 years underwent examinations of pupil size, visual acuity (VA), depth of focus (DOF), and near point accommodation (NPA); tests for visual field (VF), contrast sensitivity (CS), stereopsis, and reading speed; and a survey of ocular discomfort after reading. Both types of pinhole glasses enlarged pupil diameter and improved VA, DOF, and NPA. However, CS, stereopsis, and VF parameters deteriorated. In comparison with SPH glasses, MPH glasses induced smaller pupil dilation (5.3 and 5.9 mm, P SPH glasses showed the slowest reading speed. Both types of glasses caused significant ocular discomfort after reading compared with baseline, and symptoms were worst with MPH glasses. In conclusion, both types of pinhole glasses had positive effects due to the pinhole effect; however, they had negative effects on VF, CS, stereopsis, reading speed, and ocular discomfort. In spite of the increased luminance and preserved peripheral VF with MPHs, these glasses caused more severe ocular discomfort than SPH glasses. This clinical trial was registered at www.ClinicalTrials.gov (Identifier: NCT02572544). PMID:28378561
Kim, Won Soo; Park, In Ki; Park, Young Kee; Chun, Yeoun Sook
2017-05-01
Multiple-pinhole (MPH) glasses are currently sold in many countries with unproven advertisements; however, their objective and subjective effects have not been investigated. Therefore, to investigate the effects of MPH glasses excluding the single-pinhole (SPH) effect, we compared the visual functional changes, reading speed, and ocular discomfort after reading caused by MPH and SPH glasses. Healthy 36 participants with a mean age of 33.1 years underwent examinations of pupil size, visual acuity (VA), depth of focus (DOF), and near point accommodation (NPA); tests for visual field (VF), contrast sensitivity (CS), stereopsis, and reading speed; and a survey of ocular discomfort after reading. Both types of pinhole glasses enlarged pupil diameter and improved VA, DOF, and NPA. However, CS, stereopsis, and VF parameters deteriorated. In comparison with SPH glasses, MPH glasses induced smaller pupil dilation (5.3 and 5.9 mm, P pinhole glasses was significantly slower than baseline; SPH glasses showed the slowest reading speed. Both types of glasses caused significant ocular discomfort after reading compared with baseline, and symptoms were worst with MPH glasses. In conclusion, both types of pinhole glasses had positive effects due to the pinhole effect; however, they had negative effects on VF, CS, stereopsis, reading speed, and ocular discomfort. In spite of the increased luminance and preserved peripheral VF with MPHs, these glasses caused more severe ocular discomfort than SPH glasses. © 2017 The Korean Academy of Medical Sciences.
Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J
2014-08-27
State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.
Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara
2017-01-01
In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.
Palmer, D; Pou, J O; Gonzalez-Sabaté, L; Díaz-Ferrero, J
2018-05-01
The formation of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) is governed by complex chemical reactions with complex kinetic models. The simulation of Municipal Solid Waste incinerators, or other industrial thermal processes, is a powerful tool that can be used to optimize and control them, and reducing the number of components to simulate is mandatory for a proper use. In this study it has been determined that only the formation of 3 of the 17 main PCDD/F congeners can be considered as linearly independent. This fact has been used to establish linear regression models that are able to estimate properly the total amount and toxicity of a sample considering only the amount of 1,2,3,6,7,8-HxCDD, OCDF and 2,3,7,8-TCDF. All models have been validated using new samples performing a close approach to the real values provided by complete analytical studies. The average relative error is 3.5% and the maximum relative error is below 9% for these new testing samples. The main goal of our investigation is to build a dynamic simulation process of a MSW facility and include the dioxins formation on it using these models. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Fujita Shigetaka
2016-01-01
Full Text Available The mean flowfield of a linear array of multiple rectangular jets run through transversely with a two-dimensional jet, has been investigated, experimentally. The object of this experiment is to operate both the velocity scale and the length scale of the multiple rectangular jets using a two-dimensional jet. The reason of the adoption of this nozzle exit shape was caused by the reports of authors in which the cruciform nozzle promoted the inward secondary flows strongly on both the two jet axes. Aspect ratio of the rectangular nozzle used in this experiment was 12.5. Reynolds number based on the nozzle width d and the exit mean velocity Ue (≅ 39 m / s was kept constant 25000. Longitudinal mean velocity was measured using an X-array Hot-Wire Probe (lh = 3.1 μm in diameter, dh = 0.6 mm effective length : dh / lh = 194 operated by the linearized constant temperature anemometers (DANTEC, and the spanwise and the lateral mean velocities were measured using a yaw meter. The signals from the anemometers were passed through the low-pass filters and sampled using A.D. converter. The processing of the signals was made by a personal computer. Acquisition time of the signals was usually 60 seconds. From this experiment, it was revealed that the magnitude of the inward secondary flows on both the y and z axes in the upstream region of the present jet was promoted by a two-dimensional jet which run through transversely perpendicular to the multiple rectangular jets, therefore the potential core length on the x axis of the present jet extended 2.3 times longer than that of the multiple rectangular jets, and the half-velocity width on the rectangular jet axis of the present jet was suppressed 41% shorter compared with that of the multiple rectangular jets.
Directory of Open Access Journals (Sweden)
R. Talebitooti
Full Text Available In this paper the effect of quadratic and cubic non-linearities of the system consisting of the crankshaft and torsional vibration damper (TVD is taken into account. TVD consists of non-linear elastomer material used for controlling the torsional vibration of crankshaft. The method of multiple scales is used to solve the governing equations of the system. Meanwhile, the frequency response of the system for both harmonic and sub-harmonic resonances is extracted. In addition, the effects of detuning parameters and other dimensionless parameters for a case of harmonic resonance are investigated. Moreover, the external forces including both inertia and gas forces are simultaneously applied into the model. Finally, in order to study the effectiveness of the parameters, the dimensionless governing equations of the system are solved, considering the state space method. Then, the effects of the torsional damper as well as all corresponding parameters of the system are discussed.
Meng, Yilin; Roux, Benoît
2015-08-11
The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.
Krüger, Theresa; Behrens, Janina R; Grobelny, Anuschka; Otte, Karen; Mansow-Model, Sebastian; Kayser, Bastian; Bellmann-Strobl, Judith; Brandt, Alexander U; Paul, Friedemann; Schmitz-Hübsch, Tanja
2017-01-13
Physical activity (PA) is frequently restricted in people with multiple sclerosis (PwMS) and aiming to enhance PA is considered beneficial in this population. We here aimed to explore two standard methods (subjective plus objective) to assess PA reduction in PwMS and to describe the relation of PA to health-related quality of life (hrQoL). PA was objectively measured over a 7-day period in 26 PwMS (EDSS 1.5-6.0) and 30 matched healthy controls (HC) using SenseWear mini® armband (SWAmini) and reported as step count, mean total and activity related energy expenditure (EE) as well as time spent in PA of different intensities. Measures of EE were also derived from self-assessment with IPAQ (International Physical Activity Questionnaire) long version, which additionally yielded information on the context of PA and a classification into subjects' PA levels. To explore the convergence between both types of assessment, IPAQ categories (low, moderate, high) were related to selected PA parameters from objective assessment using ANOVA. Group differences and associated effect sizes for all PA parameters as well as their relation to clinical and hrQoL measures were determined. Both, SWAmini and IPAQ assessment, captured differences in PA between PwMS and HC. IPAQ categories fit well with common cut-offs for step count (p = 0.002) and mean METs (p = 0.004) to determine PA levels with objective devices. Correlations between specifically matched pairs of IPAQ and SWAmini parameters ranged between r .288 and r .507. Concerning hrQoL, the lower limb mobility subscore was related to four PA measures, while a relation with patients' report of general contentment was only seen for one. Both methods of assessment seem applicable in PwMS and able to describe reductions in daily PA at group level. Whether they can be used to track individual effects of interventions to enhance PA levels needs further exploration. The relation of PA measures with hrQoL seen with lower limb
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
Directory of Open Access Journals (Sweden)
Bochkin G.A., Fel'dman E.B., Vasil'ev S.G.
2016-12-01
Full Text Available Experimental and theoretical investigations of dynamics and relaxation of multiple quantum (MQ nuclear magnetic resonance (NMR coherences of the zeroth and second orders are performed in a quasi-one-dimensional chain of nuclear spins of 19F in calcium fluorapatite. MQ NMR dynamics are studied on the preparation period of the MQ NMR experiment in the approximation of nearest neighbor interactions. The density matrix of the system at the end of the preparation period is used as the initial condition for the study of the relaxation process on the evolution period of the MQ NMR experiment. The relaxation asymptotics of the intensity of the MQ NMR coherence of the zeroth order is obtained. Relaxation of the MQ NMR coherence of the second order is investigated with ZZ part of the dipole-dipole interactions. The experimental data qualitatively agree with the results of the developed theory.
DEFF Research Database (Denmark)
Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.
2000-01-01
Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets...... of LTI models are employed to approximate the faulty, reconfigured and nominal nonlinear systems respectively with respect to the on-line information of the operating system, and a set of compensating modules are proposed and designed so as to make the local LTI model approximating to the reconfigured...... corresponding to the updating of local LTI models, which validations are determined by the model approximation errors and the optimal index of local design. The test on a nonlinear ship propulsion system shows the promising potential of this method for system reconfiguration...
Dahm, Stefan; Bertz, Joachim; Barnes, Benjamin; Kraywinkel, Klaus
2018-01-10
Large temporal and geographical variation in survival rates estimated from epidemiological cancer registries coupled with heterogeneity in death certificate only (DCO) notifications makes it difficult to interpret trends in survival. The aim of our study is to introduce a method for estimating such trends while accounting for heterogeneity in DCO notifications in a cancer site-specific manner. We used the data of 4.0 million cancer cases notified in 14 German epidemiological cancer registries. Annual 5-year relative survival rates from 2002 through 2013 were estimated, and proportions of DCO notifications were recorded. "DCO-excluded" survival rates were regressed on DCO proportions and calendar years using a mixed linear model with cancer registry as a random effect. Based on this model, trends in survival rates were estimated for Germany at 0% DCO. For most cancer sites and age groups, we estimated significant positive trends in survival. Age-standardized survival for all cancers combined increased by 7.1% units for women and 10.8% units for men. The described method could be used to estimate trends in cancer survival based on the data from epidemiological cancer registries with differing DCO proportions and with changing DCO proportions over time. Copyright © 2018 Elsevier Inc. All rights reserved.
Sahai, Vivek
2013-01-01
Beginning with the basic concepts of vector spaces such as linear independence, basis and dimension, quotient space, linear transformation and duality with an exposition of the theory of linear operators on a finite dimensional vector space, this book includes the concept of eigenvalues and eigenvectors, diagonalization, triangulation and Jordan and rational canonical forms. Inner product spaces which cover finite dimensional spectral theory and an elementary theory of bilinear forms are also discussed. This new edition of the book incorporates the rich feedback of its readers. We have added new subject matter in the text to make the book more comprehensive. Many new examples have been discussed to illustrate the text. More exercises have been included. We have taken care to arrange the exercises in increasing order of difficulty. There is now a new section of hints for almost all exercises, except those which are straightforward, to enhance their importance for individual study and for classroom use.
Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.
2017-03-01
To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.
Baba, Toshimi; Gotoh, Yusaku; Yamaguchi, Satoshi; Nakagawa, Satoshi; Abe, Hayato; Masuda, Yutaka; Kawahara, Takayoshi
2017-08-01
This study aimed to evaluate a validation reliability of single-step genomic best linear unbiased prediction (ssGBLUP) with a multiple-lactation random regression test-day model and investigate an effect of adding genotyped cows on the reliability. Two data sets for test-day records from the first three lactations were used: full data from February 1975 to December 2015 (60 850 534 records from 2 853 810 cows) and reduced data cut off in 2011 (53 091 066 records from 2 502 307 cows). We used marker genotypes of 4480 bulls and 608 cows. Genomic enhanced breeding values (GEBV) of 305-day milk yield in all the lactations were estimated for at least 535 young bulls using two marker data sets: bull genotypes only and both bulls and cows genotypes. The realized reliability (R 2 ) from linear regression analysis was used as an indicator of validation reliability. Using only genotyped bulls, R 2 was ranged from 0.41 to 0.46 and it was always higher than parent averages. The very similar R 2 were observed when genotyped cows were added. An application of ssGBLUP to a multiple-lactation random regression model is feasible and adding a limited number of genotyped cows has no significant effect on reliability of GEBV for genotyped bulls. © 2016 Japanese Society of Animal Science.
Directory of Open Access Journals (Sweden)
Giovanni Leopoldo Rozza
2015-09-01
Full Text Available With world becoming each day a global village, enterprises continuously seek to optimize their internal processes to hold or improve their competitiveness and make better use of natural resources. In this context, decision support tools are an underlying requirement. Such tools are helpful on predicting operational issues, avoiding cost risings, loss of productivity, work-related accident leaves or environmental disasters. This paper has its focus on the prediction of spent liquor caustic concentration of Bayer process for alumina production. Caustic concentration measuring is essential to keep it at expected levels, otherwise quality issues might arise. The organization requests caustic concentration by chemical analysis laboratory once a day, such information is not enough to issue preventive actions to handle process inefficiencies that will be known only after new measurement on the next day. Thereby, this paper proposes using Multiple Linear Regression and Artificial Neural Networks techniques a mathematical model to predict the spent liquor´s caustic concentration. Hence preventive actions will occur in real time. Such models were built using software tool for numerical computation (MATLAB and a statistical analysis software package (SPSS. The models output (predicted caustic concentration were compared with the real lab data. We found evidence suggesting superior results with use of Artificial Neural Networks over Multiple Linear Regression model. The results demonstrate that replacing laboratorial analysis by the forecasting model to support technical staff on decision making could be feasible.
Directory of Open Access Journals (Sweden)
Vukojević Vesna
2016-01-01
Full Text Available The study focuses on the mental health and subjective well-being (SWB of Serbian immigrants of the first generation in Canada. We wanted to examine if perceived discrimination, sense of control, self-esteem and perceived multiple discrepancy affect their mental health and SWB. Our results indicate that self-esteem and sense of control have a positive effect on mental health and all aspects of the SWB, while the perceived discrimination and perceived multiple discrepancy negatively affect SWB and mental health. Self-esteem was the most salient predictor of mental health, while the perceived multiple discrepancy was the most salient predictor of life satisfaction of Serbian immigrants.
Harmon, H James
2008-09-01
Real-time chemical sensors have been developed based on the binding of the analyte to monolayers of either porphyrin alone or porphyrins incorporated into the active site of enzymes. Binding of an analyte to porphyrin alone causes a redistribution of electrons in the porphyrin, altering the energy levels of the electrons which manifests as a change in the absorbance spectrum of the porphyrin. Porphyrins incorporated into the active site of enzymes such as cholinesterases are displaced when a competitive inhibitor such as nerve agents binds to the active site; this results in the porphyrin experiencing a different microenvironment than in the protein, resulting in a change in absorbance spectrum. Based on the Beer-Lambert relationship of concentration and absorbance, the limit of detection (LOD) for porphyrin-based sensors should be approximately 2 nM although LODs several orders of magnitude lower have been published. This increased sensitivity is explained as the result of multiple photon absorbance by the porphyrin and limiting self-quenching energy transfer reactions in the evanescent monolayer.
Mevissen, E.H.M.; Didden, H.C.M.; Korzilius, H.P.L.M.; Jongh, A. de
2017-01-01
BACKGROUND: This study explored the effectiveness of eye movement desensitisation and reprocessing (EMDR) therapy for post-traumatic stress disorder (PTSD) in persons with mild to borderline intellectual disability (MBID) using a multiple baseline across subjects design. METHODS: One child and one
Mevissen, Liesbeth; Didden, Robert; Korzilius, Hubert; de Jongh, Ad
2017-01-01
Background: This study explored the effectiveness of eye movement desensitisation and reprocessing (EMDR) therapy for post-traumatic stress disorder (PTSD) in persons with mild to borderline intellectual disability (MBID) using a multiple baseline across subjects design. Methods: One child and one adolescent with MBID, who met diagnostic criteria…
Zhou, Pei-Jun; Xu, Da; Yu, Zi-Cheng; Wang, Xiang-Hui; Shao, Kun; Zhao, Ju-Ping
2007-01-01
To investigate the pharmacokinetics of mycophenolic acid (MPA) in Chinese adult renal allograft recipients, and to generate the validated model equations for estimation of the MPA area under the plasma concentration-time curve from 0 to 12 hours (AUC(12)) with a limited sampling strategy. The pharmacokinetics in 75 Chinese renal allograft recipients treated with mycophenolate mofetil 2 g/day in combination with cyclosporin and corticosteroids were determined. The MPA concentration was assayed by high-performance liquid chromatography at pre-dose (C(0)) and at 0.5 (C(0.5)), 1 (C(1)), 1.5 (C(1.5)), 2 (C(2)), 4 (C(4)), 6 (C(6)), 8 (C(8)), 10 (C(10)) and 12 (C(12)) hours after dosing on day 14 post-transplant. Patients were randomly divided into: (i) a model group (n = 50) to generate the model equations by multiple stepwise regression analysis for estimation of the MPA AUC by a limited sampling strategy; and (ii) a validation group (n = 25) to evaluate the predictive performance of the model equations. The mean MPA AUC(12) was 52.97 +/- 15.09 mg . h/L, ranging from 24.0 to 102.3 mg . h/L. The patient's age and serum albumin level had a significant impact on the MPA AUC(12). The correlation between the pre-dose MPA trough level (C(0)) and the MPA AUC(12) was poor (r(2) = 0.02, p = 0.33). Model equations 7 (MPA AUC(12) = 14.81 + 0.80 . C(0.5) + 1.56 . C(2) + 4.80 . C(4), r(2) = 0.70) and 11 (MPA AUC(12) = 11.29 + 0.51 . C(0.5) + 2.13 . C(2) + 8.15 . C(8), r(2) = 0.88) were selected for MPA AUC calculation in Chinese patients, resulting in good agreements between the estimated MPA AUC and the full MPA AUC(12), with a mean prediction error of +/-10.1 and +/-6.9 mg . h/L, respectively. In Chinese renal allograft recipients, MPA pharmacokinetics manifest substantial interindividual variability, and the MPA AUC(12) tends to be higher than that in Caucasian patients receiving the same dose of mycophenolate mofetil. Two validated model equations with three sampling timepoints
Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong
2014-09-01
Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.
Directory of Open Access Journals (Sweden)
K. P. Moustris
2012-01-01
Full Text Available An attempt is made to forecast the daily maximum surface ozone concentration for the next 24 hours, within the greater Athens area (GAA. For this purpose, we applied Multiple Linear Regression (MLR models against a forecasting model based on Artificial Neural Network (ANN approach. The availability of basic meteorological parameters is of great importance in order to forecast the ozone’s concentration levels. Modelling was based on recorded meteorological and air pollution data from thirteen monitoring sites within the GAA (network of the Hellenic Ministry of the Environment, Energy and Climate Change over five years from 2001 to 2005. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that in every aspect, the prognostic model by far is the ANN model. This suggests that the ANN model can be used to issue warnings for the general population and mainly sensitive groups.
Cui, Haibo; Wei, Xiaomei; Huang, Yu; Hu, Bin; Fang, Yaping; Wang, Jia
2014-01-01
Among human influenza viruses, strain A/H3N2 accounts for over a quarter of a million deaths annually. Antigenic variants of these viruses often render current vaccinations ineffective and lead to repeated infections. In this study, a computational model was developed to predict antigenic variants of the A/H3N2 strain. First, 18 critical antigenic amino acids in the hemagglutinin (HA) protein were recognized using a scoring method combining phi (ϕ) coefficient and information entropy. Next, a prediction model was developed by integrating multiple linear regression method with eight types of physicochemical changes in critical amino acid positions. When compared to other three known models, our prediction model achieved the best performance not only on the training dataset but also on the commonly-used testing dataset composed of 31878 antigenic relationships of the H3N2 influenza virus.
Whitlock, C. H., III
1977-01-01
Constituents with linear radiance gradients with concentration may be quantified from signals which contain nonlinear atmospheric and surface reflection effects for both homogeneous and non-homogeneous water bodies provided accurate data can be obtained and nonlinearities are constant with wavelength. Statistical parameters must be used which give an indication of bias as well as total squared error to insure that an equation with an optimum combination of bands is selected. It is concluded that the effect of error in upwelled radiance measurements is to reduce the accuracy of the least square fitting process and to increase the number of points required to obtain a satisfactory fit. The problem of obtaining a multiple regression equation that is extremely sensitive to error is discussed.
