Single- and multiple-dose pharmacokinetics, pharmacodynamics, and safety of apixaban in healthy Chinese subjects

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

Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

International Nuclear Information System (INIS)

Bao Min; Shi Quanlin; Zhang Jiamei

2004-01-01

This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

The Core Problem within a Linear Approximation Problem $AX/approx B$ with Multiple Right-Hand Sides

Czech Academy of Sciences Publication Activity Database

Hnětynková, Iveta; Plešinger, Martin; Strakoš, Z.

2013-01-01

Roč. 34, č. 3 (2013), s. 917-931 ISSN 0895-4798 R&D Projects: GA ČR GA13-06684S Grant - others:GA ČR(CZ) GA201/09/0917; GA MŠk(CZ) EE2.3.09.0155; GA MŠk(CZ) EE2.3.30.0065 Program:GA Institutional support: RVO:67985807 Keywords : total least squares problem * multiple right-hand sides * core problem * linear approximation problem * error-in-variables modeling * orthogonal regression * singular value decomposition Subject RIV: BA - General Mathematics Impact factor: 1.806, year: 2013

Direction of Effects in Multiple Linear Regression Models.

Science.gov (United States)

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.

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.

Pharmacokinetics and Safety of Intravenous Murepavadin Infusion in Healthy Adult Subjects Administered Single and Multiple Ascending Doses.

Science.gov (United States)

Wach, Achim; Dembowsky, Klaus; Dale, Glenn E

2018-04-01

Murepavadin is the first in class of the outer membrane protein-targeting antibiotics (OMPTA) and a pathogen-specific peptidomimetic antibacterial with a novel, nonlytic mechanism of action targeting Pseudomonas aeruginosa Murepavadin is being developed for the treatment of hospital-acquired bacterial pneumonia (HABP) and ventilator-associated bacterial pneumonia (VABP). The pharmacokinetics (PK) and safety of single and multiple doses of murepavadin were investigated in healthy male subjects. Part A of the study was a double-blind, randomized, placebo-controlled, single-ascending-dose investigation in 10 sequential cohorts where each cohort comprised 6 healthy male subjects; 4 subjects were randomized to murepavadin, and 2 subjects were randomized to placebo. Part B was a double-blind, randomized, placebo-controlled, multiple-ascending-dose investigation in 3 sequential cohorts. After a single dose of murepavadin, the geometric mean half-life (2.52 to 5.30 h), the total clearance (80.1 to 114 ml/h/kg), and the volume of distribution (415 to 724 ml/kg) were consistent across dose levels. The pharmacokinetics of the dosing regimens evaluated were dose proportional and linear. Murepavadin was well tolerated, adverse events were transient and generally mild, and no dose-limiting toxicity was identified. Copyright © 2018 American Society for Microbiology.

Maximising water supply system yield subject to multiple reliability ...

African Journals Online (AJOL)

Maximising water supply system yield subject to multiple reliability constraints via simulation-optimisation. ... Water supply systems have to satisfy different demands that each require various levels of reliability ... and monthly operating rules that maximise the yield of a water supply system subject to ... HOW TO USE AJOL.

Seismic analysis of piping systems subjected to multiple support excitations

International Nuclear Information System (INIS)

Sundararajan, C.; Vaish, A.K.; Slagis, G.C.

1981-01-01

The paper presents the results of a comparative study between the multiple response spectrum method and the time-history method for the seismic analysis of nuclear piping systems subjected to different excitation at different supports or support groups. First, the necessary equations for the above analysis procedures are derived. Then, three actual nuclear piping systems subjected to single and multiple excitations are analyzed by the different methods, and extensive comparisons of the results (stresses) are made. Based on the results, it is concluded that the multiple response spectrum analysis gives acceptable results as compared to the ''exact'', but much more costly, time-history analysis. 6 refs

Non-linear self-reinforced growth of tearing modes with multiple rational surfaces

International Nuclear Information System (INIS)

Maschke, E.K.; Persson, M.; Dewar, R.L.; Australian National Univ., Canberra, ACT

1993-06-01

The non-linear evolution of tearing modes with multiple rational surfaces is discussed. It is demonstrated that, in the presence of small differential rotation, the non-linear growth might be faster than exponential. This growth occurs as the rotation frequencies of the plasma at the different rational surfaces go into equilibrium

Multi-objective optimization of linear multi-state multiple sliding window system

International Nuclear Information System (INIS)

Konak, Abdullah; Kulturel-Konak, Sadan; Levitin, Gregory

2012-01-01

This paper considers the optimal element sequencing in a linear multi-state multiple sliding window system that consists of n linearly ordered multi-state elements. Each multi-state element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The failure of type i in the system occurs if for any i (1≤i≤I) the cumulative performance of any r i consecutive elements is lower than w i . The element sequence strongly affects the probability of any type of system failure. The sequence that minimizes the probability of certain type of failure can provide high probability of other types of failures. Therefore the optimization problem for the multiple sliding window system is essentially multi-objective. The paper formulates and solves the multi-objective optimization problem for the multiple sliding window systems. A multi-objective Genetic Algorithm is used as the optimization engine. Illustrative examples are presented.

The linearized inversion of the generalized interferometric multiple imaging

KAUST Repository

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.

The number of subjects per variable required in linear regression analyses

NARCIS (Netherlands)

P.C. Austin (Peter); E.W. Steyerberg (Ewout)

2015-01-01

textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

Optimized multiple linear mappings for single image super-resolution

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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.

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 ...

'Normal' and 'failing' mothers: Women's constructions of maternal subjectivity while living with multiple sclerosis.

Science.gov (United States)

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.

Brain-heart linear and nonlinear dynamics during visual emotional elicitation in healthy subjects.

Science.gov (United States)

Valenza, G; Greco, A; Gentili, C; Lanata, A; Toschi, N; Barbieri, R; Sebastiani, L; Menicucci, D; Gemignani, A; Scilingo, E P

2016-08-01

This study investigates brain-heart dynamics during visual emotional elicitation in healthy subjects through linear and nonlinear coupling measures of EEG spectrogram and instantaneous heart rate estimates. To this extent, affective pictures including different combinations of arousal and valence levels, gathered from the International Affective Picture System, were administered to twenty-two healthy subjects. Time-varying maps of cortical activation were obtained through EEG spectral analysis, whereas the associated instantaneous heartbeat dynamics was estimated using inhomogeneous point-process linear models. Brain-Heart linear and nonlinear coupling was estimated through the Maximal Information Coefficient (MIC), considering EEG time-varying spectra and point-process estimates defined in the time and frequency domains. As a proof of concept, we here show preliminary results considering EEG oscillations in the θ band (4-8 Hz). This band, indeed, is known in the literature to be involved in emotional processes. MIC highlighted significant arousal-dependent changes, mediated by the prefrontal cortex interplay especially occurring at intermediate arousing levels. Furthermore, lower and higher arousing elicitations were associated to not significant brain-heart coupling changes in response to pleasant/unpleasant elicitations.

Inference regarding multiple structural changes in linear models with endogenous regressors

NARCIS (Netherlands)

Boldea, O.; Hall, A.R.; Han, S.

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

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...

Multiple modernities, modern subjectivities and social order

DEFF Research Database (Denmark)

Jung, Dietrich; Sinclair, Kirstine

2015-01-01

to modern subjectivity formation. In combining conceptual tools from these strands of social theory, we argue that the emergence of multiple modernities should be understood as a historical result of idiosyncratic social constructions combining global social imaginaries with religious and other cultural......Taking its point of departure in the conceptual debate about modernities in the plural, this article presents a heuristic framework based on an interpretative approach to modernity. The article draws on theories of multiple modernities, successive modernities and poststructuralist approaches...... 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...