Jeanjean, L; Castelnovo, G; Carlander, B; Villain, M; Mura, F; Dupeyron, G; Labauge, P
2008-11-01
Multiple sclerosis is a common disabling progressive neurological disorder. Axonal loss is thought to be a likely cause of persistent disability after a multiple sclerosis relapse. Retinal nerve fiber layer (RNFL) imaging by optical coherence tomography (OCT) seems to be a non-invasive way of detecting optical axonal loss following optic neuritis. To determine whether multiple sclerosis affects retinal nerve fiber layer measurements obtained with optical coherence tomography (OCT3-Carl Zeiss Meditec, Dublin, California, USA). Diagnosis of MS was based on the MacDonald criteria. The cohort was divided into two groups based on their clinical course (multiple sclerosis with [n=8; 16 eyes] or without [n=7; 14 eyes] optic neuritis antecedents). The disease-free controls were matched for age and gender (n=15; 30 eyes). Retinal nerve fiber layer thickness was measured using optical coherence tomography (OCT; fastRNFL and RNFL thickness software protocol). Visual acuity, visual field, color vision were also noted. There were highly significant reductions (pcolor vision were globally less altered than OCT. There were no significant relationships among RNFL thickness and visual acuity, visual field, or color vision. This study has demonstrated the anatomic changes of the retinal nerve fiber layer of patients with multiple sclerosis with optic neuritis antecedents. Thus axonal loss following optic neuritis can be detected with OCT. But the retinal nerve fiber layer of patients without optic neuritis is also thinner than disease-free controls so that chronic optic axonal loss can be frequent in multiple sclerosis. Additionally, OCT was more sensitive than the common ophthalmological explorations to detect optical nerve impairment during multiple sclerosis. Finally, we demonstrated that two procedures fastRNFL and RNFL could be used to detect optic nerve impairment.
Directory of Open Access Journals (Sweden)
paresa soulimani
2016-06-01
Full Text Available Pearl millet has tolerance to harsh growing conditions such as drought. It is at least equivalent to maize and generally superior to sorghum in protein content and metabolizable energy levels. Thus it is of importance for poultry feeding. Amino acid (AA determination is expensive and time consuming. Therefore nutritionists have prompted a search for alternatives to estimate AA levels. Traditionally, two methods of predicting AA levels have been developed using multiple linear regression (MLR with an input of either CP or proximate analysis. Artificial neural networks (ANN may be more effective to predict AA concentration in feedstuff. Therefore a study was conducted to predict the AAs level in pearl millet with either MLR or ANN. Fifty two samples of pearl millet’s data lines contained chemical compositions and AAs which collected from literature were used to find the relationship between chemical analysis as xi and AA contents as y. For both MLR and ANN models chemical composition (dry matter, ash, crude fiber, crude protein, ether extract was used as inputs and each individual AA was the output in each model. The results of this study showed that it is possible to predict AAs with a simple analytical determination of proximate analysis. Furthermore ANN models could more effectively identify the relationship between AAs and proximate analysis than linear regression model.
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.
Azadi, Sama; Karimi-Jashni, Ayoub
2016-02-01
Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate. Copyright © 2015 Elsevier Ltd. All rights reserved.
Yano, Kentaro; Mita, Suzune; Morimoto, Kaori; Haraguchi, Tamami; Arakawa, Hiroshi; Yoshida, Miyako; Yamashita, Fumiyoshi; Uchida, Takahiro; Ogihara, Takuo
2015-09-01
P-glycoprotein (P-gp) regulates absorption of many drugs in the gastrointestinal tract and their accumulation in tumor tissues, but the basis of substrate recognition by P-gp remains unclear. Bitter-tasting phenylthiocarbamide, which stimulates taste receptor 2 member 38 (T2R38), increases P-gp activity and is a substrate of P-gp. This led us to hypothesize that bitterness intensity might be a predictor of P-gp-inhibitor/substrate status. Here, we measured the bitterness intensity of a panel of P-gp substrates and nonsubstrates with various taste sensors, and used multiple linear regression analysis to examine the relationship between P-gp-inhibitor/substrate status and various physical properties, including intensity of bitter taste measured with the taste sensor. We calculated the first principal component analysis score (PC1) as the representative value of bitterness, as all taste sensor's outputs shared significant correlation. The P-gp substrates showed remarkably greater mean bitterness intensity than non-P-gp substrates. We found that Km value of P-gp substrates were correlated with molecular weight, log P, and PC1 value, and the coefficient of determination (R(2) ) of the linear regression equation was 0.63. This relationship might be useful as an aid to predict P-gp substrate status at an early stage of drug discovery. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Chen, Qingxia; Ibrahim, Joseph G
2014-07-01
Multiple Imputation, Maximum Likelihood and Fully Bayesian methods are the three most commonly used model-based approaches in missing data problems. Although it is easy to show that when the responses are missing at random (MAR), the complete case analysis is unbiased and efficient, the aforementioned methods are still commonly used in practice for this setting. To examine the performance of and relationships between these three methods in this setting, we derive and investigate small sample and asymptotic expressions of the estimates and standard errors, and fully examine how these estimates are related for the three approaches in the linear regression model when the responses are MAR. We show that when the responses are MAR in the linear model, the estimates of the regression coefficients using these three methods are asymptotically equivalent to the complete case estimates under general conditions. One simulation and a real data set from a liver cancer clinical trial are given to compare the properties of these methods when the responses are MAR.
Marami Milani, Mohammad Reza; Hense, Andreas; Rahmani, Elham; Ploeger, Angelika
2016-07-23
This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new ), and respiratory rate predictor RRP) with three main components of cow's milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p -value < 0.001 and R ² (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation ( p -value < 0.001) with R ² (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.
Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo
2011-03-04
Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.
El Bach, A.; Salhi, A.; Cambon, Claude
2008-04-01
The linear effect of rapid rotation is studied on the transport by homogeneous turbulence of a passive scalar with vertical mean scalar gradient. Connection with one-particle diffusion studied by Cambon et al. [C. Cambon, F.S. Godeferd, F. Nicolleau, J.C. Vassilicos, Turbulent diffusion in rapidly rotating turbulence with and without stable stratification, J. Fluid Mech. 499 (2004) 231-255] is discussed. The input of the initial anisotropy of the velocity field is then investigated in the axisymmetric case, using a general and systematic way to construct axisymmetric initial data: a classical expansion in terms of scalar spherical harmonics for the 3D spectral density of kinetic energy and a modified expansion for the polarization anisotropy. The scalar variance exhibits a quadratic evolution (∝t) for short times and a linear one (∝t) for larger times. The long-time behaviour looks similar to the classical 'Brownian' evolution but it has a very different origin: a linear impact of dispersive inertial waves via phase-mixing instead of a nonlinearly-induced random walk. It is shown that this trend is not altered by the polarization anisotropy. The vertical scalar flux varies linearly with time for short times and tends to a plateau for larger times. To cite this article: A. El Bach et al., C. R. Mecanique 336 (2008).
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…
Sergott, R C; Brown, M J; Polenta, R M; Lisak, R P; Silberberg, D H
1985-10-01
We injected guinea pig optic nerves with serum from patients with MS or acute optic neuritis (ON), or normal subjects. Serum from 12 of 17 MS patients, 3 of 3 patients with ON, and 5 of 11 normal age- and sex-matched controls produced myelin vesiculation and demyelination 24 hours after injection. Nerves injected with demyelinating serum contained oligodendrocytes with pyknotic nuclei and edematous, rarefied cytoplasm. Nerves injected with serum that did not cause demyelination did not have these oligodendrocyte changes. Serum from normal subjects or patients with MS may induce in vivo demyelination in mammalian CNS.
Perry, Chris; Ball, Ian
2004-01-01
This study explores issues in teacher education that increase our understanding of, and response to, the individual differences displayed by learners. A large undergraduate teacher education cohort provided evidence of the range and distribution of preferences in learning styles, psychological types and multiple intelligences. This information…
African Journals Online (AJOL)
by considering two linear transforms of the unbiased estimator of the coefﬁcients of the multiple linear regression model. Key words/phrases: Admissibility, linear transforms, multivariate statistics, strong-and weak mean square criteria. INTRODUCTION. Improvement of estimation and prediction by introducing biased ...
Bourlès, Henri
2013-01-01
Linear systems have all the necessary elements (modeling, identification, analysis and control), from an educational point of view, to help us understand the discipline of automation and apply it efficiently. This book is progressive and organized in such a way that different levels of readership are possible. It is addressed both to beginners and those with a good understanding of automation wishing to enhance their knowledge on the subject. The theory is rigorously developed and illustrated by numerous examples which can be reproduced with the help of appropriate computation software. 60 exe
Kanters, Deon; ten Hove, Willem; Luijk, Bart; van Aalst, Corneli; Schweizer, René C; Lammers, Jan-Willem J; Leufkens, Hubert G M; Raaijmakers, Jan A M; Bracke, Madelon; Koenderman, Leo
2007-11-01
Allergic asthma is associated with chronic airway and systemic immune responses. Systemic responses include priming of peripheral blood eosinophils, which is enhanced after allergen challenge. In a subpopulation of asthmatic subjects, neutrophils are associated with bronchial inflammation. We sought to monitor systemic granulocyte priming in allergic asthmatic subjects as a consequence of chronic and acute inflammatory signals initiated by allergen challenge. Blood was taken at baseline and 6 to 24 hours after allergen challenge in asthmatic subjects with and without late asthmatic responses. Systemic granulocyte priming was studied by using expression of cellular markers, such as alpha-chain of Mac-1 (alpha m)/CD11b, L-selectin/CD62L, and an activation epitope present on Fc gamma RII/CD32 recognized by monoclonal phage antibody A17. Eosinophils of asthmatic subjects have a primed phenotype identified by cell-surface markers. Neutrophils of these patients were subtly primed, which was only identified after activation with N-formyl-methionyl-leucyl-phenylalanine. After allergen challenge, an acute increase in eosinophil priming characterized by enhanced expression of activated Fc gamma RII was found in patients experiencing a late asthmatic response and not in patients with a single early asthmatic response. In contrast, expression of alpha m/CD11b and L-selectin on granulocytes was not different between control and asthmatic subjects and was not affected by allergen challenge. Interestingly, expression of both adhesion molecules was positively correlated, and alpha m expression on eosinophils and neutrophils correlated positively with bronchial hyperresponsiveness. Different phases, phenotypes, or both of allergic asthma are associated with distinct priming profiles of inflammatory cells in peripheral blood. Insight in differences of systemic innate responses will lead to better definition of asthma subtypes and to better designs of new therapeutic options.
Winkelmann, Rainer
2004-01-01
The previous literature on the determinants of individual well-being has failed to fully account for the interdependencies in well-being at the family level. This paper develops an ordered probit model with multiple random effects that allows to identify the intrafamily correlation in well-being. The parameters of the model can be estimated with panel data using Maximum Marginal Likelihood. The approach is illustrated in an application using panel data for the period 1984-1997 from the German...
Pasquinelli, Claudio; McPhee, Fiona; Eley, Timothy; Villegas, Criselda; Sandy, Katrina; Sheridan, Pamela; Persson, Anna; Huang, Shu-Pang; Hernandez, Dennis; Sheaffer, Amy K; Scola, Paul; Marbury, Thomas; Lawitz, Eric; Goldwater, Ronald; Rodriguez-Torres, Maribel; Demicco, Michael; Wright, David; Charlton, Michael; Kraft, Walter K; Lopez-Talavera, Juan-Carlos; Grasela, Dennis M
2012-04-01
Hepatitis C virus (HCV) protease inhibitors combined with pegylated alfa interferon-ribavirin have demonstrated improved efficacy compared with pegylated alfa interferon-ribavirin alone for the treatment of chronic hepatitis C. Asunaprevir (BMS-650032), a novel HCV NS3 protease inhibitor in clinical development, was evaluated for safety, antiviral activity, and resistance in four double-blind, placebo-controlled, sequential-panel, single- and multiple-ascending-dose (SAD and MAD) studies in healthy subjects or subjects with chronic HCV genotype 1 infection. In SAD studies, subjects (healthy or with chronic HCV infection) were randomized to receive asunaprevir in dose groups of 10 to 1,200 mg or a placebo. In MAD studies, healthy subjects were randomized to receive asunaprevir in dose groups of 10 to 600 mg twice daily or a placebo for 14 days; subjects with HCV infection received asunaprevir in dose groups of 200 to 600 mg twice daily, or a placebo, for 3 days. Across all four studies, headache and diarrhea were the most frequent adverse events in asunaprevir recipients. Asunaprevir at doses of 200 to 600 mg resulted in rapid HCV RNA decreases from the baseline; maximal mean changes in HCV RNA over time were 2.7 and 3.5 log(10) IU/ml in the SAD and MAD studies, respectively. No enrichment of signature asunaprevir-resistant viral variants was detected. In conclusion, the novel NS3 protease inhibitor asunaprevir, when administered at single or multiple doses of 200 to 600 mg twice daily, is generally well tolerated, achieving rapid and substantial decreases in HCV RNA levels in subjects chronically infected with genotype 1 HCV.
Albert, Paul S.; Harel, Ofer; Perkins, Neil; Browne, Richard
2011-01-01
Background The goal of many studies in environmental epidemiology is to assess the relationship between chemical exposure and disease outcome. Often various assays can be used to measure a particular environmental exposure, with some assays being more invasive or expensive than others. Methods We consider the situation in which 2 assays can be used to measure an environmental exposure. The first assay has measurement error and is subject to a lower detection limit (LOD), and the second assay has less measurement error and is not subject to a lower LOD. In this situation, the first assay is less invasive or less expensive and is measured in all study participants, whereas the second assay is more invasive or more expensive and is only measured in a subset of individuals. We develop a flexible class of regression models that incorporates both sets of assay measurements and allows for continuous or binary outcomes. We explore different design strategies for selecting the subset of patients in whom to measure the second assay. One design strategy is to measure the second more invasive or expensive assay only when the first assay is below LOD. We compare these designs with a simple design in which the second assay is measured in a random subset of patients without regard to the results of the first assay. Results We develop estimation approaches for these regression models. We demonstrate through simulations that there are efficiency advantages of measuring the second assay in at least a fraction of cases in which the first assay is above LOD. We illustrate the methodology by using data from a study examining the effect of environmental polychlorinated biphenyl exposure on the risk of endometriosis. Conclusion The proposed methodology has good statistical properties and will be a useful methodological technique for studying the effect of exposure on outcome when exposure assays are subject to LOD. PMID:20386105
Energy Technology Data Exchange (ETDEWEB)
Campbell, John L., E-mail: icampbel@uoguelph.ca; Heirwegh, Christopher M.; Ganly, Brianna
2016-09-15
Spectra from the laboratory and flight versions of the Curiosity rover’s alpha particle X-ray spectrometer were fitted with an in-house version of GUPIX, revealing departures from linear behavior of the energy-channel relationships in the low X-ray energy region where alpha particle PIXE is the dominant excitation mechanism. The apparent energy shifts for the lightest elements present were attributed in part to multiple ionization satellites and in part to issues within the detector and/or the pulse processing chain. No specific issue was identified, but the second of these options was considered to be the more probable. Approximate corrections were derived and then applied within the GUAPX code which is designed specifically for quantitative evaluation of APXS spectra. The quality of fit was significantly improved. The peak areas of the light elements Na, Mg, Al and Si were changed by only a few percent in most spectra. The changes for elements with higher atomic number were generally smaller, with a few exceptions. Overall, the percentage peak area changes are much smaller than the overall uncertainties in derived concentrations, which are largely attributable to the effects of rock heterogeneity. The magnitude of the satellite contributions suggests the need to incorporate these routinely in accelerator-based PIXE using helium beams.
Baird, Jim; Curry, Robin; Reid, Tim
2013-03-01
This article describes the development and application of a multiple linear regression model to identify how the key elements of waste and recycling infrastructure, namely container capacity and frequency of collection, affect the yield from municipal kerbside recycling programmes. The overall aim of the research was to gain an understanding of the factors affecting the yield from municipal kerbside recycling programmes in Scotland with an underlying objective to evaluate the efficacy of the model as a decision-support tool for informing the design of kerbside recycling programmes. The study isolates the principal kerbside collection service offered by all 32 councils across Scotland, eliminating those recycling programmes associated with flatted properties or multi-occupancies. The results of the regression analysis model have identified three principal factors which explain 80% of the variability in the average yield of the principal dry recyclate services: weekly residual waste capacity, number of materials collected and the weekly recycling capacity. The use of the model has been evaluated and recommendations made on ongoing methodological development and the use of the results in informing the design of kerbside recycling programmes. We hope that the research can provide insights for the further development of methods to optimise the design and operation of kerbside recycling programmes.
Yu, Jianwei; Liu, Juan; An, Wei; Wang, Yongjing; Zhang, Junzhi; Wei, Wei; Su, Ming; Yang, Min
2015-01-01
A total of 86 source water samples from 38 cities across major watersheds of China were collected for a bromide (Br(-)) survey, and the bromate (BrO3 (-)) formation potentials (BFPs) of 41 samples with Br(-) concentration >20 μg L(-1) were evaluated using a batch ozonation reactor. Statistical analyses indicated that higher alkalinity, hardness, and pH of water samples could lead to higher BFPs, with alkalinity as the most important factor. Based on the survey data, a multiple linear regression (MLR) model including three parameters (alkalinity, ozone dose, and total organic carbon (TOC)) was established with a relatively good prediction performance (model selection criterion = 2.01, R (2) = 0.724), using logarithmic transformation of the variables. Furthermore, a contour plot was used to interpret the influence of alkalinity and TOC on BrO3 (-) formation with prediction accuracy as high as 71 %, suggesting that these two parameters, apart from ozone dosage, were the most important ones affecting the BFPs of source waters with Br(-) concentration >20 μg L(-1). The model could be a useful tool for the prediction of the BFPs of source water.
Qin, Zijian; Wang, Maolin; Yan, Aixia
2017-07-01
In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a multiple linear regression (MLR) and a support vector machine (SVM) method. 512 HCV NS3/4A protease inhibitors and their IC 50 values which were determined by the same FRET assay were collected from the reported literature to build a dataset. All the inhibitors were represented with selected nine global and 12 2D property-weighted autocorrelation descriptors calculated from the program CORINA Symphony. The dataset was divided into a training set and a test set by a random and a Kohonen's self-organizing map (SOM) method. The correlation coefficients (r 2 ) of training sets and test sets were 0.75 and 0.72 for the best MLR model, 0.87 and 0.85 for the best SVM model, respectively. In addition, a series of sub-dataset models were also developed. The performances of all the best sub-dataset models were better than those of the whole dataset models. We believe that the combination of the best sub- and whole dataset SVM models can be used as reliable lead designing tools for new NS3/4A protease inhibitors scaffolds in a drug discovery pipeline. Copyright © 2017 Elsevier Ltd. All rights reserved.
Tugcu, Gulcin; Yilmaz, H Birkan; Saçan, Melek Türker
2014-10-01
This study presents quantitative structure-toxicity relationship (QSTR) models on the toxicity of 91 organic compounds to Chlorella vulgaris using multiple linear regression (MLR) and Kriging techniques. The molecular descriptors were calculated using SPARTAN and DRAGON programs, and descriptor selection was made by "all subset" method available in the QSARINS software. MLR and Kriging models developed with the same descriptors were compared. In addition to these models, Kriging method was used for descriptor selection, and model development. The selected descriptors showed the importance of hydrophobicity, molecular weight and atomic ionization state in describing the toxicity of a diverse set of chemicals to C. vulgaris. A QSTR model should be associated with appropriate measures of goodness-of-fit, robustness, and predictivity in order to be used for regulatory purpose. Therefore, while the internal performances (goodness-of-fit and robustness) of the models were determined by using a training set, the predictive abilities of the models were determined by using a test set. The results of the study showed that while MLR method is easier to apply, the Kriging method was more successful in predicting toxicity.
Saalwächter, Kay; Ziegler, Pascal; Spyckerelle, Olivier; Haidar, Bassel; Vidal, Alain; Sommer, Jens-Uwe
2003-08-01
We present proton-proton multiple-quantum investigations on a series of monomodal and strongly bimodal end-linked poly(dimethylsiloxane) model networks. A robust pulse sequence characterized by a well-defined double-quantum Hamiltonian along with a specific normalization approach is used to obtain double-quantum build-up curves. These curves are analyzed in terms of the spin dynamics of a local subsystem of monomer-fixed spins, where analytical fitting functions yielding residual dipole-dipole coupling constants are derived on the basis of exact solutions provided by simulations. Further employing the novel experimental strategy of double-quantum preselection of elastically active network chains, it is shown that the network response is purely heterogeneous, and that the data can be analyzed in terms of distributions of local dynamic order parameters using different models. The results yield consistent proof that local chain order in bimodal networks obeys a linear mixing law of short- and long-chain components. The order parameter distribution in a long-chain monomodal network is found to be surprisingly narrow, with a rather high average order parameter. Implications on the validity of present theories used to explain order and dynamics in networks are discussed.