Seismic response analysis of structural system subjected to multiple support excitation

International Nuclear Information System (INIS)

Wu, R.W.; Hussain, F.A.; Liu, L.K.

1978-01-01

In the seismic analysis of a multiply supported structural system subjected to nonuniform excitations at each support point, the single response spectrum, the time history, and the multiple response spectrum are the three commonly employed methods. In the present paper the three methods are developed, evaluated, and the limitations and advantages of each method assessed. A numerical example has been carried out for a typical piping system. Considerably smaller responses have been predicted by the time history method than that by the single response spectrum method. This is mainly due to the fact that the phase and amplitude relations between the support excitations are faithfully retained in the time history method. The multiple response spectrum prediction has been observed to compare favourably with the time history method prediction. Based on the present evaluation, the multiple response spectrum method is the most efficient method for seismic response analysis of structural systems subjected to multiple support excitation. (Auth.)

COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

Directory of Open Access Journals (Sweden)

K. Seetharaman

2015-08-01

Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

Output feedback control of linear fractional transformation systems subject to actuator saturation

Science.gov (United States)

Ban, Xiaojun; Wu, Fen

2016-11-01

In this paper, the control problem for a class of linear parameter varying (LPV) plant subject to actuator saturation is investigated. For the saturated LPV plant depending on the scheduling parameters in linear fractional transformation (LFT) fashion, a gain-scheduled output feedback controller in the LFT form is designed to guarantee the stability of the closed-loop LPV system and provide optimised disturbance/error attenuation performance. By using the congruent transformation, the synthesis condition is formulated as a convex optimisation problem in terms of a finite number of LMIs for which efficient optimisation techniques are available. The nonlinear inverted pendulum problem is employed to demonstrate the effectiveness of the proposed approach. Moreover, the comparison between our LPV saturated approach with an existing linear saturated method reveals the advantage of the LPV controller when handling nonlinear plants.

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

Science.gov (United States)

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.

Multiple linear B-cell epitopes of classical swine fever virus glycoprotein E2 expressed in E.coli as multiple epitope vaccine induces a protective immune response

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.

Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

Directory of Open Access Journals (Sweden)

Tae-Hyoung Kim

2017-01-01

Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Enteric-Coated Mycophenolate Sodium in Adult Kidney Transplant Recipients.

Science.gov (United States)

Brooks, Emily K; Tett, Susan E; Isbel, Nicole M; McWhinney, Brett; Staatz, Christine E

2018-04-01

Although multiple linear regression-based limited sampling strategies (LSSs) have been published for enteric-coated mycophenolate sodium, 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 20 adult renal transplant patients on 2 occasions a week apart. All subjects received concomitant tacrolimus and were approximately 1 month after 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 after dose on the first and second sampling occasion, respectively. Predicted MPA AUC0-12 was calculated using 19 published LSSs and data from the first or second sampling occasion for each patient and compared with the second occasion full MPA AUC0-12 calculated using the linear trapezoidal rule. Bias (median percentage prediction error) and imprecision (median absolute prediction error) were determined. Median percentage prediction error and median absolute prediction error 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.

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

Science.gov (United States)

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…

A scalable parallel algorithm for multiple objective linear programs

Science.gov (United States)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

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

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

Science.gov (United States)

Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions

KAUST Repository

Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem

2017-01-01

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

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Science.gov (United States)

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Generalized linear longitudinal mixed models with linear covariance structure and multiplicative random effects

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....

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

Science.gov (United States)

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

2006-01-01

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

A note on the use of multiple linear regression in molecular ecology.

Science.gov (United States)

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.

Research on the multiple linear regression in non-invasive blood glucose measurement.

Science.gov (United States)

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.

Modeling coupled bending, axial, and torsional vibrations of a CANDU fuel rod subjected to multiple frictional contact constraints

International Nuclear Information System (INIS)

Fadaee, M.; Yu, S.D.