Khanfar, Mohammad A; Taha, Mutasem O
2013-10-28
The mammalian target of rapamycin (mTOR) has an important role in cell growth, proliferation, and survival. mTOR is frequently hyperactivated in cancer, and therefore, it is a clinically validated target for cancer therapy. In this study, we combined exhaustive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent mTOR inhibitors employing 210 known mTOR ligands. Genetic function algorithm (GFA) coupled with k nearest neighbor (kNN) and multiple linear regression (MLR) analyses were employed to build self-consistent and predictive QSAR models based on optimal combinations of pharmacophores and physicochemical descriptors. Successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve (ROC) profiles. Optimal QSAR models and their associated pharmacophore hypotheses were validated by identification and experimental evaluation of several new promising mTOR inhibitory leads retrieved from the National Cancer Institute (NCI) structural database. The most potent hit illustrated an IC50 value of 48 nM.
Srivastava, Vikas; Sinha, Deepa; Tiwari, Anjani K; Sharma, Himanshu; Bala Sharma, Raj; Singh, Vinay K; Mishra, Anil K
2010-10-01
Computational chemistry is playing an increasingly important role in drug design and discovery, structural biology, and quantitative structure-activity relationship studies. A series of 4(3H)-quinozolone derivatives were screened for two-dimensional quantitative structure-activity relationship studies and subsequently their absorption, distribution, metabolism, and excretion (ADME) properties with the use of soft modeling techniques after selecting suitable descriptors for molecular structure. Multiple linear regression analysis was performed for this study. The final quantitative structure-property relationship mathematical models were found as follows: Equation [Y= log (1MIC)] [symbol: see the text] pMIC= 1. 0:2165κ(1) - 2.082χ(3) - 0.3235μT - 0.2185μx - 100.6qN - 35.42. 2. 0:2185κ(1) - 2.1575χ(3) - 0.3622μT - 0.2142μx - 100.4qN - 31.25. 3. 0:0015ω - 2.0822χ(3) - 0.1252μT - 0.2180μx - 112.9qN - 36.05. 4. 2:108χ(3) - 0.0035ET - 0.2033μx - 3.489qesp - 92.60qN - 33.20. 5. 0:2140κ(1) - 2.186χ(3) - 0.0036Oxxx - 0.0016Oxyy - 78.02qN - 31.52.
Sofowote, Uwayemi; Su, Yushan; Bitzos, Melynda M; Munoz, Anthony
2014-01-01
Tapered element oscillating microbalances equipped with sample equilibration system (TEOM-SES) used by the province of Ontario for the ambient monitoring of PM2.5 (particulate matter with an aerodynamic diameter multiple linear regression analyses (MLRAs) of particulate matter data from both instrumental monitors, with the inclusion of operational parameters of physicochemical relevance for both cases of transformations of historical TEOM and TEOM measurements to be made in the future. For historical TEOM data, it was observed that the transformations only benefited winter and fall months. Furthermore, comparisons of the transformed historical TEOM data with PM2.5 concentrations determined from the Federal Reference Method (FRM) sampler at seven locations within the province showed marked improvements over the observed TEOM-FRM comparisons. This work provides a path to correcting the historically observed underreporting of particulate mass in winter and fall in Ontario by making the TEOM-based continuous data resemble the new FEM outputs (in this case, more SHARP-like). It is possible that the transformation of mainly winter TEOM data as detailed in this work may potentially lead to revisions in historical annual composite mean PM2.5 concentrations and total annual number of days PM2.5 exceeded the Canada-wide Standard (CWS) metric across the province.
Liping, Wang; Binghui, Zheng
2013-01-01
After the impoundment of the Three Gorges Reservoir (TGR) since 2003, eutrophication has occurred and has become severe in Daning River. To predict chlorophyll-a (Chl-a) levels, the relationships between Chl-a and 11/13 routine monitoring data on water quality and hydrodynamics in Daning River were studied by principal component scores in the multiple linear regression model (principal component regression (PCR) model). In order to determine the hydrodynamic effect on simulated accuracy, two 0-day ahead prediction models were established: model A without hydrodynamic factors as variables, and model B with hydrodynamic factors (surface water velocity and water residence time) as variables. Based on the results of correlation analysis, score 1 and 2 with significant loads of phosphorus and nitrogen nutrients were omitted in developing model A (R(2) = 0.355); while score 2 with significant loads of nitrogen was omitted in developing model B (R(2) = 0.777). The results of validation using a new dataset showed that model B achieved a better fitted relationship between the predicted and observed values of Chl-a. It indicated hydrodynamics play an important role in limiting algal growth. The results suggested that a PCR model incorporating hydrodynamics processes has been suitable for the Chl-a concentration simulation and algal blooming prediction in Daning River of TGR.
Ne'eman, Yuval; Šijački, Djordje
1979-01-01
We review two possible affine extensions of gravity connected to the strong interactions. In the metric affine theory, torsion and nonmetricity do not propagate, gravitation is effectively unmodified, and the observed approximate conservation of hadron intrinsic hypermomentum—i.e., scaling, SU(6), and Regge trajectories—is due to the ḠL̄(4,R) band-spinor structure of the hadrons. In the second approach, the new gravitational Lagrangian density generates propagating but confined torsion and nonmetricity, presumably the main contributions to quark confinement. Leptons are represented nonlinearly as Poincaré spinors with the metric field as “realizer” and Higgs boson, and are unconfined. We present a construction for all linear multiplicity-free (= bandor) representations of ḠL̄(4,R) and in particular the [Formula: see text] fitting the hadron manifield. We also construct the Hilbert space hadron states [irreps (irreducible representations) of ḠĀ(4,R)] and the nonlinear realizations of ḠL̄(4,R) for lepton fields. PMID:16592616
Sharma, B K; Pilania, P; Singh, P; Prabhakar, Y S
2010-01-01
The caspase-3 inhibition activity of isoquinoline-1,3,4-trione derivatives has been analysed with the topological and molecular features from Dragon software. Analysis of the structural features in conjunction with the biological endpoints in combinatorial protocol in multiple linear regression (CP-MLR) led to the identification of 45 descriptors for modelling the activity. The study clearly suggested the role of rotatable bonds, mean information on the distance degree equality, radial centricity, bond and structural information content of five-order neighbourhood symmetry, atomic van der Waals volumes and the presence or absence of certain structural fragments to optimise the caspase-3 inhibitory activity of titled compounds. The models developed and the participating descriptors advocate that the substituent groups of the isoquinoline moiety hold scope for further modification in the optimization of the caspase-3 inhibitory activity. Analysis of these descriptors in partial least squares (PLS) highlighted their relative significance in modulating the biological response. The selected descriptors are enriched with information corresponding to the activity when compared to the remaining ones.
Mizoguchi, H; Wilson, A; Jerdack, G R; Hull, J D; Goodale, M; Grender, J M; Tyler, B A
2007-04-01
The aim of this study was to evaluate the efficacy of a single night-time dose of a syrup containing paracetamol, dextromethorphan hydrobromide, doxylamine succinate and ephedrine sulfate in subjects with multiple cold symptoms. A syrup containing 15 mg dextromethorphan hydrobromide, 7.5 mg doxylamine succinate, 600 mg paracetamol and 8 mg ephedrine sulfate (Wick MediNait produced by WICK Pharma, Germany, a subsidiary of Procter & Gamble GmbH; test syrup) or placebo (placebo syrup) for oral administration. This was a randomized, double-blind, placebo-controlled, multi-center, parallel design study. At enrollment, eligible subjects had to have at least moderate nasal congestion and a runny nose, at least mild cough and at least mild pain with one or more of the following: sore throat, sore chest, headache or body pain/aches. Subjects were randomized into either Group T (test syrup) or Group P (placebo syrup). On the evening of enrollment, subjects rated baseline symptoms, ingested the assigned study product and completed symptom-relief assessments at 3 hours post-dosing. Within one hour of awakening the following morning, subjects completed night-time symptom relief and sleep satisfaction assessments. All symptoms were recorded using an Interactive Voice Response system. Treatment comparisons were made after adjusting for the severity of baseline symptom using analysis of covariance. Of 485 subjects who took the study product, 432 (224 in Group T; 208 in Group P) were evaluable for analysis. For the primary endpoint (composite of nasal congestion/runny nose/cough/pain relief scores 3 hours post-dosing), subjects in Group T had clinically and statistically significantly greater relief than Group P (p = 0.0002). Each individual symptom score also showed statistically significant improvement at this time point (p sleep (p = 0.002) compared to placebo syrup. Improvement in individual symptoms after 3 hours was obtained in 16-42% more subjects in Group T than in Group P
Directory of Open Access Journals (Sweden)
Melissa A Batson
Full Text Available The recent increase in the use of high field MR systems is accompanied by a demand for acquisition techniques and coil systems that can take advantage of increased power and accuracy without being susceptible to increased noise. Physical location and anatomical complexity of targeted regions must be considered when attempting to image deeper structures with small nuclei and/or complex cytoarchitechtonics (i.e. small microvasculature and deep nuclei, such as the brainstem and the cerebellum (Cb. Once these obstacles are overcome, the concomitant increase in signal strength at higher field strength should allow for faster acquisition of MR images. Here we show that it is technically feasible to quickly and accurately detect blood oxygen level dependent (BOLD signal changes and obtain anatomical images of Cb at high spatial resolutions in individual subjects at 7 Tesla in a single one-hour session. Images were obtained using two high-density multi-element surface coils (32 channels in total placed beneath the head at the level of Cb, two channel transmission, and three-dimensional sensitivity encoded (3D, SENSE acquisitions to investigate sensorimotor activations in Cb. Two classic sensorimotor tasks were used to detect Cb activations. BOLD signal changes during motor activity resulted in concentrated clusters of activity within the Cb lobules associated with each task, observed consistently and independently in each subject: Oculomotor vermis (VI/VII and CrusI/II for pro- and anti-saccades; ipsilateral hemispheres IV-VI for finger tapping; and topographical separation of eye- and hand- activations in hemispheres VI and VIIb/VIII. Though fast temporal resolution was not attempted here, these functional patches of highly specific BOLD signal changes may reflect small-scale shunting of blood in the microvasculature of Cb. The observed improvements in acquisition time and signal detection are ideal for individualized investigations such as
Directory of Open Access Journals (Sweden)
Vinson JA
2012-01-01
Full Text Available Joe A Vinson1, Bryan R Burnham3, Mysore V Nagendran31Chemistry Department, 2Psychology Department, University of Scranton, Scranton, PA, USA; 3Health Sciences Clinic, Bangalore, IndiaBackground: Adult weight gain and obesity have become worldwide problems. Issues of cost and potential side effects of prescription weight loss drugs have led overweight and obese adults to try nutraceuticals that may aid weight loss. One promising nutraceutical is green coffee extract, which contains high concentrations of chlorogenic acids hat are known to have health benefits and to influence glucose and fat metabolism. A 22-week crossover study was conducted to examine the efficacy and safety of a commercial green coffee extract product GCA™ at reducing weight and body mass in 16 overweight adults.Methods: Subjects received high-dose GCA (1050 mg, low-dose GCA (700 mg, or placebo in separate six-week treatment periods followed by two-week washout periods to reduce any influence of preceding treatment. Treatments were counterbalanced between subjects. Primary measurements were body weight, body mass index, and percent body fat. Heart rate and blood pressure were also measured.Results: Significant reductions were observed in body weight (-8.04 ± 2.31 kg, body mass index (-2.92 ± 0.85 kg/m2, and percent body fat (-4.44% ± 2.00%, as well as a small decrease in heart rate (-2.56 ± 2.85 beats per minute, but with no significant changes to diet over the course of the study. Importantly, the decreases occurred when subjects were taking GCA. Body mass index for six subjects shifted from preobesity to the normal weight range (<25.00 kg/m2.Conclusion: The results are consistent with human and animal studies and a meta-analysis of the efficacy of green coffee extract in weight loss. The results suggest that GCA may be an effective nutraceutical in reducing weight in preobese adults, and may be an inexpensive means of preventing obesity in overweight adults
Ramos Batalha, Priscila; Borghi-Silva, Audrey; Campos Freire, Renato; Zanela DA Silva Arêas, Fernando; Peixoto Tinoco Arêas, Guilherme
2016-11-01
Elastic bands are therapeutic tools widely used in rehabilitation. However, knowledge regarding autonomic cardiovascular overload during this type of resistance exercise is limited. This study assessed the autonomic control of heart rate during an incremental exercise protocol with elastic bands in sedentary healthy young individuals. Ten young women were subjected to an exercise protocol involving bilateral shoulder flexion to 90° with various thicknesses of elastic bands; the exercise was performed for 36 uninterrupted repetitions with a 15-minute rest interval between sets. During the exercise, the RR intervals (R-Ri) were collected and determined, the heart rate variability was analyzed. All subjects completed the exercise protocol. Heart rate increased, and RR intervals decreased from the yellow elastic band onward. However, the square root of the sum of the square of the difference of RR intervals divided by the number of RR interval, standard deviation of the arithmetic mean of all normal RR intervals, and standard deviation of the RR interval instantaneous intervals of type I decreased significantly when performed with the green band onward (Pheart rate. However, the green elastic band induces less total and parasympathetic modulation heart rate variability.
Directory of Open Access Journals (Sweden)
Deepali eMathur
2015-09-01
Full Text Available Gene expression studies employing real-time PCR has become an intrinsic part of biomedical research. Appropriate normalization of target gene transcript(s based on stably expressed housekeeping genes is crucial in individual experimental conditions to obtain accurate results. In multiple sclerosis (MS, several gene expression studies have been undertaken, however, the suitability of housekeeping genes to express stably in this disease is not yet explored. Recent research suggests that their expression level may vary under different experimental conditions. Hence it is indispensible to evaluate their expression stability to accurately normalize target gene transcripts. The present study aims to evaluate the expression stability of seven housekeeping genes in rat granule neurons treated with cerebrospinal fluid of MS patients. The selected reference genes were quantified by real time PCR and their expression stability was assessed using GeNorm and NormFinder algorithms. Both methods reported transferrin receptor (Tfrc and microglobulin beta-2 (B2m the most stable genes whereas beta-actin (ActB and glyceraldehyde-3-phosphate-dehydrogenase (Gapdh the most fluctuated ones. Altogether our data demonstrate the significance of pre-validation of housekeeping genes for accurate normalization and indicates Tfrc and B2m as best endogenous controls in MS. ActB and Gapdh are not recommended in gene expression studies related to the current one.
DEFF Research Database (Denmark)
Darula, Radoslav; Sorokin, Sergey
2013-01-01
. To study the non-linear behaviour of the coupled problem analytically, the classical multiple scale method is applied. The response at each mode in resonant as well as in sub-harmonic excitation conditions is analysed in the cases of internal resonance and internal parametric resonance....... electrical circuit is described by a differential equation of the 1st order, which is considered to contribute to the coupled system by 0.5 DOF. The electrical and mechanical systems are coupled via a magnetic circuit, which is inherently non-linear, due to a non-linear nature of the electro-magnetic force...
Gasperini, Claudio; Hupperts, Raymond; Lycke, Jan; Short, Christine; McNeill, Manjit; Zhong, John; Mehta, Lahar R
2016-11-15
Prolonged-release (PR) fampridine is approved to treat walking impairment in persons with multiple sclerosis (MS); however, treatment benefits may extend beyond walking. MOBILE was a phase 2, 24-week, double-blind, placebo-controlled exploratory study to assess the impact of 10mg PR-fampridine twice daily versus placebo on several subject-assessed measures. This analysis evaluated the physical and psychological health outcomes of subjects with progressing or relapsing MS from individual items of the Multiple Sclerosis Impact Scale (MSIS-29). PR-fampridine treatment (n=68) resulted in greater improvements from baseline in the MSIS-29 physical (PHYS) and psychological (PSYCH) impact subscales, with differences of 89% and 148% in mean score reduction from baseline (n=64) at week 24 versus placebo, respectively. MSIS-29 item analysis showed that a higher percentage of PR-fampridine subjects had mean improvements in 16/20 PHYS and 6/9 PSYCH items versus placebo after 24weeks. Post hoc analysis of the 12-item Multiple Sclerosis Walking Scale (MSWS-12) improver population (≥8-point mean improvement) demonstrated differences in mean reductions from baseline of 97% and 111% in PR-fampridine MSIS-29 PHYS and PSYCH subscales versus the overall placebo group over 24weeks. A higher percentage of MSWS-12 improvers treated with PR-fampridine showed mean improvements in 20/20 PHYS and 8/9 PSYCH items versus placebo at 24weeks. In conclusion, PR-fampridine resulted in physical and psychological benefits versus placebo, sustained over 24weeks. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael
2017-01-01
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness
Zivadinov, R; Hagemeier, J; Bergsland, N; Tavazzi, E; Weinstock-Guttman, B
2018-03-01
Dimethyl fumarate (DMF) is an oral treatment for relapsing-remitting multiple sclerosis (MS) with anti-inflammatory and possible neuroprotective properties. Its effect on white matter and gray matter pathology is still not fully understood. The aim of the study was to characterize the effect of DMF on normal-appearing white matter (NAWM) and thalamic pathology longitudinally. In this observational, longitudinal, 24-month magnetic resonance imaging study, 75 patients with relapsing-remitting MS treated with DMF and 40 age- and sex-matched healthy individuals were enrolled. Regional diffusion tensor imaging metrics and tract-based spatial statistics analyses were used to assess differences between groups. Mean diffusivity, axial diffusivity, radial diffusivity and fractional anisotropy were measured in the thalamus and NAWM. Baseline differences and changes over time were evaluated within and between study groups. At baseline, patients with MS showed significantly increased diffusivity and decreased fractional anisotropy in the thalamus (P < 0.001 for mean diffusivity, axial diffusivity and radial diffusivity) and NAWM (all P < 0.016) compared with healthy individuals. No significant within-group difference was found in diffusion tensor imaging measures over 24 months in either group. Healthy individuals showed a significantly greater rate of increased diffusivity parameters in the thalamus and NAWM compared with patients with MS, over 24 months (P < 0.05). The lack of changes in diffusion tensor imaging metrics in patients with MS over 24 months possibly indicates a neuroprotective role of DMF. These findings provide additional evidence of the beneficial effect of DMF on MS-related pathology. © 2018 EAN.
Directory of Open Access Journals (Sweden)
E. Fallahi
2016-10-01
Full Text Available Introduction: Determining a suitable cropping pattern is an important task for planners and requires an exact and realistic decision-making process based on several goals and criteria corresponding to secure the interest of agricultural beneficiaries in long-term. Accordingly, this study reviews the current pattern operated by farmers in Sari, Iran, and intends to provide a cropping pattern that considers the multifold regional and agricultural sustainability criteria along with economic considerations. Materials and Methods: In order to achieve the study goals, a consolidated model of AHP and Linear Programming was applied. For this purpose, we constructed a three-level AHP, including a goal (determining the weight of each crop, seven criteria, and seven alternatives. Profitability, compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop were considered as the criteria in the model. Seven alternative crops including rice, wheat, rapeseed, barley, soybean, clover, and vegetables were considered too. The next step is determining the weight of each criterion with regard to the goal and the weight of each alternative with regard to each criteria. By multiplying these weights, final weights for various crops were obtained from the model. Derived weights for each crop were then applied as objective function coefficients in the Linear Programming model and the model was solved subject to the constraints. Results and Discussion: Optimal cropping pattern determined based on the consolidated model of AHP and Linear Programming and the results compared to a scenario that only looks forward to maximizing the economic interests. Due to the low profitability of rapeseed and barley, these crops eliminated from the pattern in the profit-maximizing scenario. According to the results, the
Caravaggi, Paolo; Leardini, Alberto; Giacomozzi, Claudia
2016-10-03
Plantar load can be considered as a measure of the foot ability to transmit forces at the foot/ground, or foot/footwear interface during ambulatory activities via the lower limb kinematic chain. While morphological and functional measures have been shown to be correlated with plantar load, no exhaustive data are currently available on the possible relationships between range of motion of foot joints and plantar load regional parameters. Joints' kinematics from a validated multi-segmental foot model were recorded together with plantar pressure parameters in 21 normal-arched healthy subjects during three barefoot walking trials. Plantar pressure maps were divided into six anatomically-based regions of interest associated to corresponding foot segments. A stepwise multiple regression analysis was performed to determine the relationships between pressure-based parameters, joints range of motion and normalized walking speed (speed/subject height). Sagittal- and frontal-plane joint motion were those most correlated to plantar load. Foot joints' range of motion and normalized walking speed explained between 6% and 43% of the model variance (adjusted R 2 ) for pressure-based parameters. In general, those joints' presenting lower mobility during stance were associated to lower vertical force at forefoot and to larger mean and peak pressure at hindfoot and forefoot. Normalized walking speed was always positively correlated to mean and peak pressure at hindfoot and forefoot. While a large variance in plantar pressure data is still not accounted for by the present models, this study provides statistical corroboration of the close relationship between joint mobility and plantar pressure during stance in the normal healthy foot. Copyright © 2016 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Peter Nynäs
2011-01-01
Full Text Available Body modification practices have lately gained growing visibility in contemporary Western cultures. It is more like a trend or fashion ranging from, on the on hand, decorative tattoos and piercing, to branding, implants and surgery on the other. In most forms body modification occurs without any obvious religious, spiritual or ideological marks attached, but some forms involve discourses that explicitly address such aspirations. However, despite the fluidity and diversity of practices, it can be claimed that body modification represents specific or distinct ways of working with the body that differ from other forms of contemporary Western body cultures. Further, it needs be considered as part of the broader body culture. Hence it draws our attention to the role of corporeality in contemporary Western culture. Body modification could be regarded as a reaction to the nature of contemporary society, a way of compensating the lack of corporeal engagement in the world. Its former association with different subcultures might underpin this oppositional position. On the other hand, some scholars regard body-modification as nothing but part of the contemporary free floating carnival of signs, as mere mainstream supermarket signifiers, emptied of meaning and deprived of any external references. In this article emphasis is put on forms of body modification that more explicitly connote religion. One example of body modification is explored from an empirical perspective: the story about the spirituality of the gay porn star Logan McCree. This is a personal narrative about spirituality in which tattooing plays a central role. Still, despite being personal it is also part of McCree’s public image. With the help of both literature and the examples on body modification the place of corporeality in the story of McCree is explored. The aim is to shed some light on corporeality and in particular in relation to subjectivity.
Directory of Open Access Journals (Sweden)
Dominique Hansen
2014-01-01
Full Text Available Background and Purpose. Walking capacity is reduced in subjects with multiple sclerosis (MS. To develop effective exercise interventions to enhance walking capacity, it is important to determine the impact of factors, modifiable by exercise intervention (maximal muscle strength versus muscle oxidative capacity, on walking capacity. The purpose of this pilot study is to discriminate between the impact of maximal muscle strength versus muscle oxidative capacity on walking capacity in subjects with MS. Methods. From 24 patients with MS, muscle oxidative capacity was determined by calculation of exercise-onset oxygen uptake kinetics (mean response time during submaximal exercise bouts. Maximal muscle strength (isometric knee extension and flexion peak torque was assessed on dynamometer. All subjects completed a 6-minute walking test. Relationships between walking capacity (as a percentage of normal value and muscle strength (of knee flexors and extensors versus muscle oxidative capacity were assessed in multivariate regression analyses. Results. The expanded disability status score (EDSS showed a significant univariate correlation (r=-0.70, P<0.004 with walking capacity. In multivariate regression analyses, EDSS and mean response time, but not muscle strength, were independently related to walking capacity (P<0.05. Conclusions. Walking distance is, next to disability level and not taking neurologic symptoms/deficits into account, primarily related to muscle oxidative capacity in subjects with MS. Additional study is needed to further examine/verify these findings.
Ibanez, C. A. G.; Carcellar, B. G., III; Paringit, E. C.; Argamosa, R. J. L.; Faelga, R. A. G.; Posilero, M. A. V.; Zaragosa, G. P.; Dimayacyac, N. A.
2016-06-01
Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike's Information Criterion) and BIC (Bayesian Information Criterion) was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO) Coefficient and the Barlett's Test for Spherecity (BTS).
Directory of Open Access Journals (Sweden)
C. A. G. Ibanez
2016-06-01
Full Text Available Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike’s Information Criterion and BIC (Bayesian Information Criterion was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO Coefficient and the Barlett’s Test for Spherecity (BTS.
Hu, L; Liang, M; Mouraux, A; Wise, R G; Hu, Y; Iannetti, G D
2011-12-01
Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1) wavelet filtering (WF) to enhance the SNR of ERPs and 2) a multiple linear regression with a dispersion term (MLR(d)) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLR(d) method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLR(d) approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLR(d) effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLR(d) can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli.
Iserbyt, Peter; Schouppe, Gilles; Charlier, Nathalie
2015-04-01
Research investigating lifeguards' performance of Basic Life Support (BLS) with Automated External Defibrillator (AED) is limited. Assessing simulated BLS/AED performance in Flemish lifeguards and identifying factors affecting this performance. Six hundred and sixteen (217 female and 399 male) certified Flemish lifeguards (aged 16-71 years) performed BLS with an AED on a Laerdal ResusciAnne manikin simulating an adult victim of drowning. Stepwise multiple linear regression analysis was conducted with BLS/AED performance as outcome variable and demographic data as explanatory variables. Mean BLS/AED performance for all lifeguards was 66.5%. Compression rate and depth adhered closely to ERC 2010 guidelines. Ventilation volume and flow rate exceeded the guidelines. A significant regression model, F(6, 415)=25.61, p<.001, ES=.38, explained 27% of the variance in BLS performance (R2=.27). Significant predictors were age (beta=-.31, p<.001), years of certification (beta=-.41, p<.001), time on duty per year (beta=-.25, p<.001), practising BLS skills (beta=.11, p=.011), and being a professional lifeguard (beta=-.13, p=.029). 71% of lifeguards reported not practising BLS/AED. Being young, recently certified, few days of employment per year, practising BLS skills and not being a professional lifeguard are factors associated with higher BLS/AED performance. Measures should be taken to prevent BLS/AED performances from decaying with age and longer certification. Refresher courses could include a formal skills test and lifeguards should be encouraged to practise their BLS/AED skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi
2017-11-01
In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hu, L.; Liang, M.; Mouraux, A.; Wise, R. G.; Hu, Y.
2011-01-01
Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1) wavelet filtering (WF) to enhance the SNR of ERPs and 2) a multiple linear regression with a dispersion term (MLRd) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLRd method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLRd approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLRd effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLRd can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli. PMID:21880936
Directory of Open Access Journals (Sweden)
Ardeshir Khazaei
2017-09-01
Full Text Available The quantitative structure–activity relationship (QSAR analyses were carried out in a series of novel sulfonamide derivatives as the procollagen C-proteinase inhibitors for treatment of fibrotic conditions. Sphere exclusion method was used to classify data set into categories of train and test set at different radii ranging from 0.9 to 0.5. Multiple linear regression (MLR, principal component regression (PCR and partial least squares (PLS were used as the regression methods and stepwise, Genetic algorithm (GA, and simulated annealing (SA were used as the feature selection methods. Three of the statistically best significant models were chosen from the results for discussion. Model 1 was obtained by MLR–SA methodology at a radius of 1.6. This model with a coefficient of determination (r2 = 0.71 can well predict the real inhibitor activities. Cross-validated q2 of this model, 0.64, indicates good internal predictive power of the model. External validation of the model (pred_r2 = 0.85 showed that the model can well predict activity of novel PCP inhibitors. The model 2 which developed using PLS–SW explains 72% (r2 = 0.72 of the total variance in the training set as well as it has internal (q2 and external (pred_r2 predictive ability of ∼67% and ∼71% respectively. The last developed model by PCR–SA has a correlation coefficient (r2 of 0.68 which can explains 68% of the variance in the observed activity values. In this case internal and external validations are 0.61 and 0.75, respectively. Alignment Independent (AI and atomic valence connectivity index (chiv have the greatest effect on the biological activities. Developed models can be useful in designing and synthesis of effective and optimized novel PCP inhibitors which can be used for treatment of fibrotic conditions.
Directory of Open Access Journals (Sweden)
Ольга Валентиновна Шохова
2013-11-01
Full Text Available The article is devoted to the problem of emotional response in children with developmental disorders in subject-communicative activity . The characteristic of the particularities of emotional reaction in children with divelopmental disorders is given. The author proves that it is necessary to develop emotional response as the base for further social adaptation of children with multiple disorders in development; mechanisms of formation of emotional reaction in communicative activity are described: contents, methods used for multiple diorders. Experimental data has proved the effectiveness of pedagogical thechnology on forming of emotional reaction in subject-communicative activity. Corrective and development work used in this technology is based on principles of integrity, complexness; the interralated series of thematical studies is organized intended for develoment of motor, sensor, communicative and emotional sphere in different activities of children. All this facilitate gradual interiorization of emotional reactions, their automatization in communicative activity.DOI: http://dx.doi.org/10.12731/2218-7405-2013-10-7
Directory of Open Access Journals (Sweden)
Serena eScarpelli
2015-07-01
Full Text Available We examined the question whether the role of EEG oscillations in predicting presence/absence of dream recall (DR is explained by state- or trait-like factors. Six healthy subjects were awakened from REM sleep in a within-subjects design with multiple naps, until a recall (REC and a non-recall (NREC condition were obtained. Naps were scheduled in the early afternoon and were separated by one week. Topographical EEG data of the 5-min of REM sleep preceding each awakening were analyzed by power spectral analysis [Fast Fourier Transform (FFT] and by a method to detect oscillatory activity [Better OSCillations (BOSC].Both analyses show that REC is associated to higher frontal theta activity (5-7 Hz and theta oscillations (6.06 Hz compared to NREC condition, but only the second comparison reached significance. Our pilot study provides support to the notion that sleep and wakefulness share similar EEG correlates of encoding in episodic memories, and supports the state-like hypothesis: dream recall may depend on the physiological state related to the sleep stage from which the subject is awakened rather than on a stable individual EEG pattern.
Scarpelli, Serena; Marzano, Cristina; D'Atri, Aurora; Gorgoni, Maurizio; Ferrara, Michele; De Gennaro, Luigi
2015-01-01
We examined the question whether the role of EEG oscillations in predicting presence/absence of dream recall (DR) is explained by "state-" or "trait-like" factors. Six healthy subjects were awakened from REM sleep in a within-subjects design with multiple naps, until a recall and a non-recall condition were obtained. Naps were scheduled in the early afternoon and were separated by 1 week. Topographical EEG data of the 5-min of REM sleep preceding each awakening were analyzed by power spectral analysis [Fast Fourier Transform (FFT)] and by a method to detect oscillatory activity [Better OSCillations (BOSC)]. Both analyses show that REC is associated to higher frontal theta activity (5-7 Hz) and theta oscillations (6.06 Hz) compared to NREC condition, but only the second comparison reached significance. Our pilot study provides support to the notion that sleep and wakefulness share similar EEG correlates of encoding in episodic memories, and supports the "state-like hypothesis": DR may depend on the physiological state related to the sleep stage from which the subject is awakened rather than on a stable individual EEG pattern.
Computational linear and commutative algebra
Kreuzer, Martin
2016-01-01
This book combines, in a novel and general way, an extensive development of the theory of families of commuting matrices with applications to zero-dimensional commutative rings, primary decompositions and polynomial system solving. It integrates the Linear Algebra of the Third Millennium, developed exclusively here, with classical algorithmic and algebraic techniques. Even the experienced reader will be pleasantly surprised to discover new and unexpected aspects in a variety of subjects including eigenvalues and eigenspaces of linear maps, joint eigenspaces of commuting families of endomorphisms, multiplication maps of zero-dimensional affine algebras, computation of primary decompositions and maximal ideals, and solution of polynomial systems. This book completes a trilogy initiated by the uncharacteristically witty books Computational Commutative Algebra 1 and 2 by the same authors. The material treated here is not available in book form, and much of it is not available at all. The authors continue to prese...
Matrices and linear transformations
Cullen, Charles G
1990-01-01
""Comprehensive . . . an excellent introduction to the subject."" - Electronic Engineer's Design Magazine.This introductory textbook, aimed at sophomore- and junior-level undergraduates in mathematics, engineering, and the physical sciences, offers a smooth, in-depth treatment of linear algebra and matrix theory. The major objects of study are matrices over an arbitrary field. Contents include Matrices and Linear Systems; Vector Spaces; Determinants; Linear Transformations; Similarity: Part I and Part II; Polynomials and Polynomial Matrices; Matrix Analysis; and Numerical Methods. The first
Brix, Kevin V; DeForest, David K; Tear, Lucinda; Grosell, Martin; Adams, William J
2017-05-02
Biotic Ligand Models (BLMs) for metals are widely applied in ecological risk assessments and in the development of regulatory water quality guidelines in Europe, and in 2007 the United States Environmental Protection Agency (USEPA) recommended BLM-based water quality criteria (WQC) for Cu in freshwater. However, to-date, few states have adopted BLM-based Cu criteria into their water quality standards on a state-wide basis, which appears to be due to the perception that the BLM is too complicated or requires too many input variables. Using the mechanistic BLM framework to first identify key water chemistry parameters that influence Cu bioavailability, namely dissolved organic carbon (DOC), pH, and hardness, we developed Cu criteria using the same basic methodology used by the USEPA to derive hardness-based criteria but with the addition of DOC and pH. As an initial proof of concept, we developed stepwise multiple linear regression (MLR) models for species that have been tested over wide ranges of DOC, pH, and hardness conditions. These models predicted acute Cu toxicity values that were within a factor of ±2 in 77% to 97% of tests (5 species had adequate data) and chronic Cu toxicity values that were within a factor of ±2 in 92% of tests (1 species had adequate data). This level of accuracy is comparable to the BLM. Following USEPA guidelines for WQC development, the species data were then combined to develop a linear model with pooled slopes for each independent parameter (i.e., DOC, pH, and hardness) and species-specific intercepts using Analysis of Covariance. The pooled MLR and BLM models predicted species-specific toxicity with similar precision; adjusted R 2 and R 2 values ranged from 0.56 to 0.86 and 0.66-0.85, respectively. Graphical exploration of relationships between predicted and observed toxicity, residuals and observed toxicity, and residuals and concentrations of key input parameters revealed many similarities and a few key distinctions between the
Directory of Open Access Journals (Sweden)
M.A. Mousavi Shalmani
2014-08-01
Full Text Available In order to assessment of water quality and characterize seasonal variation in 18O and 2H in relation with different chemical and physiographical parameters and modelling of effective parameters, an study was conducted during 2010 to 2011 in 30 different ponds in the north of Iran. Samples were collected at three different seasons and analysed for chemical and isotopic components. Data shows that highest amounts of δ18O and δ2H were recorded in the summer (-1.15‰ and -12.11‰ and the lowest amounts were seen in the winter (-7.50‰ and -47.32‰ respectively. Data also reveals that there is significant increase in d-excess during spring and summer in ponds 20, 21, 22, 24, 25 and 26. We can conclude that residual surface runoff (from upper lands is an important source of water to transfer soluble salts in to these ponds. In this respect, high retention time may be the main reason for movements of light isotopes in to the ponds. This has led d-excess of pond 12 even greater in summer than winter. This could be an acceptable reason for ponds 25 and 26 (Siyahkal county with highest amount of d-excess and lowest amounts of δ18O and δ2H. It seems light water pumped from groundwater wells with minor source of salt (originated from sea deep percolation in to the ponds, could may be another reason for significant decrease in the heavy isotopes of water (18O and 2H for ponds 2, 12, 14 and 25 from spring to summer. Overall conclusion of multiple linear regression test indicate that firstly from 30 variables (under investigation only a few cases can be used for identifying of changes in 18O and 2H by applications. Secondly, among the variables (studied, phytoplankton content was a common factor for interpretation of 18O and 2H during spring and summer, and also total period (during a year. Thirdly, the use of water in the spring was recommended for sampling, for 18O and 2H interpretation compared with other seasons. This is because of function can be
Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y
2008-02-18
The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.
Bifano, Marc; Adamczyk, Robert; Hwang, Carey; Kandoussi, Hamza; Marion, Alan; Bertz, Richard J
2015-05-01
Chronic hepatitis C virus (HCV) infection is a major cause of liver transplantation. Drug-drug interactions (DDIs) with cyclosporine and tacrolimus hindered the use of first-generation protease inhibitors in transplant recipients. The current study investigated DDIs between daclatasvir-a pan-genotypic HCV NS5A inhibitor with clinical efficacy in multiple regimens (including all-oral)-and cyclosporine or tacrolimus in healthy subjects. Healthy fasted subjects (aged 18-49 years; body mass index 18-32 kg/m(2)) received single oral doses of cyclosporine 400 mg on days 1 and 9, and daclatasvir 60 mg once daily on days 4-11 (group 1, n = 14), or a single oral dose of tacrolimus 5 mg on days 1 and 13, and daclatasvir 60 mg once daily on days 8-19 (group 2, n = 14). Blood samples for pharmacokinetic analysis [by liquid chromatography with tandem mass spectrometry (LC-MS/MS)] were collected on days 1 and 9 for cyclosporine (72 h), on days 1 and 13 for tacrolimus (168 h) and on days 8 and 9 (group 1) or on days 12 and 13 (group 2) for daclatasvir (24 h). Plasma concentrations were determined by validated LC-MS/MS methods. Daclatasvir did not affect the pharmacokinetic parameters of cyclosporine or tacrolimus, and tacrolimus did not affect the pharmacokinetic parameters of daclatasvir. Co-administration of cyclosporine resulted in a 40 % increase in the area under the concentration-time curve of daclatasvir but did not affect its maximum observed concentration. On the basis of these observations in healthy subjects, no clinically relevant DDIs between daclatasvir and cyclosporine or tacrolimus are anticipated in liver transplant recipients infected with HCV; dose adjustments during co-administration are unlikely to be required.
Maleki, Afshin; Daraei, Hiua; Alaei, Loghman; Faraji, Aram
2014-01-01
Four stepwise multiple linear regressions (SMLR) and a genetic algorithm (GA) based multiple linear regressions (MLR), together with artificial neural network (ANN) models, were applied for quantitative structure-activity relationship (QSAR) modeling of dissociation constants (Kd) of 62 arylsulfonamide (ArSA) derivatives as human carbonic anhydrase II (HCA II) inhibitors. The best subsets of molecular descriptors were selected by SMLR and GA-MLR methods. These selected variables were used to generate MLR and ANN models. The predictability power of models was examined by an external test set and cross validation. In addition, some tests were done to examine other aspects of the models. The results show that for certain purposes GA-MLR is better than SMLR and for others, ANN overcomes MLR models.
Engelen, MPKJ; De Castro, CLN; Rutten, EPA; Wouters, EFM; Schols, AMWJ; Deutz, NEP
2012-01-01
Background & Aims We previously observed in elderly subjects with Chronic Obstructive Pulmonary Disease (COPD) an enhanced anabolic response to milk protein sip feeding, associated with reduced splanchnic extraction (SPE) of phenylalanine. Milk proteins are known for their high Branched-chain Amino Acids (BCAA) content, but no information is present about splanchnic extraction and metabolism of the individual BCAA in COPD. Objective To investigate whether BCAA metabolism and SPE of the individual BCAA are altered in COPD during milk protein sip feeding. Design In elderly subjects with COPD and in healthy age-matched elderly SPE, endogenous rate of appearance (Raendo) of the leucine (LEU), isoleucine (ILE) and valine (VAL) were measured before and during sip feeding of a Whey protein meal. To study the effect of aging, the healthy elderly were compared to a group of healthy young subjects. Stable isotopes of L-[2H3]-LEU, L-[1-13C]-ILE and L-[1-13C]-VAL were given on two separate test days orally or intravenously. Simultaneously, L-[ring-2H5]-phenylalanine (PHE) and L-[ring-2H2]-tyrosine (TYR) were given to determine the whole body protein breakdown (WbPB), synthesis (WbPS) and NetPS. Results SPE of all BCAA, TYR, and PHE (p<0.01) were lower in the COPD group, and the increase in netPS during feeding was higher in the COPD group (P<0.01) due to higher values for PS (P<0.001). Raendo of all BCAA, PHE and TYR were higher in the COPD than the healthy elderly group (P<0.05) before and during feeding (P<0.001). Sip feeding resulted in a reduction of Raendo of PHE, ILE and VAL (P<0.05). Postabsorptive Raendo was not different for any of the measured amino acids between the healthy elderly and young group, while sip feeding resulted in a reduction of Raendo of PHE. Only SPE of TYR was higher in the elderly (P<0.05) and the increase in netPS during sip feeding was independent of aging. Conclusion The enhanced anabolic response to milk protein sip feeding in normal
Directory of Open Access Journals (Sweden)
Karunanayake Chandima P
2009-02-01
Full Text Available Abstract Background A positive family history of chronic diseases including cancer can be used as an index of genetic and shared environmental influences. The tumours studied have several putative risk factors in common including occupational exposure to certain pesticides and a positive family history of cancer. Methods We conducted population-based studies of Hodgkin lymphoma (HL, Multiple Myeloma (MM, non-Hodgkin's Lymphoma (NHL, and Soft Tissue Sarcoma (STS among male incident case and control subjects in six Canadian provinces. The postal questionnaire was used to collect personal demographic data, a medical history, a lifetime occupational history, smoking pattern, and the information on family history of cancer. The family history of cancer was restricted to first degree relatives and included relationship to the index subjects and the types of tumours diagnosed among relatives. The information was collected on 1528 cases (HL (n = 316, MM (n = 342, NHL (n = 513, STS (n = 357 and 1506 age ± 2 years and province of residence matched control subjects. Conditional logistic regression analyses adjusted for the matching variables were conducted. Results We found that most families were cancer free, and a minority included two or more affected relatives. HL [(ORadj (95% CI 1.79 (1.33, 2.42], MM (1.38(1.07, 1.78, NHL (1.43 (1.15, 1.77, and STS cases (1.30(1.00, 1.68 had higher incidence of cancer if any first degree relative was affected with cancer compared to control families. Constructing mutually exclusive categories combining "family history of cancer" (yes, no and "pesticide exposure ≥10 hours per year" (yes, no indicated that a positive family history was important for HL (2.25(1.61, 3.15, and for the combination of the two exposures increased risk for MM (1.69(1.14,2.51. Also, a positive family history of cancer both with (1.72 (1.21, 2.45 and without pesticide exposure (1.43(1.12, 1.83 increased risk of NHL. Conclusion HL, MM, NHL
Directory of Open Access Journals (Sweden)
Hideaki Komiyama
2016-07-01
Full Text Available Solution-processable star-shaped and linear π-conjugated oligomers consisting of an electron-donating tetrathienoanthracene (TTA core and electron-accepting diketopyrrolopyrrole (DPP arms, namely, TTA-DPP4 and TTA-DPP2, were designed and synthesized. Based on density functional theory calculations, the star-shaped TTA-DPP4 has a larger oscillator strength than the linear TTA-DPP2, and consequently, better photoabsorption property over a wide range of visible wavelengths. The photovoltaic properties of organic solar cells based on TTA-DPP4 and TTA-DPP2 with a fullerene derivative were evaluated by varying the thickness of the bulk heterojunction active layer. As a result of the enhanced visible absorption properties of the star-shaped π-conjugated structure, better photovoltaic performances were obtained with relatively thin active layers (40–60 nm.