2013-01-01

In this paper, a finite element based dynamic model is presented for bending, axial, and torsional vibrations of an outer CANDU fuel element subjected to multiple unilateral frictional contact (MUFC) constraints. The Bozzak-Newmark relaxation-integration scheme is used to discretize the equations of motion in the time domain. At a time step, equations of state of the fuel element with MUFC constraints reduce to a linear complementarity problem (LCP). Results are compared with those available in the literature. Good agreement is achieved. The 2D sliding and stiction motion of a fuel element at points of contact is obtained for harmonic excitations. (author)

Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression

KAUST Repository

Abdul Jameel, Abdul Gani; Naser, Nimal; Emwas, Abdul-Hamid M.; Dooley, Stephen; Sarathy, Mani

2016-01-01

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

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.

Error analysis of dimensionless scaling experiments with multiple points using linear regression

International Nuclear Information System (INIS)

Guercan, Oe.D.; Vermare, L.; Hennequin, P.; Bourdelle, C.

2010-01-01

A general method of error estimation in the case of multiple point dimensionless scaling experiments, using linear regression and standard error propagation, is proposed. The method reduces to the previous result of Cordey (2009 Nucl. Fusion 49 052001) in the case of a two-point scan. On the other hand, if the points follow a linear trend, it explains how the estimated error decreases as more points are added to the scan. Based on the analytical expression that is derived, it is argued that for a low number of points, adding points to the ends of the scanned range, rather than the middle, results in a smaller error estimate. (letter)

Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.

Directory of Open Access Journals (Sweden)

Radek Matušů

Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.

A method for computing the stationary points of a function subject to linear equality constraints

International Nuclear Information System (INIS)

Uko, U.L.

1989-09-01

We give a new method for the numerical calculation of stationary points of a function when it is subject to equality constraints. An application to the solution of linear equations is given, together with a numerical example. (author). 5 refs

Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

Science.gov (United States)

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.

Classification Systems for Individual Differences in Multiple-task Performance and Subjective Estimates of Workload

Science.gov (United States)

Damos, D. L.

1984-01-01

Human factors practitioners often are concerned with mental workload in multiple-task situations. Investigations of these situations have demonstrated repeatedly that individuals differ in their subjective estimates of workload. These differences may be attributed in part to individual differences in definitions of workload. However, after allowing for differences in the definition of workload, there are still unexplained individual differences in workload ratings. The relation between individual differences in multiple-task performance, subjective estimates of workload, information processing abilities, and the Type A personality trait were examined.

Relationships between each part of the spinal curves and upright posture using Multiple stepwise linear regression analysis.

Science.gov (United States)

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.

A one-layer recurrent neural network for non-smooth convex optimization subject to linear inequality constraints

International Nuclear Information System (INIS)

Liu, Xiaolan; Zhou, Mi

2016-01-01

In this paper, a one-layer recurrent network is proposed for solving a non-smooth convex optimization subject to linear inequality constraints. Compared with the existing neural networks for optimization, the proposed neural network is capable of solving more general convex optimization with linear inequality constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds.

MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY

OpenAIRE

Chayalakshmi C.L

2018-01-01

MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY ABSTRACT Calculation of boiler efficiency is essential if its parameters need to be controlled for either maintaining or enhancing its efficiency. But determination of boiler efficiency using conventional method is time consuming and very expensive. Hence, it is not recommended to find boiler efficiency frequently. The work presented in this paper deals with establishing the statistical mo...

Inverse chaos synchronization in linearly and nonlinearly coupled systems with multiple time-delays

International Nuclear Information System (INIS)

Shahverdiev, E.M.; Hashimov, R.H.; Nuriev, R.A.; Hashimova, L.H.; Huseynova, E.M.; Shore, K.A.