Capistran, Julie; Martini, Rose
2016-10-01
Cognitive Orientation to daily Occupational Performance (CO-OP) approach has been shown to be effective for improving the performance of tasks worked on in therapy and the use of cognitive strategies. No study to date seems to have explored its effectiveness for improving performance of untrained tasks (inter-task transfer) in children with Developmental Coordination Disorder (DCD). This study aimed to determine whether CO-OP leads to improved performance in an untrained task. A single-subject design with multiple baselines across skills was adopted, with three replications. Four children with DCD (7-12years) received 10 sessions of CO-OP intervention where each child worked on three tasks during therapy sessions and a fourth task was identified, but not worked on, to verify inter-task transfer. Task performance was rated over four phases (baseline, intervention, post-intervention, follow-up) using the Performance Quality Rating Scale (PQRS-OD). Graphed data was statistically analyzed using a two or three standard deviation band method. Significant improvement was obtained for 11 of 12 tasks worked on during therapy and for two of the four untrained tasks. These results indicate that the effectiveness of CO-OP to improve untrained tasks in children merit further exploration. Copyright © 2016 Elsevier B.V. All rights reserved.
Cohen-Barak, Orit; Wildeman, Jacqueline; van de Wetering, Jeroen; Hettinga, Judith; Schuilenga-Hut, Petra; Gross, Aviva; Clark, Shane; Bassan, Merav; Gilgun-Sherki, Yossi; Mendzelevski, Boaz; Spiegelstein, Ofer
2015-05-01
Human plasma butyrylcholinesterase (BChE) contributes to cocaine metabolism and has been considered for use in treating cocaine addiction and cocaine overdose. TV-1380 is a recombinant protein composed of the mature form of human serum albumin fused at its amino terminus to the carboxy-terminus of a truncated and mutated BChE. In preclinical studies, TV-1380 has been shown to rapidly eliminate cocaine in the plasma thus forestalling entry of cocaine into the brain and heart. Two randomized, blinded phase I studies were conducted to evaluate the safety, pharmacokinetics, and pharmacodynamics of TV-1380, following single and multiple administration in healthy subjects. TV-1380 was found to be safe and well tolerated with a long half-life (43-77 hours) and showed a dose-proportional increase in systemic exposure. Consistent with preclinical results, the ex vivo cocaine hydrolysis, TV-1380 activity clearly increased upon treatment in a dose-dependent manner. In addition, there was a direct relationship between ex vivo cocaine hydrolysis (kel ) and TV-1380 serum concentrations. There was no evidence that TV-1380 affected heart rate, the uncorrected QT interval, or the heart-rate-corrected QTcF interval. TV-1380, therefore, offers a safe once-weekly therapy to increase cocaine hydrolysis. © 2015 The Authors. The Journal of Clinical Pharmacology Published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.
Mevissen, Liesbeth; Didden, Robert; Korzilius, Hubert; de Jongh, Ad
2017-12-01
This study explored the effectiveness of eye movement desensitisation and reprocessing (EMDR) therapy for post-traumatic stress disorder (PTSD) in persons with mild to borderline intellectual disability (MBID) using a multiple baseline across subjects design. One child and one adolescent with MBID, who met diagnostic criteria for PTSD according to a PTSD clinical interview (i.e., ADIS-C PTSD section), adapted and validated for this target group, were offered four sessions of EMDR. PTSD symptoms were measured before, during and after EMDR, and at six weeks follow-up. For both participants, number of PTSD symptoms decreased in response to treatment and both no longer met PTSD criteria at post-treatment. This result was maintained at 6-week follow-up. The results of this study add further support to the notion that EMDR can be an effective treatment for PTSD in children and adolescents with MBID. Replication of this study in larger samples and using a randomized controlled design is warranted. © 2017 John Wiley & Sons Ltd.
Karanika-Murray, M; Cox, T
2010-01-01
Although psychological theory acknowledges the existence of complex systems and the importance of nonlinear effects, linear statistical models have been traditionally used to examine relationships between environmental stimuli and outcomes. The way we analyse these relationships does not seem to reflect the way we conceptualize them. The present study investigated the application of connectionism (artificial neural networks) to modelling the relationships between work characteristics and empl...
Liu, M; Wang, X L; Zhang, D; Yang, M; Han, J; Zhang, Y N; Wang, Z L; Liu, H C
2014-06-01
A fixed dose combination tablet of niacin extended release (ER)/simvastatin was recently developed in China. This study was designed to assess and compare the pharmacokinetics of niacin, simvastatin and their metabolites in healthy Chinese subjects after single and multiple doses administration. From day 1 to day 7, 12 Chinese subjects were given a tablet every day at approximately 10 p.m. Serial blood samples were collected. Niacin and nicotinuric acid (NUA) in plasma, niacin, NUA, N-methylnicotinamide (MNA) and N-methyl-2-pyridone-5-carboxamide (2PY) in urine, simvastatin and simvastatin acid in plasma were determined by LC/MS/MS methods. Pharmacokinetic parameters on days 1 and 7 were compared. The main pharmacokinetic parameters for the single and multiple doses were as -follows: Niacin: Tmax were 3.8±1.5 h and 3.9±2.0 h; Cmax were 2 091±1 315 ng/ml and 2 323±1 542 ng/ml; AUC0-t were 4 123.88±3 138.48 ng ∙ h/ml and 4 385.98±3 127.05 ng ∙ h/ml. NUA: Tmax were 4.7±1.7 h and 3.8±1.5 h; Cmax were 1 057±549 ng/ml and 1 087±470 ng/ml; AUC0-t were 4 012.49±2 168.68 ng ∙ h/ml and 4 040.45±1 886.57 ng ∙ h/ml. Simvastatin: Tmax were 1.8±1.0 h and 2.5±2.5 h; Cmax were 3.15±1.67 ng/ml and 4.87±4.11 ng/ml; AUC0-t were 9.03±5.10 ng ∙ h/ml and 17.63±13.93 ng ∙ h/ml. Simvastatin acid: Tmax were 5.8±1.7 h and 6.5±1.4 h; Cmax were 4.22±2.10 ng/ml and 9.30±8.09 ng/ml; AUC0-t were 34.65±16.89 ng ∙ h/ml and 61.62±46.41 ng ∙ h/ml. Urine Recovery rate of total niacin: (40.55±7.38)% and (62.87±12.04)%. Compared with those after a single dose, pharmacokinetics of niacin and NUA was similar; total urine recovery of niacin was higher; exposure to simvastatin and simvastatin acid were higher following multiple doses. © Georg Thieme Verlag KG Stuttgart · New York.
Said-Houari, Belkacem
2017-01-01
This self-contained, clearly written textbook on linear algebra is easily accessible for students. It begins with the simple linear equation and generalizes several notions from this equation for the system of linear equations and introduces the main ideas using matrices. It then offers a detailed chapter on determinants and introduces the main ideas with detailed proofs. The third chapter introduces the Euclidean spaces using very simple geometric ideas and discusses various major inequalities and identities. These ideas offer a solid basis for understanding general Hilbert spaces in functional analysis. The following two chapters address general vector spaces, including some rigorous proofs to all the main results, and linear transformation: areas that are ignored or are poorly explained in many textbooks. Chapter 6 introduces the idea of matrices using linear transformation, which is easier to understand than the usual theory of matrices approach. The final two chapters are more advanced, introducing t...
Amir-Moez, A R; Sneddon, I N
1962-01-01
Elements of Linear Space is a detailed treatment of the elements of linear spaces, including real spaces with no more than three dimensions and complex n-dimensional spaces. The geometry of conic sections and quadric surfaces is considered, along with algebraic structures, especially vector spaces and transformations. Problems drawn from various branches of geometry are given.Comprised of 12 chapters, this volume begins with an introduction to real Euclidean space, followed by a discussion on linear transformations and matrices. The addition and multiplication of transformations and matrices a
DEFF Research Database (Denmark)
Grüner-Nielsen, L.; Clausen, Anders; Oxenløwe, Leif Katsuo
2000-01-01
A tuneable RZ-pulsesource over the entire EDFA gain bandwidth is proposed. The pulses show good performance in a transmission-experiment over 160 km Standard Single Mode Fibre and multiplexing/demultiplexing experiments. Expandable to a multiple RZ pulsesource....
Schneider, Hans
1989-01-01
Linear algebra is one of the central disciplines in mathematics. A student of pure mathematics must know linear algebra if he is to continue with modern algebra or functional analysis. Much of the mathematics now taught to engineers and physicists requires it.This well-known and highly regarded text makes the subject accessible to undergraduates with little mathematical experience. Written mainly for students in physics, engineering, economics, and other fields outside mathematics, the book gives the theory of matrices and applications to systems of linear equations, as well as many related t
Linear Algebra Thoroughly Explained
Vujičić, Milan
2008-01-01
Linear Algebra Thoroughly Explained provides a comprehensive introduction to the subject suitable for adoption as a self-contained text for courses at undergraduate and postgraduate level. The clear and comprehensive presentation of the basic theory is illustrated throughout with an abundance of worked examples. The book is written for teachers and students of linear algebra at all levels and across mathematics and the applied sciences, particularly physics and engineering. It will also be an invaluable addition to research libraries as a comprehensive resource book for the subject.
Linear Algebra and Linear Models
Indian Academy of Sciences (India)
This monograph provides an introduction to the basic aspects of the theory oflinear estima- tion and that of testing linear hypotheses. The primary objective is to provide a basic knowledge of analysis of linear models to advanced undergraduate or first year Master's students. The second edition virtually covers the same ...
Monahan, John F
2008-01-01
Preface Examples of the General Linear Model Introduction One-Sample Problem Simple Linear Regression Multiple Regression One-Way ANOVA First Discussion The Two-Way Nested Model Two-Way Crossed Model Analysis of Covariance Autoregression Discussion The Linear Least Squares Problem The Normal Equations The Geometry of Least Squares Reparameterization Gram-Schmidt Orthonormalization Estimability and Least Squares Estimators Assumptions for the Linear Mean Model Confounding, Identifiability, and Estimability Estimability and Least Squares Estimators F
Yan, Jun; Huang, Jian-Hua; He, Min; Lu, Hong-Bing; Yang, Rui; Kong, Bo; Xu, Qing-Song; Liang, Yi-Zeng
2013-08-01
Retention indices for frequently reported compounds of plant essential oils on three different stationary phases were investigated. Multivariate linear regression, partial least squares, and support vector machine combined with a new variable selection approach called random-frog recently proposed by our group, were employed to model quantitative structure-retention relationships. Internal and external validations were performed to ensure the stability and predictive ability. All the three methods could obtain an acceptable model, and the optimal results by support vector machine based on a small number of informative descriptors with the square of correlation coefficient for cross validation, values of 0.9726, 0.9759, and 0.9331 on the dimethylsilicone stationary phase, the dimethylsilicone phase with 5% phenyl groups, and the PEG stationary phase, respectively. The performances of two variable selection approaches, random-frog and genetic algorithm, are compared. The importance of the variables was found to be consistent when estimated from correlation coefficients in multivariate linear regression equations and selection probability in model spaces. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Cuss, C W; Guéguen, C
2014-01-01
This study reports on the development and application of a piecewise linear model for the determination of copper-binding parameters at concentrations in the nanomolar range using fluorescence quenching. L-Tyrosine, Suwannee River natural organic matter, and two leaf leachates with similar fluorescence signatures were used as test compounds, and results were compared with those of the standard Ryan-Weber model. The piecewise model was also applied to and compared with data from an earlier study. Parallel factor analysis (PARAFAC) was used to identify three to five independent fluorophores in each test compound, and copper-binding parameters were estimated for one to three binding sites for each fluorophore. The binding properties of similar and different fluorophores were also compared. The conditional binding strengths (log K') estimated using the piecewise approach were similar to those obtained using the Ryan-Weber approach (p > 0.05); however, the piecewise linear model provided superior results compared to models based on the Ryan-Weber equation in several ways, including (1) capable of distinguishing more binding sites for a single fluorophore, (2) capable of extracting binding parameters at environmentally relevant, nanomolar concentrations of copper, where fluorescence changes are often observed as enhancement, (3) greater precision over repeated titrations, and (4) no severe underestimation of complexing capacities. Finally, the copper-binding properties of PARAFAC components with similar optical signatures were found to be similar, both in sources with dramatically different and similar total fluorescence signatures.
Liesen, Jörg
2015-01-01
This self-contained textbook takes a matrix-oriented approach to linear algebra and presents a complete theory, including all details and proofs, culminating in the Jordan canonical form and its proof. Throughout the development, the applicability of the results is highlighted. Additionally, the book presents special topics from applied linear algebra including matrix functions, the singular value decomposition, the Kronecker product and linear matrix equations. The matrix-oriented approach to linear algebra leads to a better intuition and a deeper understanding of the abstract concepts, and therefore simplifies their use in real world applications. Some of these applications are presented in detailed examples. In several ‘MATLAB-Minutes’ students can comprehend the concepts and results using computational experiments. Necessary basics for the use of MATLAB are presented in a short introduction. Students can also actively work with the material and practice their mathematical skills in more than 300 exerc...
Searle, Shayle R
2012-01-01
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
Solow, Daniel
2014-01-01
This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.
Berberian, Sterling K
2014-01-01
Introductory treatment covers basic theory of vector spaces and linear maps - dimension, determinants, eigenvalues, and eigenvectors - plus more advanced topics such as the study of canonical forms for matrices. 1992 edition.
Directory of Open Access Journals (Sweden)
G. Selvaraju
2013-12-01
Full Text Available Aim: A study was undertaken to develop a forecasting model for predicting bluetongue outbreaks in North-west agroclimatic zone of Tamil Nadu, India. Materials and Methods: Eleven bluetongue outbreaks were characterised by active and passive surveillances for a period of twelve years and used in this study. Meteorological data comprising of maximum and minimum temperatures, relative humidity, rainfall and wind speed were collected and used as the multiple predictor variables in the multiple liner regression model. Results: A multiple liner regression model was developed for the North-west zone of Tamil Nadu. Values of the dependant variables were less than or greater than one, and indicated remote or greater chances of bluetongue outbreaks respectively. The monthly mean maximum and minimum temperatures, relative humidity at 8.30 h and at 17.00 h IST, wind speed, and monthly total rainfall of 29.1 - 31.0°C, 20.1 - 22.0°C, 80.1 85.0%, 65.1 70.0%, 3.1 5.0 km/h and < 200 mm respectively, were identified as the ideal climatic conditions for increased numbers of bluetongue outbreaks in this zone. Conclusion: Based on the values obtained from the prediction model, stake holders can be warned timely through the media to institute suitable prophylactic measures against bluetongue, to avoid economic losses due to disease. [Vet World 2013; 6(6.000: 321-324
Christofilos, N.C.; Polk, I.J.
1959-02-17
Improvements in linear particle accelerators are described. A drift tube system for a linear ion accelerator reduces gap capacity between adjacent drift tube ends. This is accomplished by reducing the ratio of the diameter of the drift tube to the diameter of the resonant cavity. Concentration of magnetic field intensity at the longitudinal midpoint of the external sunface of each drift tube is reduced by increasing the external drift tube diameter at the longitudinal center region.
Spiegelstein, Ofer; Stevens, Jasper; Van Gerven, Joop; Nathan, Pradeep J; Maynard, James P; Mayleben, David W; Hellriegel, Edward; Yang, Ronghua
2016-10-01
CEP-26401 is a novel orally active, brain-penetrant, high-affinity histamine H3 receptor (H3R) antagonist, with potential therapeutic utility in cognition enhancement. Two randomized, double-blind, placebo-controlled dose escalation studies with single (0.02 to 5 mg) or multiple administration (0.02 to 0.5 mg once daily) of CEP-26401 were conducted in healthy subjects. Plasma and urine samples were collected to investigate CEP-26401 pharmacokinetics. Pharmacodynamic endpoints included a subset of tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB) and nocturnal polysomnography. Population pharmacokinetic-pharmacodynamic modeling was conducted on one CANTAB and one polysomnography parameter of interest. CEP-26401 was slowly absorbed (median tmax range 3-6 hours) and the mean terminal elimination half-life ranged from 24-60 hours. Steady-state plasma concentrations were achieved within six days of dosing. CEP-26401 exhibits dose- and time-independent pharmacokinetics, and renal excretion is a major elimination pathway. CEP-26401 had a dose-dependent negative effect on sleep, with some positive effects on certain CANTAB cognitive parameters seen at lower concentrations. The derived three compartment population pharmacokinetic model, with first-order absorption and elimination, accurately described the available pharmacokinetic data. CEP-26401 was generally well tolerated up to 0.5 mg/day with most common treatment related adverse events being headache and insomnia. Further clinical studies are required to establish the potential of low-dose CEP-26401 in cognition enhancement. © The Author(s) 2016.
Feature Multi-Selection among Subjective Features
Sabato, Sivan; Kalai, Adam
2013-01-01
When dealing with subjective, noisy, or otherwise nebulous features, the "wisdom of crowds" suggests that one may benefit from multiple judgments of the same feature on the same object. We give theoretically-motivated `feature multi-selection' algorithms that choose, among a large set of candidate features, not only which features to judge but how many times to judge each one. We demonstrate the effectiveness of this approach for linear regression on a crowdsourced learning task of predicting...
Shen, Qing; Ogomi, Yuhei; Park, Byung-wook; Inoue, Takafumi; Pandey, Shyam S; Miyamoto, Akari; Fujita, Shinsuke; Katayama, Kenji; Toyoda, Taro; Hayase, Shuzi
2012-04-07
Understanding the electron transfer dynamics at the interface between dye sensitizer and semiconductor nanoparticle is very important for both a fundamental study and development of dye-sensitized solar cells (DSCs), which are a potential candidate for next generation solar cells. In this study, we have characterized the ultrafast photoexcited electron dynamics in a newly produced linearly-linked two dye co-sensitized solar cell using both a transient absorption (TA) and an improved transient grating (TG) technique, in which tin(IV) 2,11,20,29-tetra-tert-butyl-2,3-naphthalocyanine (NcSn) and cis-diisothiocyanato-bis(2,2'-bipyridyl-4,4'-dicarboxylato)ruthenium(II) bis(tetrabutylammonium) (N719) are molecularly and linearly linked and are bonded to the surface of a nanocrystalline tin dioxide (SnO(2)) electrode by a metal-O-metal linkage (i.e. SnO(2)-NcSn-N719). By comparing the TA and TG kinetics of NcSn, N719, and hybrid NcSn-N719 molecules adsorbed onto both of the SnO(2) and zirconium dioxide (ZrO(2)) nanocrystalline films, the forward and backward electron transfer dynamics in SnO(2)-NcSn-N719 were clarified. We found that there are two pathways for electron injection from the linearly-linked two dye molecules (NcSn-N719) to SnO(2). The first is a stepwise electron injection, in which photoexcited electrons first transfer from N719 to NcSn with a transfer time of 0.95 ps and then transfer from NcSn to the conduction band (CB) of SnO(2) with two timescales of 1.6 ps and 4.2 ps. The second is direct photoexcited electron transfer from N719 to the CB of SnO(2) with a timescale of 20-30 ps. On the other hand, back electron transfer from SnO(2) to NcSn is on a timescale of about 2 ns, which is about three orders of magnitude slower compared to the forward electron transfer from NcSn to SnO(2). The back electron transfer from NcSn to N719 is on a timescale of about 40 ps, which is about one order slower compared to the forward electron transfer from N719 to Nc
Bielawa, R. L.
1976-01-01
The differential equations of motion for the lateral and torsional deformations of a nonlinearly twisted rotor blade in steady flight conditions together with those additional aeroelastic features germane to composite bearingless rotors are derived. The differential equations are formulated in terms of uncoupled (zero pitch and twist) vibratory modes with exact coupling effects due to finite, time variable blade pitch and, to second order, twist. Also presented are derivations of the fully coupled inertia and aerodynamic load distributions, automatic pitch change coupling effects, structural redundancy characteristics of the composite bearingless rotor flexbeam - torque tube system in bending and torsion, and a description of the linearized equations appropriate for eigensolution analyses. Three appendixes are included presenting material appropriate to the digital computer program implementation of the analysis, program G400.
Williams, D Keith; Chadwick, M Ashley; Williams, Taufika Islam; Muddiman, David C
2008-12-01
Operation of any mass spectrometer requires implementation of mass calibration laws to translate experimentally measured physical quantities into a m/z range. While internal calibration in Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) offers several attractive features, including exposure of calibrant and analyte ions to identical experimental conditions (e.g. space charge), external calibration affords simpler pulse sequences and higher throughput. The automatic gain control method used in hybrid linear trap quadrupole (LTQ) FT-ICR-MS to consistently obtain the same ion population is not readily amenable to matrix-assisted laser desorption/ionization (MALDI) FT-ICR-MS, due to the heterogeneous nature and poor spot-to-spot reproducibility of MALDI. This can be compensated for by taking external calibration laws into account that consider magnetic and electric fields, as well as relative and total ion abundances. Herein, an evaluation of external mass calibration laws applied to MALDI-FT-ICR-MS is performed to achieve higher mass measurement accuracy (MMA). Copyright (c) 2008 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
De Pasquale C
2014-06-01
Full Text Available Concetta De Pasquale,1,2 Maria Luisa Pistorio,1 Massimiliano Veroux,2 Alessia Giaquinta,2 Pierfrancesco Veroux,2 Michele Fornaro11Department of Education Science, University of Catania, Catania, Italy; 2Vascular Surgery and Organ Transplant Unit, Department of Surgery Transplantation and Advanced Technologies, University Hospital of Catania, Catania, ItalyBackground: Multiple sclerosis (MS is a disease of the nervous system that has profound effects on everyday functioning and quality of life of not only the person who is diagnosed, but also her/his family and acquaintances. Despite this, the uncertainties of the actual etiological basis of MS make it difficult to reach a conclusive statement about the optimal therapeutic management of the disease, which may differ depending on the given case and phase of illness. This has led to an interest in potential novel therapeutic avenues, including percutaneous transluminal angioplasty (PTA. Yet, evidence in support of PTA in the management of MS is scarce and contradictory. The aim of the present study was to provide a preliminary assessment as to whether PTA may impact subjective quality of life and cognitive functioning in severe MS. Method: Ninety-five MS outpatients were followed-up for 24 months on a scheduled basis using the Milan Overall Dementia Assessment and the short-form 36-item scales, and were clinically evaluated by an appointed neurologist and psychiatrist. Results: At end point (month 24, only a minority of patients were still active in the study (n=33 or 34.74%. Among other measures, those who remained in the study until completion showed a significantly better Expanded Disability Status Scale and Milan Overall Dementia Assessment autonomy profile at study entrance compared to those patients who did not remain in the study until completion. Limitations were: a lack of any active control group; small sample size; Berkson’s bias; and selection by indication biases.Conclusion: Given
On the linear programming bound for linear Lee codes.
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.
Malygin, Ya V; Tsygankov, B D
To find out the factors of satisfaction with psychiatric help in inpatients with neurotic and depressive disorders depending on the moment of satisfaction evaluation and patients' treatment experience. The sample included 266 first-time admission inpatients (satisfaction was evaluated at the moment of discharge) and 134 rehospitalized inpatients (satisfaction with previous treatment was evaluated at the moment of discharge; satisfaction with current treatment was evaluated at the moment of rehospitalization). The survey was performed using a questionnaire designed for this study. Statistical analysis was performed using multiple regression. Satisfaction with nursing care was the key factor of satisfaction at the moment of discharge among both groups of inpatients (first-time admission and rehospitalization). Psychiatrist's empathy was the 2nd factor by importance. The structure of factors of medical service satisfaction of these 2 groups was different. General satisfaction with psychiatrist's work was the key factor of satisfaction with medical service during previous hospitalization while nursing care was twice less important. In whole, there were major differences in the structure of factors of medical service satisfaction during previous and current hospitalizations. The shift of importance from nursing care to psychiatrist's work and other differences in the structure of factors of satisfaction of rehospitalized patients with medical services can be explained by belonging of medical services to credible goods - patient is able to evaluate results of treatment only some period after discharge.
Directory of Open Access Journals (Sweden)
Wensheng Zhang
Full Text Available Single-nucleotide polymorphisms (SNPs contribute to the between-individual expression variation of many genes. A regulatory (trait-associated SNP is usually located near or within a (host gene, possibly influencing the gene's transcription or/and post-transcriptional modification. But its targets may also include genes that are physically farther away from it. A heuristic explanation of such multiple-target interferences is that the host gene transfers the SNP genotypic effects to the distant gene(s by a transcriptional or signaling cascade. These connections between the host genes (regulators and the distant genes (targets make the genetic analysis of gene expression traits a promising approach for identifying unknown regulatory relationships. In this study, through a mixed model analysis of multi-source digital expression profiling for 140 human lymphocyte cell lines (LCLs and the genotypes distributed by the international HapMap project, we identified 45 thousands of potential SNP-induced regulatory relationships among genes (the significance level for the underlying associations between expression traits and SNP genotypes was set at FDR < 0.01. We grouped the identified relationships into four classes (paradigms according to the two different mechanisms by which the regulatory SNPs affect their cis- and trans- regulated genes, modifying mRNA level or altering transcript splicing patterns. We further organized the relationships in each class into a set of network modules with the cis- regulated genes as hubs. We found that the target genes in a network module were often characterized by significant functional similarity, and the distributions of the target genes in three out of the four networks roughly resemble a power-law, a typical pattern of gene networks obtained from mutation experiments. By two case studies, we also demonstrated that significant biological insights can be inferred from the identified network modules.
Karloff, Howard
1991-01-01
To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...
Linear algebra and its applications
Lax, Peter D
2013-01-01
Praise for the First Edition"". . .recommended for the teacher and researcher as well as for graduate students. In fact, [it] has a place on every mathematician's bookshelf."" -American Mathematical MonthlyLinear Algebra and Its Applications, Second Edition presents linear algebra as the theory and practice of linear spaces and linear maps with a unique focus on the analytical aspects as well as the numerous applications of the subject. In addition to thorough coverage of linear equations, matrices, vector spaces, game theory, and numerical analysis, the Second Edition features
Directory of Open Access Journals (Sweden)
Maryam Khodadadi
2016-06-01
Full Text Available Background: Data mining (DM is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (WSP in Birjand, a city in Eastern Iran. Methods: Multiple regression (MR and neural network (NN models were examined using influent characteristics (pH, Biochemical oxygen demand [BOD5], temperature, chemical oxygen demand [COD], total suspended solids [TSS], total dissolved solid [TDS], electrical conductivity [EC] and turbidity as the regression input vectors. Models were adjusted to input attributes, effluent BOD5 (BODout and COD (CODout. The models performances were estimated by 10-fold external cross-validation. An internal 5-fold cross-validation was also used for the training data set in NN model. The models were compared using regression error characteristic (REC plot and other statistical measures such as relative absolute error (RAE. Sensitivity analysis was also applied to extract useful knowledge from NN model. Results: NN models (with RAE = 78.71 ± 1.16 for BODout and 83.67 ± 1.35 for CODout and MR models (with RAE = 84.40% ± 1.07 for BODout and 88.07 ± 0.80 for CODout indicate different performances and the former was better (P < 0.05 for the prediction of both effluent BOD5 and COD parameters. For the prediction of CODout the NN model with hidden layer size (H = 4 and decay factor = 0.75 ± 0.03 presented the best predictive results. For BODout the H and decay factor were found to be 4 and 0.73 ± 0.03, respectively. TDS was found as the most descriptive influent wastewater characteristics for the prediction of the WSP performance. The REC plots confirmed the NN model performance superiority for both BOD and COD effluent prediction. Conclusion: Modeling the performance of WSP systems using NN models along with sensitivity analysis can offer better
Hogben, Leslie
2013-01-01
With a substantial amount of new material, the Handbook of Linear Algebra, Second Edition provides comprehensive coverage of linear algebra concepts, applications, and computational software packages in an easy-to-use format. It guides you from the very elementary aspects of the subject to the frontiers of current research. Along with revisions and updates throughout, the second edition of this bestseller includes 20 new chapters.New to the Second EditionSeparate chapters on Schur complements, additional types of canonical forms, tensors, matrix polynomials, matrix equations, special types of
National Aeronautics and Space Administration — A method has been developed for prognostication of accrued prior damage in electronics subjected to overlapping sequential environments of thermal aging and thermal...
National Research Council Canada - National Science Library
Rocha, José Francisco; Almeida, Luis; Falcão, Amílcar; Palma, P. Nuno; Loureiro, Ana I; Pinto, Roberto; Bonifácio, Maria João; Wright, Lyndon C; Nunes, Teresa; Soares‐da‐Silva, Patrício
2013-01-01
...) activity following repeated doses of opicapone. This randomized, placebo-controlled, double-blind study enrolled healthy male subjects who received either once daily placebo or opicapone 5, 10, 20 or 30 mg for 8 days...
González-Díaz, Humberto; Arrasate, Sonia; Gómez-SanJuan, Asier; Sotomayor, Nuria; Lete, Esther; Besada-Porto, Lina; Ruso, Juan M
2013-01-01
In general perturbation methods starts with a known exact solution of a problem and add "small" variation terms in order to approach to a solution for a related problem without known exact solution. Perturbation theory has been widely used in almost all areas of science. Bhor's quantum model, Heisenberg's matrix mechanincs, Feyman diagrams, and Poincare's chaos model or "butterfly effect" in complex systems are examples of perturbation theories. On the other hand, the study of Quantitative Structure-Property Relationships (QSPR) in molecular complex systems is an ideal area for the application of perturbation theory. There are several problems with exact experimental solutions (new chemical reactions, physicochemical properties, drug activity and distribution, metabolic networks, etc.) in public databases like CHEMBL. However, in all these cases, we have an even larger list of related problems without known solutions. We need to know the change in all these properties after a perturbation of initial boundary conditions. It means, when we test large sets of similar, but different, compounds and/or chemical reactions under the slightly different conditions (temperature, time, solvents, enzymes, assays, protein targets, tissues, partition systems, organisms, etc.). However, to the best of our knowledge, there is no QSPR general-purpose perturbation theory to solve this problem. In this work, firstly we review general aspects and applications of both perturbation theory and QSPR models. Secondly, we formulate a general-purpose perturbation theory for multiple-boundary QSPR problems. Last, we develop three new QSPR-Perturbation theory models. The first model classify correctly >100,000 pairs of intra-molecular carbolithiations with 75-95% of Accuracy (Ac), Sensitivity (Sn), and Specificity (Sp). The model predicts probabilities of variations in the yield and enantiomeric excess of reactions due to at least one perturbation in boundary conditions (solvent, temperature
A two-phase linear programming approach for redundancy allocation problems
Directory of Open Access Journals (Sweden)
Hsieh Yi-Chih
2002-01-01
Full Text Available Provision of redundant components in parallel is an efficient way to increase the system reliability, however, the weight, volume and cost of the system will increase simultaneously. This paper proposes a new two-phase linear programming approach for solving the nonlinear redundancy allocation problems subject to multiple linear constraints. The first phase is used to approximately allocate the resource by using a general linear programming, while the second phase is used to re-allocate the slacks of resource by using a 0-1 integer linear programming. Numerical results demonstrate the effectiveness and efficiency of the proposed approach.
Ranking Forestry Investments With Parametric Linear Programming
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.
Yi, Jun; Yang, Wenhong; Sun, Wen-Hua; Nomura, Kotohiro; Hada, Masahiko
2017-11-30
The NMR chemical shifts of vanadium ( 51 V) in (imido)vanadium(V) dichloride complexes with imidazolin-2-iminato and imidazolidin-2-iminato ligands were calculated by the density functional theory (DFT) method with GIAO. The calculated 51 V NMR chemical shifts were analyzed by the multiple linear regression (MLR) analysis (MLRA) method with a series of calculated molecular properties. Some of calculated NMR chemical shifts were incorrect using the optimized molecular geometries of the X-ray structures. After the global minimum geometries of all of the molecules were determined, the trend of the observed chemical shifts was well reproduced by the present DFT method. The MLRA method was performed to investigate the correlation between the 51 V NMR chemical shift and the natural charge, band energy gap, and Wiberg bond index of the V═N bond. The 51 V NMR chemical shifts obtained with the present MLR model were well reproduced with a correlation coefficient of 0.97.
Directory of Open Access Journals (Sweden)
Majid Mohammadhosseini
2014-05-01
Full Text Available A reliable quantitative structure retention relationship (QSRR study has been evaluated to predict the retention indices (RIs of a broad spectrum of compounds, namely 118 non-linear, cyclic and heterocyclic terpenoids (both saturated and unsaturated, on an HP-5MS fused silica column. A principal component analysis showed that seven compounds lay outside of the main cluster. After elimination of the outliers, the data set was divided into training and test sets involving 80 and 28 compounds. The method was tested by application of the particle swarm optimization (PSO method to find the most effective molecular descriptors, followed by multiple linear regressions (MLR. The PSO-MLR model was further confirmed through “leave one out cross validation” (LOO-CV and “leave group out cross validation” (LGO-CV, as well as external validations. The promising statistical figures of merit associated with the proposed model (R2train=0.936, Q2LOO=0.928, Q2LGO=0.921, F=376.4 confirm its high ability to predict RIs with negligible relative errors of predictions (REP train=4.8%, REP test=6.0%.
Colucci, Philippe; Pottage, John C.; Robison, Heather; Turgeon, Jacques; Schuermann, Dirk; Hoepelman, I. M.; Ducharme, Murray P.
The purpose of this study was to describe the plasma pharmacokinetics (PK) of elvucitabine at different doses when administered daily or every other day for 21 days with lopinavir-ritonavir ( Kaletra) in human immunodeficiency virus (HIV)-infected subjects. Three different dosing regimens of
Wynia, K.; Middel, B.; de Ruiter, H.; van Dijk, J.P.; Lok, W.S.; De Keyser, J.H.; Reijneveld, S.A.
2009-01-01
Objective. The subjective dimension of disability, the perception of disability, is a dimension missing from the International Classification of Functioning, Disability and Health (ICF), and from health-related quality of life (HRQOL) instruments. However, it is a highly relevant dimension for
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Directory of Open Access Journals (Sweden)
Chaoying Hu
Full Text Available Darapladib is a lipoprotein-associated phospholipase A2 (Lp-PLA2 inhibitor. This study evaluated the pharmacokinetics, pharmacodynamics and safety of darapladib in healthy Chinese subjects.Twenty-four subjects received darapladib 160 mg orally, approximately 1 hour after a standard breakfast, as a single dose and once daily for 28 days. Non-compartmental methods were used to determine the single and multiple dose pharmacokinetics of darapladib and its metabolite SB-553253. Repeat dose Lp-PLA2 activity and safety were evaluated.Systemic exposure (AUC(0-T, Cmax geometric mean (CVb% of darapladib was higher after multiple-dosing (519 ng.h/mL (33.3%, 34.4 ng/mL (49.9% compared to single-dose administration (153 ng.h/mL (69.0%, 17.9 ng/mL (55.2%. The steady-state accumulation ratio was less than unity (Rs = 0.80, indicating time-dependent pharmacokinetics of darapladib. Darapladib steady-state was reached by Day 14 of once daily dosing. Systemic exposure to SB-553253 was lower than darapladib with median (SB-553253: darapladib ratios for AUC(0-τ of 0.0786 for single dose and 0.0532 for multiple dose administration. On Day 28, pre-dose and maximum inhibition of Lp-PLA2 activity was approximately 70% and 75% relative to the baseline value, respectively and was dependent of darapladib concentration. The most common adverse events (≥ 21% subjects were abnormal faeces, abnormal urine odour, diarrhoea and nasopharyngitis.Darapladib 160 mg single and repeat doses were profiled in healthy Chinese subjects. Single dose systemic exposure to darapladib in healthy Chinese subjects was consistent with that observed previously in Western subjects whereas steady-state systemic exposure was approximately 65% higher in Chinese than Western subjects. The Lp-PLA2 activity and adverse event profile were similar in healthy Chinese and previous reports in Western subjects. Ethnic-specific dose adjustment of darapladib is not considered necessary for the Chinese
Hood, John Linsley
2013-01-01
The Art of Linear Electronics presents the principal aspects of linear electronics and techniques in linear electronic circuit design. The book provides a wide range of information on the elucidation of the methods and techniques in the design of linear electronic circuits. The text discusses such topics as electronic component symbols and circuit drawing; passive and active semiconductor components; DC and low frequency amplifiers; and the basic effects of feedback. Subjects on frequency response modifying circuits and filters; audio amplifiers; low frequency oscillators and waveform generato
Directory of Open Access Journals (Sweden)
A. A. Bosov
2015-04-01
Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets
Streeter, Anthony J; Faria, Ellen C
2017-06-01
The elderly constitute a significant, potentially sensitive, subpopulation within the general population, which must be taken into account when performing risk assessments including determining an acceptable daily exposure (ADE) for the purpose of a cleaning validation. Known differences in the pharmacokinetics of drugs between young adults (who are typically the subjects recruited into clinical trials) and the elderly are potential contributors affecting the interindividual uncertainty factor (UFH) component of the ADE calculation. The UFH values were calculated for 206 drugs for young adult and elderly groups separately and combined (with the elderly assumed to be a sensitive subpopulation) from published studies where the pharmacokinetics of the young adult and elderly groups were directly compared. Based on the analysis presented here, it is recommended to use a default UFH value of 10 for worker populations (which are assumed to be approximately equivalent to the young adult groups) where no supporting pharmacokinetic data exist, while it is recommended to use a default UFH value of 15 for the general population, to take the elderly into consideration when calculating ADE values. The underlying reasons for the large differences between the exposures in the young adult and elderly subjects for the 10 compounds which show the greatest separation are different in almost every case, involving the OCT2 transporter, glucuronidation, hydrolysis, CYP1A2, CYP2A6, CYP2C19, CYP2D6, CYP3A4 or CYP3A5. Therefore, there is no consistent underlying mechanism which appears responsible for the largest differences in pharmacokinetic parameters between young adult and elderly subjects. Copyright © 2017 Elsevier GmbH. All rights reserved.
Directory of Open Access Journals (Sweden)
Ivo Marinić-Kragić
2016-01-01
Full Text Available Fully generic 3D shapes of centrifugal roof fan vanes are explored based on a custom-developed numerical workflow with the ability to vary the vane 3D shape by manipulating the control points of parametric surfaces and change the number of vanes and rotation speed. An excellence formulation is based on design flow efficiency, multi-regime operational conditions and noise criteria for various cases, including multi-objective optimization. Multiple cases of optimization demonstrate the suitability of customized and individualized fan designs for specific working environments according to the selected excellence criteria. Noise analysis is considered as an additional decision-making tool for cases where multiple solutions of equal efficiency are generated and as an additional criteria for multi-objective optimization. The 3D vane shape enables further gains in efficiency compared to 2D shape optimization, while multi-objective optimization with noise as an additional criterion shows potential to greatly reduce the roof fan noise with only small losses in efficiency. The developed workflow which comprises (i a 3D parametric shape modeler, (ii an evolutionary optimizer and (iii a computational fluid dynamics (CFD simulator can be viewed as an integral tool for optimizing the designs of roof fans under custom conditions.
Rhodes, Ryan E; Courneya, Kerry S
2003-03-01
The presence of two subcomponents within each theory of planned behaviour (TPB) concept of attitude (affective and instrumental), subjective norm (injunctive and descriptive), and PBC (self-efficacy and controllability) has been widely supported. However, research has not examined whether the commonality of variance between these components (i.e. a general factor) or the specificity of variance within the subcomponents influences intention and behaviour. Therefore, the purpose of this study was to examine the optimal conceptualization of either two subcomponents or a general common factor for each TPB concept within an omnibus model. Further, to test whether conceptualizations may differ by population even within the same behavioural domain, we examined these research questions with 300 undergraduates (M age = 20) and 272 cancer survivors (M age = 61) for exercise behaviour. Results identified that a general subjective norm factor was an optimal predictive conceptualization over two separate injunctive and descriptive norm components. In contrast, a specific self-efficacy component, and not controllability or a general factor of PBC, predicted intention optimally for both samples. Finally, optimal models of attitude differed between the populations, with a general factor best predicting intention for undergraduates but only affective attitude influencing intention for cancer survivors. The findings of these studies underscore the possibility for optimal tailored interventions based on population and behaviour. Finally, a discussion of the theoretical ambiguity of the PBC concept led to suggestions for future research and possible re-conceptualization.