2005-04-01

We report on inverse chaos synchronization between two unidirectionally linearly and nonlinearly coupled chaotic systems with multiple time-delays and find the existence and stability conditions for different synchronization regimes. We also study the effect of parameter mismatches on synchonization regimes. The method is tested on the famous Ikeda model. Numerical simulations fully support the analytical approach. (author)

An improved multiple linear regression and data analysis computer program package

Science.gov (United States)

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.

Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression

Directory of Open Access Journals (Sweden)

Maokuan Zheng

2017-01-01

Full Text Available The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2. The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.

Waste management under multiple complexities: Inexact piecewise-linearization-based fuzzy flexible programming

International Nuclear Information System (INIS)

Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen

2012-01-01

Highlights: ► Inexact piecewise-linearization-based fuzzy flexible programming is proposed. ► It’s the first application to waste management under multiple complexities. ► It tackles nonlinear economies-of-scale effects in interval-parameter constraints. ► It estimates costs more accurately than the linear-regression-based model. ► Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: 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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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…

The linear attenuation coefficients as features of multiple energy CT image classification

International Nuclear Information System (INIS)

Homem, M.R.P.; Mascarenhas, N.D.A.; Cruvinel, P.E.

2000-01-01

We present in this paper an analysis of the linear attenuation coefficients as useful features of single and multiple energy CT images with the use of statistical pattern classification tools. We analyzed four CT images through two pointwise classifiers (the first classifier is based on the maximum-likelihood criterion and the second classifier is based on the k-means clustering algorithm) and one contextual Bayesian classifier (ICM algorithm - Iterated Conditional Modes) using an a priori Potts-Strauss model. A feature extraction procedure using the Jeffries-Matusita (J-M) distance and the Karhunen-Loeve transformation was also performed. Both the classification and the feature selection procedures were found to be in agreement with the predicted discrimination given by the separation of the linear attenuation coefficient curves for different materials

The number of subjects per variable required in linear regression analyses.

Science.gov (United States)

Austin, Peter C; Steyerberg, Ewout W

2015-06-01

To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.)

Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure.

Science.gov (United States)

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.

Multiple nucleon transfer in damped nuclear collisions. [Lectures, mass charge, and linear and angular momentum transport

Energy Technology Data Exchange (ETDEWEB)

Randrup, J.

1979-07-01

This lecture discusses a theory for the transport of mass, charge, linear, and angular momentum and energy in damped nuclear collisions, as induced by multiple transfer of individual nucleons. 11 references.

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

Science.gov (United States)

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

Behavior of mixed-oxide fuel subjected to multiple thermal transients

International Nuclear Information System (INIS)

Fenske, G.R.; Hofman, G.L.; Neimark, L.A.; Poeppel, R.B.

1983-11-01

The microstructural behavior of irradiated mixed-oxide fuel subjected to multiple, mild thermal transients was investigated using direct electrical heating. The results demonstrate that significant intergranular porosity, accompanied by large-scale (>90%) release of the retained fission gas, developed as a result of the cyclic heating. Microstructural examination of the fuel indicated that thermal-shock-induced cracking of the fuel contributed significantly to the increased swelling and gas release

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

Science.gov (United States)

Xu, Xueli; von Davier, Matthias

2008-01-01

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

Behavior of mixed-oxide fuel subjected to multiple thermal transients

International Nuclear Information System (INIS)

Fenske, G.R.; Neimark, L.A.; Poeppel, R.B.; Hofman, G.L.

1985-01-01

The microstructural behavior of irradiated mixed-oxide fuel subjected to multiple, mild thermal transients was investigated using direct electrical heating. The results demonstrate that significant intergranular porosity, accompanied by large-scale (>90%) release of the retained fission gas, developed as a result of the cyclic heating. Microstructural examination of the fuel indicated that thermal-shock-induced cracking of the fuel contributed significantly to the increased swelling and gas release. 29 refs., 12 figs

Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

Science.gov (United States)

Furlotte, Nicholas A; Eskin, Eleazar

2015-05-01

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.

Science.gov (United States)

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.