Directory of Open Access Journals (Sweden)
Ronny eScherer
2015-10-01
Full Text Available Research on educational effectiveness most often uses student assessments of classroom instruction for measuring aspects of teaching quality. Given that crucial inferences on the success of education are based on these assessments, it is essential to ensure that they provide valid indicators. In this study, we illustrate the application of an innovative application of a multilevel bifactor structural equation model (ML-BFSEM to examine the validity of student assessments. Analyzing a large-scale data set of 12,077 fourth-grade students in three countries (Finland, Norway, and Sweden, we find that (a three aspects of teaching quality and subject domain factors can be established; (b metric and scalar invariance could be established for the ML-BFSEM approach across countries; (c significant relations between students’ assessments of how easy the teacher is to understand and achievement in all subjects exist. In support of substantive research, we demonstrate a methodological approach for representing the complex nature of student assessments of teaching quality. We finally encourage substantive and methodological researchers to advance the ML-BFSEM.
Directory of Open Access Journals (Sweden)
Larijani Kambiz
2011-01-01
Full Text Available The chemical composition of the volatile fraction obtained by head-space solid phase microextraction (HS-SPME, single drop microextraction (SDME and the essential oil obtained by cold-press from the peels of C. sinensis cv. valencia were analyzed employing gas chromatography-flame ionization detector (GC-FID and gas chromatography-mass spectrometry (GC-MS. The main components were limonene (61.34 %, 68.27 %, 90.50 %, myrcene (17.55 %, 12.35 %, 2.50 %, sabinene (6.50 %, 7.62 %, 0.5 % and α-pinene (0 %, 6.65 %, 1.4 % respectively obtained by HS-SPME, SDME and cold-press. Then a quantitative structure-retention relationship (QSRR study for the prediction of retention indices (RI of the compounds was developed by application of structural descriptors and the multiple linear regression (MLR method. Principal components analysis was used to select the training set. A simple model with low standard errors and high correlation coefficients was obtained. The results illustrated that linear techniques such as MLR combined with a successful variable selection procedure are capable of generating an efficient QSRR model for prediction of the retention indices of different compounds. This model, with high statistical significance (R2 train = 0.983, R2 test = 0.970, Q2 LOO = 0.962, Q2 LGO = 0.936, REP(% = 3.00, could be used adequately for the prediction and description of the retention indices of the volatile compounds.
Täubel, J; Ferber, G; Fernandes, S; Santamaría, E; Izquierdo, I
2017-08-01
A thorough QT/QTc study in healthy white Caucasian subjects demonstrated that rupatadine has no proarrhythmic potential and raised no cardiac safety concerns. The present phase 1 study aimed to confirm the cardiac safety of rupatadine in healthy Japanese subjects. In this randomized, double-blind, placebo-controlled study, 27 healthy Japanese subjects were administered single and multiple escalating rupatadine doses of 10, 20, and 40 mg or placebo. Triplicate electrocardiogram (ECG) recordings were performed on days -1, 1, and 5 at several points, and time-matched pharmacokinetic samples were also collected. Concentration-effect analysis based on the change in the QT interval corrected using Fridericia's formula (QTcF) from average baseline was performed. Data from the formal TQT study in white Caucasian subjects was used for a comparison analysis. The ECG data for rupatadine at doses up to 40 mg did not show an effect on the QTc interval of regulatory concern. The sensitivity of this study to detect small changes in the QTc interval was confirmed by demonstrating a significant shortening of QTcF on days 1 and 5 four hours after a standardized meal. The data from this study exhibited no statistically significant differences in the QTc effect between Japanese and white Caucasian subjects. © 2017, The American College of Clinical Pharmacology.
De Silva, Anurika Priyanjali; Moreno-Betancur, Margarita; De Livera, Alysha Madhu; Lee, Katherine Jane; Simpson, Julie Anne
2017-07-25
Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies. We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems. The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one. We recommend the use of FCS or MVNI in a similar
Lopez, Cesar
2014-01-01
MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Linear Algebra introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to
Rico, Salvador; Antonijoan, Rosa-María; Ballester, Maria Rosa; Gutierro, Ibon; Ayani, Ignacio; Martinez-Gonzalez, Javier; Borrell, Montserrat; Fontcuberta, Jordi; Gich, Ignasi
2014-06-01
Aging and renal impairment may prolong the half-life and lead to accumulation of low molecular weight heparins. Correct dosing is critical to prevent bleeding or thrombosis. Open, parallel study. Healthy adult [n=13] and elderly (>65yrs) [n=12] volunteers; and subjects with mild (ClCr≥50 to ≤80mL/min, n=8), moderate (ClCr≥30 to <50mL/min, n=7), and severe (ClCr<30mL/min, n=8) renal impairment received four prophylactic doses (3,500IU/24h) and a single therapeutic dose (115IU/kg) of bemiparin with an interim washout period. Anti-FXa activity and the potential need for dose adjustment were evaluated. There were statistically significant differences in the severe renal impairment group vs. adult volunteers in all anti-FXa related parameters, but no significant differences in any of the anti-FXa related parameters between the adult and the elderly. Anti-FXa simulations after 10 prophylactic doses predicted mean Amax=0.59IU/mL in subjects with severe renal impairment and 0.33-0.39IU/mL in the rest. Simulations in the severe renal impairment group with dose adjustment (2,500IU/24h) predicted all individual Amax<0.60IU/mL (mean Amax=0.42IU/ml). Simulations after 10 therapeutic doses predicted mean Amax=1.22IU/mL in severe renal impairment group and 0.89-0.98IU/mL in the rest. Simulations in the severe renal impairment group with 75% dose adjustment predicted individual Amax≤1.60IU/mL (mean Amax=0.91IU/mL). No dose adjustments are required in elderly with preserved renal function. A dose adjustment of bemiparin is only advisable in patients with severe renal impairment when using prophylactic or therapeutic doses. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gutman, Sharon A; Raphael-Greenfield, Emily I; Rao, Ashwini K
2012-01-01
OBJECTIVE. We examined the effect of a motor-based role-play intervention on the social skills of adolescents with high-functioning autism. METHOD. An ABA multiple-baseline design with three 3-mo phases occurring over 12 mo was used with 7 participants. Frequency of targeted verbal and nonverbal behaviors was tallied in each phase. Frequency data were analyzed using repeated-measures analyses of variance with post hoc comparisons to examine differences in targeted behaviors over the three phases. RESULTS. Three participants completed all three study phases, 2 completed Phase 2, and 2 completed Phase 1. All participants (N = 7) demonstrated improved social skill use in Phase 1. Participants completing Phase 2 (n = 5) further improved social skill use. Additional improvements were observed among participants (n = 3) who completed Phase 3. CONCLUSION. The intervention helped participants improve targeted social skill use. Further testing with larger samples and intervention modifications is warranted. Copyright © 2012 by the American Occupational Therapy Association, Inc.
On Systems of Linear Quaternion Functions
Ell, Todd A.
2007-01-01
A method of reducing general quaternion functions of first degree, i.e., linear quaternion functions, to quaternary canonical form is given. Linear quaternion functions, once reduced to canonical form, can be maintained in this form under functional composition. furthermore, the composition operation is symbolically identical to quaternion multiplication, making manipulation and reduction of systems of linear quaternion functions straight forward.
Furnham, Adrian; Arteche, Adriane; Chamorro-Premuzic, Tomas; Keser, Askin; Swami, Viren
2009-12-01
This study is part of a programmatic research effort into the determinants of self-assessed abilities. It examined cross-cultural differences in beliefs about intelligence and self- and other-estimated intelligence in two countries at extreme ends of the European continent. In all, 172 British and 272 Turkish students completed a three-part questionnaire where they estimated their parents', partners' and own multiple intelligences (Gardner (10) and Sternberg (3)). They also completed a measure of the 'big five' personality scales and rated six questions about intelligence. The British sample had more experience with IQ tests than the Turks. The majority of participants in both groups did not believe in sex differences in intelligence but did think there were race differences. They also believed that intelligence was primarily inherited. Participants rated their social and emotional intelligence highly (around one standard deviation above the norm). Results suggested that there were more cultural than sex differences in all the ratings, with various interactions mainly due to the British sample differentiating more between the sexes than the Turks. Males rated their overall, verbal, logical, spatial, creative and practical intelligence higher than females. Turks rated their musical, body-kinesthetic, interpersonal and intrapersonal intelligence as well as existential, naturalistic, emotional, creative, and practical intelligence higher than the British. There was evidence of participants rating their fathers' intelligence on most factors higher than their mothers'. Factor analysis of the ten Gardner intelligences yield two clear factors: cognitive and social intelligence. The first factor was impacted by sex but not culture; it was the other way round for the second factor. Regressions showed that five factors predicted overall estimates: sex (male), age (older), test experience (has done tests), extraversion (strong) and openness (strong). Results are discussed in
Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.
Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J
2016-04-01
The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.
Practical Session: Simple Linear Regression
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).
Introduction to generalized linear models
Dobson, Annette J
2008-01-01
Introduction Background Scope Notation Distributions Related to the Normal Distribution Quadratic Forms Estimation Model Fitting Introduction Examples Some Principles of Statistical Modeling Notation and Coding for Explanatory Variables Exponential Family and Generalized Linear Models Introduction Exponential Family of Distributions Properties of Distributions in the Exponential Family Generalized Linear Models Examples Estimation Introduction Example: Failure Times for Pressure Vessels Maximum Likelihood Estimation Poisson Regression Example Inference Introduction Sampling Distribution for Score Statistics Taylor Series Approximations Sampling Distribution for MLEs Log-Likelihood Ratio Statistic Sampling Distribution for the Deviance Hypothesis Testing Normal Linear Models Introduction Basic Results Multiple Linear Regression Analysis of Variance Analysis of Covariance General Linear Models Binary Variables and Logistic Regression Probability Distributions ...
Analysis of non-linear response of the human body to vertical whole-body vibration.
Tarabini, Marco; Solbiati, Stefano; Moschioni, Giovanni; Saggin, Bortolino; Scaccabarozzi, Diego
2014-01-01
The human response to vibration is typically studied using linear estimators of the frequency response function, although different literature works evidenced the presence of non-linear effects in whole-body vibration response. This paper analyses the apparent mass of standing subjects using the conditioned response techniques in order to understand the causes of the non-linear behaviour. The conditioned apparent masses were derived considering models of increasing complexity. The multiple coherence function was used as a figure of merit for the comparison between the linear and the non-linear models. The apparent mass of eight male subjects was studied in six configurations (combinations of three vibration magnitudes and two postures). The contribution of the non-linear terms was negligible and was endorsed to the change of modal parameters during the test. Since the effect of the inter-subject variability was larger than that due to the increase in vibration magnitude, the biodynamic response should be more meaningfully modelled using a linear estimator with uncertainty rather than looking for a non-linear modelling.
Linear Algebra and Smarandache Linear Algebra
Vasantha, Kandasamy
2003-01-01
The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and ve...
Directory of Open Access Journals (Sweden)
Antonio C. Quental
2005-11-01
Full Text Available Os polietilenos lineares de baixa densidade (PELBD são uma classe de polietilenos com cadeias lineares contendo somente ramificações de cadeia curta devido à inserção de uma alfa-olefina durante as reações de copolimerização com o eteno. As alfa-olefinas comumente utilizadas são o 1-buteno, o 1-hexeno e o 1-octeno. Dependendo da alfa-olefina e do catalisador utilizado na polimerização, os PELBD apresentam microestruturas que resultam em diferentes propriedades térmicas e mecânicas. Uma técnica simples e eficaz para a avaliação da distribuição de comonômeros nas cadeias poliméricas é o fracionamento por cristalização isotérmica a partir do estado fundido realizado via DSC. Neste método submete-se o polímero a diversas cristalizações isotérmicas durante o resfriamento, a partir do estado fundido. Este processo favorece a separação da fração cristalina em grupos contendo lamelas de diferentes espessuras, dependendo da distribuição da aolefina ao longo da cadeia do polímero e da massa molar. Durante o posterior aquecimento das amostras fracionadas observam-se picos endotérmicos em número igual ao de isotermas, que fornecem informações sobre a distribuição relativa dos comonômeros ao longo das cadeias dos PELBD. Neste trabalho, esta metodologia foi aplicada a diversos tipos de PELBD obtidos utilizando-se diferentes tipos e teores de alfa-olefina, e diferentes sistemas catalíticos. A influência das condições experimentais sobre a eficiência do fracionamento também foi avaliada. A eficiência do fracionamento depende das temperaturas de cristalização e dos intervalos de temperaturas de cristalização utilizados, sendo que os tempos e as temperaturas e intervalos devem variar de acordo com a microestrutura do PELBD.Linear low-density polyethylenes (LLDPE are a class of polyethylenes with linear chains containing only short chain branches due to the insertion of alpha-olefin units during the
Quantifying the Stock of Soil Organic Carbon using Multiple ...
African Journals Online (AJOL)
The stepwise multiple regression model was employed to identify ecological variables that explained significant variation of carbon in fallow soils. Using fallow genealogical cycles of 1st, 2nd, 3rd, 4th and 5th generations, soil and vegetation variables from 30 sampling plots were collected and subjected to linear regression ...
quantifying the stock of soil organic carbon using multiple regression
African Journals Online (AJOL)
Osondu
2012-03-15
Mar 15, 2012 ... QUANTIFYING THE STOCK OF SOIL ORGANIC CARBON USING MULTIPLE REGRESSION MODEL. IN A FALLOW VEGETATION, ... plots were collected and subjected to linear regression analysis. The analysis generated three ... and soils are principal reservoirs of carbon, as they help to reduce the ...
Ghaedi, M; Rahimi, Mahmoud Reza; Ghaedi, A M; Tyagi, Inderjeet; Agarwal, Shilpi; Gupta, Vinod Kumar
2016-01-01
Two novel and eco friendly adsorbents namely tin oxide nanoparticles loaded on activated carbon (SnO2-NP-AC) and activated carbon prepared from wood tree Pistacia atlantica (AC-PAW) were used for the rapid removal and fast adsorption of methyl orange (MO) from the aqueous phase. The dependency of MO removal with various adsorption influential parameters was well modeled and optimized using multiple linear regressions (MLR) and least squares support vector regression (LSSVR). The optimal parameters for the LSSVR model were found based on γ value of 0.76 and σ(2) of 0.15. For testing the data set, the mean square error (MSE) values of 0.0010 and the coefficient of determination (R(2)) values of 0.976 were obtained for LSSVR model, and the MSE value of 0.0037 and the R(2) value of 0.897 were obtained for the MLR model. The adsorption equilibrium and kinetic data was found to be well fitted and in good agreement with Langmuir isotherm model and second-order equation and intra-particle diffusion models respectively. The small amount of the proposed SnO2-NP-AC and AC-PAW (0.015 g and 0.08 g) is applicable for successful rapid removal of methyl orange (>95%). The maximum adsorption capacity for SnO2-NP-AC and AC-PAW was 250 mg g(-1) and 125 mg g(-1) respectively. Copyright © 2015 Elsevier Inc. All rights reserved.
Hsu, Fong-Fu; Wohlmann, Jens; Turk, John; Haas, Albert
2011-12-01
The cell wall of the pathogenic bacterium Rhodococcus equi ( R. equi) contains abundant trehalose monomycolate (TMM) and trehalose dimycolate (TDM), the glycolipids bearing mycolic acids. Here, we describe multiple-stage (MS n ) linear ion-trap (LIT) mass spectrometric approaches toward structural characterization of TMM and TDM desorbed as [M + Alk]+ (Alk = Na, Li) and as [M + X]- (X = CH3CO2, HCO2) ions by electrospray ionization (ESI). Upon MS n ( n = 2, 3, 4) on the [M + Alk]+ or the [M + X]- adduct ions of TMM and TDM, abundant structurally informative fragment ions are readily available, permitting fast assignment of the length of the meromycolate chain and of the α-branch on the mycolyl residues. In this way, structures of TMM and TDM isolated from pathogenic R. equi strain 103 can be determined. Our results indicate that the major TMM and TDM molecules possess 6, and/or 6'-mycolyl groups that consist of mainly C14 and C16 α-branches with meromycolate branches ranging from C18 to C28, similar to the structures of the unbound mycolic acids found in the cell envelope. Up to 60 isobaric isomers varying in chain length of the α-branch and of the meromycolate backbone were observed for some of the TDM species in the mixture. This mass spectrometric approach provides a direct method that affords identification of various TMM and TDM isomers in a mixture of which the complexity of this lipid class has not been previously reported using other analytical methods.
Reciprocity in Linear Deterministic Networks under Linear Coding
Raja, Adnan; Viswanath, Pramod
2009-01-01
The linear deterministic model has been used recently to get a first order understanding of many wireless communication network problems. In many of these cases, it has been pointed out that the capacity regions of the network and its reciprocal (where the communication links are reversed and the roles of the sources and the destinations are swapped) are the same. In this paper, we consider a linear deterministic communication network with multiple unicast information flows. For this model and under the restriction to the class of linear coding, we show that the rate regions for a network and its reciprocal are the same. This can be viewed as a generalization of the linear reversibility of wireline networks, already known in the network coding literature.
DEFF Research Database (Denmark)
Lundgaard Andersen, Linda; Soldz, Stephen
2012-01-01
A major theme in recent psychoanalytic thinking concerns the use of therapist subjectivity, especially “countertransference,” in understanding patients. This thinking converges with and expands developments in qualitative research regarding the use of researcher subjectivity as a tool to understa...
Multiple modernities, modern subjectivities and social order
DEFF Research Database (Denmark)
Jung, Dietrich; Sinclair, Kirstine
2015-01-01
traditions. In the second part of the article we illustrate this argument with three short excursions into the history of Islamic reform in the 19th and 20th centuries. In this way we interpret the modern history of Muslim societies as based on cultural conflicts between different forms of social order...... of the 20th century....... and individual identities similar to those present in European history. Contrary to the European experience, however, religious traditions gradually assumed an important role in defining ‘authentic’ Muslim modernities, leading to a relatively hegemonic role of so-called Islamic modernities toward the end...
A subjective scheduler for subjective dedicated networks
Suherman; Fakhrizal, Said Reza; Al-Akaidi, Marwan
2017-09-01
Multiple access technique is one of important techniques within medium access layer in TCP/IP protocol stack. Each network technology implements the selected access method. Priority can be implemented in those methods to differentiate services. Some internet networks are dedicated for specific purpose. Education browsing or tutorial video accesses are preferred in a library hotspot, while entertainment and sport contents could be subjects of limitation. Current solution may use IP address filter or access list. This paper proposes subjective properties of users or applications are used for priority determination in multiple access techniques. The NS-2 simulator is employed to evaluate the method. A video surveillance network using WiMAX is chosen as the object. Subjective priority is implemented on WiMAX scheduler based on traffic properties. Three different traffic sources from monitoring video: palace, park, and market are evaluated. The proposed subjective scheduler prioritizes palace monitoring video that results better quality, xx dB than the later monitoring spots.
Introduction to linear elasticity
Gould, Phillip L
2013-01-01
Introduction to Linear Elasticity, 3rd Edition, provides an applications-oriented grounding in the tensor-based theory of elasticity for students in mechanical, civil, aeronautical, and biomedical engineering, as well as materials and earth science. The book is distinct from the traditional text aimed at graduate students in solid mechanics by introducing the subject at a level appropriate for advanced undergraduate and beginning graduate students. The author's presentation allows students to apply the basic notions of stress analysis and move on to advanced work in continuum mechanics, plasticity, plate and shell theory, composite materials, viscoelasticity and finite method analysis. This book also: Emphasizes tensor-based approach while still distilling down to explicit notation Provides introduction to theory of plates, theory of shells, wave propagation, viscoelasticity and plasticity accessible to advanced undergraduate students Appropriate for courses following emerging trend of teaching solid mechan...
MAGDM linear-programming models with distinct uncertain preference structures.
Xu, Zeshui S; Chen, Jian
2008-10-01
Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.
Bolton, W
1995-01-01
This book is concerned with linear equations and matrices, with emphasis on the solution of simultaneous linear equations. The solution of simultaneous linear equations is applied to electric circuit analysis and structural analysis.
Directory of Open Access Journals (Sweden)
Jing Zhao
Full Text Available The immune system plays a fundamental role in both the development and pathobiology of stroke. Inflammasomes are multiprotein complexes that have come to be recognized as critical players in the inflammation that ultimately contributes to stroke severity. Inflammasomes recognize microbial and host-derived danger signals and activate caspase-1, which in turn controls the production of the pro-inflammatory cytokine IL-1β. We have shown that A151, a synthetic oligodeoxynucleotide containing multiple telemeric TTAGGG motifs, reduces IL-1β production by activated bone marrow derived macrophages that have been subjected to oxygen-glucose deprivation and LPS stimulation. Further, we demonstrate that A151 reduces the maturation of caspase-1 and IL-1β, the levels of both the iNOS and NLRP3 proteins, and the depolarization of mitochondrial membrane potential within such cells. In addition, we have demonstrated that A151 reduces ischemic brain damage and NLRP3 mRNA levels in SHR-SP rats that have undergone permanent middle cerebral artery occlusion. These findings clearly suggest that the modulation of inflammasome activity via A151 may contribute to a reduction in pro-inflammatory cytokine production by macrophages subjected to conditions that model brain ischemia and modulate ischemic brain damage in an animal model of stroke. Therefore, modulation of ischemic pathobiology by A151 may have a role in the development of novel stroke prevention and therapeutic strategies.
Directory of Open Access Journals (Sweden)
Celsemy E. Maia
2001-04-01
Full Text Available Objetivou-se, com o presente trabalho, desenvolver uma metodologia para classificação da composição iônica da água de irrigação, através da regressão linear múltipla, tendo-se, como variável dependente, a condutividade elétrica e, como variáveis independentes, as concentrações de cátions e ânions da água de irrigação, classificada de acordo com o peso de cada íon no modelo estatístico. A fonte secundária de dados para a pesquisa foi o Banco de Dados do Laboratório de Análise de Água e Fertilidade do Solo, da Escola Superior de Agricultura de Mossoró (LAAFS/ESAM. As regressões foram ajustadas utilizando-se o método da seleção por etapas, conhecido como the stepwise regression procedure, no qual a variável dependente foi a condutividade elétrica e, como variáveis independentes, os íons determinados pela análise físico-química da água. Os resultados mostraram que, empregando-se este critério de regressão linear múltipla, havia variação na contribuição de cada variável no modelo ajustado, cuja estimativa era baseada no aumento da soma de quadrado, devido à regressão, a medida em que se incorporava, ao modelo, cada variável independente. Em função de critérios preestabelecidos, águas provenientes de mananciais da região da Chapada do Apodi foram classificadas como cálcica-sódica, cálcica e cloretada, quando provinham de poço tubular, de poço amazonas e rio, respectivamente. As águas oriundas da região do Baixo Açu, foram classificadas como sódica, magnesiana-sódica e sódica, para as águas de poço tubular, poço amazonas e rio, respectivamente.This work was conducted with the objective of developing a methodology for classification of the ionic composition of the irrigation water using multiple linear regression. A Stepwise Regression Analysis model was tested, using electrical conductivity as the dependent variable and analyzed ions calcium, sodium, potassium, carbonate, bicarbonate
The Use of Linear Programming for Prediction.
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)
Foundations of linear and generalized linear models
Agresti, Alan
2015-01-01
A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,
Indian Academy of Sciences (India)
Subject Index. Variation of surface electric field during geomagnetic disturbed period at Maitri, Antarctica. 1721. Geomorphology. A simple depression-filling method for raster and irregular elevation datasets. 1653. Decision Support System integrated with Geographic. Information System to target restoration actions in water-.
Multiple Perspectives / Multiple Readings
Directory of Open Access Journals (Sweden)
Simon Biggs
2005-01-01
Full Text Available People experience things from their own physical point of view. What they see is usually a function of where they are and what physical attitude they adopt relative to the subject. With augmented vision (periscopes, mirrors, remote cameras, etc we are able to see things from places where we are not present. With time-shifting technologies, such as the video recorder, we can also see things from the past; a time and a place we may never have visited.In recent artistic work I have been exploring the implications of digital technology, interactivity and internet connectivity that allow people to not so much space/time-shift their visual experience of things but rather see what happens when everybody is simultaneously able to see what everybody else can see. This is extrapolated through the remote networking of sites that are actual installation spaces; where the physical movements of viewers in the space generate multiple perspectives, linked to other similar sites at remote locations or to other viewers entering the shared data-space through a web based version of the work.This text explores the processes involved in such a practice and reflects on related questions regarding the non-singularity of being and the sense of self as linked to time and place.
Advanced linear algebra for engineers with Matlab
Dianat, Sohail A
2009-01-01
Matrices, Matrix Algebra, and Elementary Matrix OperationsBasic Concepts and NotationMatrix AlgebraElementary Row OperationsSolution of System of Linear EquationsMatrix PartitionsBlock MultiplicationInner, Outer, and Kronecker ProductsDeterminants, Matrix Inversion and Solutions to Systems of Linear EquationsDeterminant of a MatrixMatrix InversionSolution of Simultaneous Linear EquationsApplications: Circuit AnalysisHomogeneous Coordinates SystemRank, Nu
Directory of Open Access Journals (Sweden)
Nayla Luz Vacarezza
2012-12-01
Full Text Available Este artículo propone una interrogación acerca de los modos en que es posible continuar utilizando, con propósitos académicos y políticos, la categoría identitaria "mujeres" desde una perspectiva que recoja los aportes del pensamiento crítico de la modernidad, con énfasis en la teoría de la performatividad del género propuesta por Judith Butler y en la filosofía de la multiplicidad de Gilles Deleuze. En lugar de apelar a un reparto trascendente y binario de los géneros optamos por una forma ética de mantener la categoría radicalmente abierta. Seguir la pista de la vida social y temporal presente de la categoría permite hacer visible un campo múltiple de subjetividades sociales que se ofrecen a otros desde una posición de enunciación y existencia corporal como "mujer".This article posits an interrogation about the ways in which it is possible to keep using, for academic and political purposes, the category "women" from a perspective that collects the contributions of the gender performativity theory proposed by Judith Butler, and the philosophy of multiplicity by Gilles Deleuze. Instead of appealing to a transcendent and binary gender distribution, we opt for an ethical way of keeping the term "women" as a radically open category. Following the track of the present social life of the category gives visibility to a multiple field of social subjectivities which offer themselves to others from a position of enunciation and corporal existence as "woman".
On pole structure assignment in linear systems
Czech Academy of Sciences Publication Activity Database
Loiseau, J.-J.; Zagalak, Petr
2009-01-01
Roč. 82, č. 7 (2009), s. 1179-1192 ISSN 0020-7179 R&D Projects: GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : linear systems * linear state feedback * pole structure assignment Subject RIV: BC - Control Systems Theory Impact factor: 1.124, year: 2009 http://library.utia.cas.cz/separaty/2009/AS/zagalak-on pole structure assignment in linear systems.pdf
Darwish, Mona; Kirby, Mary; Hellriegel, Edward T
2009-01-01
Armodafinil, the R- and longer-lasting isomer of modafinil, may maintain higher plasma drug concentrations compared with racemic modafinil because of stereospecific differences in elimination of its isomers. This analysis set out to compare the steady-state pharmacokinetic profiles of armodafinil and modafinil on a milligram-to-milligram basis following once-daily administration. A post hoc analysis of two multiple-dose pharmacokinetic studies in healthy male subjects aged 18-50 years was conducted to compare dose-normalized (200 mg/day) plasma drug concentration and pharmacokinetic data for subjects in each study who completed 7 days of once-daily (morning) administration of armodafinil (n = 34) or modafinil (n = 18). Dose-normalized plasma concentrations of armodafinil on day 7 were higher than those of modafinil, with the greatest differences being observed later in the day. Across the 24-hour dose interval, plasma drug concentration fluctuation and swing were 28% and 42% less, respectively, with armodafinil than with modafinil. In addition, average late-day (3 pm to 7 pm after an 8 am dosing) plasma drug concentrations and partial values for the area under the plasma concentration versus time curve for 7-11 hours after dosing were both 44% higher with armodafinil. At steady state, armodafinil produces consistently higher plasma drug concentrations late in the day than modafinil when compared on a milligram-to-milligram basis. The distinct pharmacokinetic profile of armodafinil compared with that of the racemate may result in fundamentally different durations of action. These differences between the two medications cannot be made equivalent by increasing the dose of the racemate without introducing potential safety concerns.
Linear algebra and matrix analysis for statistics
Banerjee, Sudipto
2014-01-01
Matrices, Vectors, and Their OperationsBasic definitions and notations Matrix addition and scalar-matrix multiplication Matrix multiplication Partitioned matricesThe ""trace"" of a square matrix Some special matricesSystems of Linear EquationsIntroduction Gaussian elimination Gauss-Jordan elimination Elementary matrices Homogeneous linear systems The inverse of a matrixMore on Linear EquationsThe LU decompositionCrout's Algorithm LU decomposition with row interchanges The LDU and Cholesky factorizations Inverse of partitioned matrices The LDU decomposition for partitioned matricesThe Sherman-W
Optimal Changepoint Tests for Normal Linear Regression
Donald W.K. Andrews; Inpyo Lee; Werner Ploberger
1992-01-01
This paper determines a class of finite sample optimal tests for the existence of a changepoint at an unknown time in a normal linear multiple regression model with known variance. Optimal tests for multiple changepoints are also derived. Power comparisons of several tests are provided based on simulations.
Kim, Jeong-Soo; Kang, Sun-Young; Jeon, Hye-Seon
2015-01-01
The body-weight-support treadmill (BWST) is commonly used for gait rehabilitation, but other forms of BWST are in development, such as visual-deprivation BWST (VDBWST). In this study, we compare the effect of VDBWST training and conventional BWST training on spatiotemporal gait parameters for three individuals who had hemiparetic strokes. We used a single-subject experimental design, alternating multiple baselines across the individuals. We recruited three individuals with hemiparesis from stroke; two on the left side and one on the right. For the main outcome measures we assessed spatiotemporal gait parameters using GAITRite, including: gait velocity; cadence; step time of the affected side (STA); step time of the non-affected side (STN); step length of the affected side (SLA); step length of the non-affected side (SLN); step-time asymmetry (ST-asymmetry); and step-length asymmetry (SL-asymmetry). Gait velocity, cadence, SLA, and SLN increased from baseline after both interventions, but STA, ST-asymmetry, and SL-asymmetry decreased from the baseline after the interventions. The VDBWST was significantly more effective than the BWST for increasing gait velocity and cadence and for decreasing ST-asymmetry. VDBWST is more effective than BWST for improving gait performance during the rehabilitation for ground walking.
Tuey, R. C.
1972-01-01
Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.
Linearization of ancestral multichromosomal genomes.
Maňuch, Ján; Patterson, Murray; Wittler, Roland; Chauve, Cedric; Tannier, Eric
2012-01-01
Recovering the structure of ancestral genomes can be formalized in terms of properties of binary matrices such as the Consecutive-Ones Property (C1P). The Linearization Problem asks to extract, from a given binary matrix, a maximum weight subset of rows that satisfies such a property. This problem is in general intractable, and in particular if the ancestral genome is expected to contain only linear chromosomes or a unique circular chromosome. In the present work, we consider a relaxation of this problem, which allows ancestral genomes that can contain several chromosomes, each either linear or circular. We show that, when restricted to binary matrices of degree two, which correspond to adjacencies, the genomic characters used in most ancestral genome reconstruction methods, this relaxed version of the Linearization Problem is polynomially solvable using a reduction to a matching problem. This result holds in the more general case where columns have bounded multiplicity, which models possibly duplicated ancestral genes. We also prove that for matrices with rows of degrees 2 and 3, without multiplicity and without weights on the rows, the problem is NP-complete, thus tracing sharp tractability boundaries. As it happened for the breakpoint median problem, also used in ancestral genome reconstruction, relaxing the definition of a genome turns an intractable problem into a tractable one. The relaxation is adapted to some biological contexts, such as bacterial genomes with several replicons, possibly partially assembled. Algorithms can also be used as heuristics for hard variants. More generally, this work opens a way to better understand linearization results for ancestral genome structure inference.
Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.
1982-01-01
The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.
Linear algebra a first course with applications
Knop, Larry E
2008-01-01
Linear Algebra: A First Course with Applications explores the fundamental ideas of linear algebra, including vector spaces, subspaces, basis, span, linear independence, linear transformation, eigenvalues, and eigenvectors, as well as a variety of applications, from inventories to graphics to Google's PageRank. Unlike other texts on the subject, this classroom-tested book gives students enough time to absorb the material by focusing on vector spaces early on and using computational sections as numerical interludes. It offers introductions to Maple™, MATLAB®, and TI-83 Plus for calculating matri
Hagedorn, Peter
1982-01-01
Thoroughly revised and updated, the second edition of this concise text provides an engineer's view of non-linear oscillations, explaining the most important phenomena and solution methods. Non-linear descriptions are important because under certain conditions there occur large deviations from the behaviors predicted by linear differential equations. In some cases, completely new phenomena arise that are not possible in purely linear systems. The theory of non-linear oscillations thus has important applications in classical mechanics, electronics, communications, biology, and many other branches of science. In addition to many other changes, this edition has a new section on bifurcation theory, including Hopf's theorem.
Parametrices and exact paralinearization of semi-linear boundary problems
DEFF Research Database (Denmark)
Johnsen, Jon
2008-01-01
The subject is parametrices for semi-linear problems, based on parametrices for linear boundary problems and on non-linearities that decompose into solution-dependent linear operators acting on the solutions. Non-linearities of product type are shown to admit this via exact paralinearization. The...... of homogeneous distributions, tensor products and halfspace extensions have been revised. Examples include the von Karman equation....
Tonn, George R; Wong, Simon G; Wong, Sylvia C; Johnson, Michael G; Ma, Ji; Cho, Robert; Floren, Leslie C; Kersey, Kathryn; Berry, Karen; Marcus, Andrew P; Wang, Xuemei; Van Lengerich, Bettina; Medina, Julio C; Pearson, Paul G; Wong, Bradley K
2009-03-01
(R)-N-{1-[3-(4-Ethoxy-phenyl)-4-oxo-3,4-dihydro-pyrido[2,3-d]-pyrimidin-2-yl]-ethyl}-N-pyridin-3-yl-methyl-2-(4-trifluoromethoxyphenyl)-acetamide (AMG 487) is a potent and selective orally bioavailable chemokine (C-X-C motif) receptor 3 (CXCR3) antagonist that displays dose- and time-dependent pharmacokinetics in human subjects after multiple oral dosing. Although AMG 487 exhibited linear pharmacokinetics on both days 1 and 7 at the 25-mg dose, dose- and time-dependent kinetics were evident at the two higher doses. Nonlinear kinetics were more pronounced after multiple dosing. Area under the plasma concentration-time curve from 0 to 24 h [AUC((0-24 h))] increased 96-fold with a 10-fold increase in dose on day 7 compared with a 28-fold increase in AUC((0-24 h)) on day 1. These changes were correlated with time- and dose-dependent decreases in the metabolite to parent plasma concentrations, suggesting that these changes result from a decrease in the oral clearance (CL) of AMG 487 (e.g., intestinal/hepatic first-pass metabolism and systemic CL). The biotransformation of AMG 487 is dependent on CYP3A and results in the formation of two primary metabolites, a pyridyl N-oxide AMG 487 (M1) and an O-deethylated AMG 487 (M2). One of these metabolites, M2, undergoes further metabolism by CYP3A. M2 has also been demonstrated to inhibit CYP3A in a competitive (K(i)=0.75 microM) manner as well as via mechanism-based inhibition (unbound K(I)=1.4 microM, k(inact)=0.041 min(-1)). Data from this study implicate M2-mediated CYP3A mechanism-based inhibition as the proximal cause for the time-dependent pharmacokinetics of AMG 487. However, the sequential metabolism of M2, nonlinear AMG 487 pharmacokinetics, and the inability to accurately determine the role of intestinal AMG 487 metabolism complicates the correlation between M2 plasma concentrations and the time-dependent AMG 487 pharmacokinetic changes.
... multiple pregnancy affect fetal growth? Are tests for genetic disorders as accurate in multiple pregnancies? How can multiple pregnancy affect delivery? Can multiple pregnancy affect my risk of postpartum depression? Can I breastfeed if I have multiples? Glossary ...
Blyth, T S
2002-01-01
Basic Linear Algebra is a text for first year students leading from concrete examples to abstract theorems, via tutorial-type exercises. More exercises (of the kind a student may expect in examination papers) are grouped at the end of each section. The book covers the most important basics of any first course on linear algebra, explaining the algebra of matrices with applications to analytic geometry, systems of linear equations, difference equations and complex numbers. Linear equations are treated via Hermite normal forms which provides a successful and concrete explanation of the notion of linear independence. Another important highlight is the connection between linear mappings and matrices leading to the change of basis theorem which opens the door to the notion of similarity. This new and revised edition features additional exercises and coverage of Cramer's rule (omitted from the first edition). However, it is the new, extra chapter on computer assistance that will be of particular interest to readers:...
Linearity in Process Languages
DEFF Research Database (Denmark)
Nygaard, Mikkel; Winskel, Glynn
2002-01-01
The meaning and mathematical consequences of linearity (managing without a presumed ability to copy) are studied for a path-based model of processes which is also a model of affine-linear logic. This connection yields an affine-linear language for processes, automatically respecting open-map bisi......The meaning and mathematical consequences of linearity (managing without a presumed ability to copy) are studied for a path-based model of processes which is also a model of affine-linear logic. This connection yields an affine-linear language for processes, automatically respecting open......-map bisimulation, in which a range of process operations can be expressed. An operational semantics is provided for the tensor fragment of the language. Different ways to make assemblies of processes lead to different choices of exponential, some of which respect bisimulation....
Energy Technology Data Exchange (ETDEWEB)
Wiedemann, H.
1981-11-01
Since no linear colliders have been built yet it is difficult to know at what energy the linear cost scaling of linear colliders drops below the quadratic scaling of storage rings. There is, however, no doubt that a linear collider facility for a center of mass energy above say 500 GeV is significantly cheaper than an equivalent storage ring. In order to make the linear collider principle feasible at very high energies a number of problems have to be solved. There are two kinds of problems: one which is related to the feasibility of the principle and the other kind of problems is associated with minimizing the cost of constructing and operating such a facility. This lecture series describes the problems and possible solutions. Since the real test of a principle requires the construction of a prototype I will in the last chapter describe the SLC project at the Stanford Linear Accelerator Center.
Multiple sclerosis; Multiple Sklerose
Energy Technology Data Exchange (ETDEWEB)
Grunwald, I.Q.; Kuehn, A.L.; Backens, M.; Papanagiotou, P. [Universitaet des Saarlandes, Abteilung fuer Diagnostische und Interventionelle Neuroradiologie, Radiologische Klinik, Homburg/Saar (Germany); Shariat, K. [Universitaet des Saarlandes, Klinik fuer Neurochirurgie, Homburg/Saar (Germany); Kostopoulos, P. [Universitaet des Saarlandes, Klinik fuer Neurologie, Homburg/Saar (Germany)
2008-06-15
Multiple sclerosis is the most common chronic inflammatory disease of myelin with interspersed lesions in the white matter of the central nervous system. Magnetic resonance imaging (MRI) plays a key role in the diagnosis and monitoring of white matter diseases. This article focuses on key findings in multiple sclerosis as detected by MRI. (orig.) [German] Die Multiple Sklerose (MS) ist die haeufigste chronisch-entzuendliche Erkrankung des Myelins mit eingesprengten Laesionen im Bereich der weissen Substanz des zentralen Nervensystems. Die Magnetresonanztomographie (MRT) hat bei der Diagnosestellung und Verlaufskontrolle eine Schluesselrolle. Dieser Artikel befasst sich mit Hauptcharakteristika der MR-Bildbebung. (orig.)
Efficient Non Linear Loudspeakers
DEFF Research Database (Denmark)
Petersen, Bo R.; Agerkvist, Finn T.
2006-01-01
Loudspeakers have traditionally been designed to be as linear as possible. However, as techniques for compensating non linearities are emerging, it becomes possible to use other design criteria. This paper present and examines a new idea for improving the efficiency of loudspeakers at high levels...... by changing the voice coil layout. This deliberate non-linear design has the benefit that a smaller amplifier can be used, which has the benefit of reducing system cost as well as reducing power consumption....
Carr, Joseph
1996-01-01
The linear IC market is large and growing, as is the demand for well trained technicians and engineers who understand how these devices work and how to apply them. Linear Integrated Circuits provides in-depth coverage of the devices and their operation, but not at the expense of practical applications in which linear devices figure prominently. This book is written for a wide readership from FE and first degree students, to hobbyists and professionals.Chapter 1 offers a general introduction that will provide students with the foundations of linear IC technology. From chapter 2 onwa
Faraway, Julian J
2014-01-01
A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.New to the Second EditionReorganiz