Confirmatory Factor Analysis and Multiple Linear Regression of the Neck Disability Index: Assessment If Subscales Are Equally Relevant in Whiplash and Nonspecific Neck Pain.

Science.gov (United States)

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 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.

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

Science.gov (United States)

Marill, Keith A

2004-01-01

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

Internal correction of spectral interferences and mass bias for selenium metabolism studies using enriched stable isotopes in combination with multiple linear regression.

Science.gov (United States)

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

Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

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.

Inference regarding multiple structural changes in linear models with endogenous regressors☆

Science.gov (United States)

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

Use of probabilistic weights to enhance linear regression myoelectric control.

Science.gov (United States)

Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

2015-12-01

Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Vibration control of bridge subjected to multi-axle vehicle using multiple tuned mass friction dampers

Science.gov (United States)

Pisal, Alka Y.; Jangid, R. S.

2016-06-01

The effectiveness of tuned mass friction damper (TMFD) in reducing undesirable resonant response of the bridge subjected to multi-axle vehicular load is investigated. A Taiwan high-speed railway (THSR) bridge subjected to Japanese SKS (Salkesa) train load is considered. The bridge is idealized as a simply supported Euler-Bernoulli beam with uniform properties throughout the length of the bridge, and the train's vehicular load is modeled as a series of moving forces. Simplified model of vehicle, bridge and TMFD system has been considered to derive coupled differential equations of motion which is solved numerically using the Newmark's linear acceleration method. The critical train velocities at which the bridge undergoes resonant vibration are investigated. Response of the bridge is studied for three different arrangements of TMFD systems, namely, TMFD attached at mid-span of the bridge, multiple tuned mass friction dampers (MTMFD) system concentrated at mid-span of the bridge and MTMFD system with distributed TMFD units along the length of the bridge. The optimum parameters of each TMFD system are found out. It has been demonstrated that an optimized MTMFD system concentrated at mid-span of the bridge is more effective than an optimized TMFD at the same place with the same total mass and an optimized MTMFD system having TMFD units distributed along the length of the bridge. However, the distributed MTMFD system is more effective than an optimized TMFD system, provided that TMFD units of MTMFD system are distributed within certain limiting interval and the frequency of TMFD units is appropriately distributed.

Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

Science.gov (United States)

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.

Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions

KAUST Repository

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.

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.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

Science.gov (United States)

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

Analysis of oil-pipeline distribution of multiple products subject to delivery time-windows

Science.gov (United States)

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

Calculation of U, Ra, Th and K contents in uranium ore by multiple linear regression method

International Nuclear Information System (INIS)

Lin Chao; Chen Yingqiang; Zhang Qingwen; Tan Fuwen; Peng Guanghui

1991-01-01

A multiple linear regression method was used to compute γ spectra of uranium ore samples and to calculate contents of U, Ra, Th, and K. In comparison with the inverse matrix method, its advantage is that no standard samples of pure U, Ra, Th and K are needed for obtaining response coefficients

The headache to subjects with multiple sclerosis: clinical and imaging study

International Nuclear Information System (INIS)

Moldovanu, Ion; Voiticovschi-Iosob, Cristina

2011-01-01

The present study showed clinical and imaging particularities of primary headache to subjects with multiple sclerosis. From the total number of 28 patients included in this study 22 (78,57%) had headache accuses (3 men and 19 women). Was observed a high prevalence of tension type headache, present to 10 of the 22 patients (45.45%). Migraine was diagnosed to 8 respondents (36.36 %). In 4 cases was found a combination of migraine and tension type headache (8.1%). Headache was more common to women with multiple sclerosis (MS) than to men. Neuroimaging of MS patients indicates the fact that the presence of demyelinating disease in the brainstem, midbrain, periaqueductal gray substance is associated with an increased risk of headache, migraine characteristics (migraine-like). Psychometric test have revealed a high level of depression and anxiety in patients with MS and chronic headache. (authors)

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

Science.gov (United States)

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.

Linear mixed-effects modeling approach to FMRI group analysis.

Science.gov (United States)

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity

Multiplicity of Solutions for a Class of Fourth-Order Elliptic Problems with Asymptotically Linear Term

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.

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

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.

Computing multiple-output regression quantile regions

Czech Academy of Sciences Publication Activity Database

Paindaveine, D.; Šiman, Miroslav

2012-01-01

Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple-output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf

Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

Science.gov (United States)

Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

2018-01-01

Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg

Cerebral blood flow and red cell delivery in normal subjects and in multiple sclerosis

International Nuclear Information System (INIS)

Swank, R.L.; Roth, J.G.; Woody, D.C. Jr.

1983-01-01

Regional cerebral blood flow (rCBF) was determined in 77 normal females and 53 normal males of different ages and in 26 men and 45 women with multiple sclerosis by the inhalation of radioactive Xe133 method. In the normal subjects the CBF was relatively high in the teens and fell, at first rapidly and then slowly in both sexes with age. During adult life the flow in females was significantly higher than in males. The delivery of packed red cells (RCD) was determined by multiplying the CBF by the percentage concentration of red cells (HCT). The RCD for both sexes was nearly the same. In the patients with multiple sclerosis there occurred a progressive generalized decrease in CBF and in RCD with age which was significantly greater than observed in normal subjects. The rate of decrease in CBF and RCD correlated directly with the rate of progress of the disease

Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming.

Science.gov (United States)

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.

[Multiple linear regression analysis of X-ray measurement and WOMAC scores of knee osteoarthritis].

Science.gov (United States)

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.

Computational linear and commutative algebra

CERN Document Server

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...

Multiple Intelligences, Motivations and Learning Experience Regarding Video-Assisted Subjects in a Rural University

Science.gov (United States)

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…

Approximate Forward Difference Equations for the Lower Order Non-Stationary Statistics of Geometrically Non-Linear Systems subject to Random Excitation

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....

Non-Linear Structural Dynamics Characterization using a Scanning Laser Vibrometer

Science.gov (United States)

Pai, P. F.; Lee, S.-Y.

2003-01-01

This paper presents the use of a scanning laser vibrometer and a signal decomposition method to characterize non-linear dynamics of highly flexible structures. A Polytec PI PSV-200 scanning laser vibrometer is used to measure transverse velocities of points on a structure subjected to a harmonic excitation. Velocity profiles at different times are constructed using the measured velocities, and then each velocity profile is decomposed using the first four linear mode shapes and a least-squares curve-fitting method. From the variations of the obtained modal \\ielocities with time we search for possible non-linear phenomena. A cantilevered titanium alloy beam subjected to harmonic base-excitations around the second. third, and fourth natural frequencies are examined in detail. Influences of the fixture mass. gravity. mass centers of mode shapes. and non-linearities are evaluated. Geometrically exact equations governing the planar, harmonic large-amplitude vibrations of beams are solved for operational deflection shapes using the multiple shooting method. Experimental results show the existence of 1:3 and 1:2:3 external and internal resonances. energy transfer from high-frequency modes to the first mode. and amplitude- and phase- modulation among several modes. Moreover, the existence of non-linear normal modes is found to be questionable.

QSAR models for prediction study of HIV protease inhibitors using support vector machines, neural networks and multiple linear regression

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.

Study of optical non-linear properties of a constant total effective length multiple quantum wells system

International Nuclear Information System (INIS)

Solaimani, M.; Morteza, Izadifard; Arabshahi, H.; Reza, Sarkardehi Mohammad

2013-01-01

In this work, we have studied the effect of the number of the wells, in a multiple quantum wells structure with constant total effective length, on the optical properties of multiple quantum wells like the absorption coefficient and the refractive index by means of compact density matrix approach. GaAs/Al x Ga (1−x) As multiple quantum wells systems was selected as an example. Besides, the effect of varying number of wells on the subband energies, wave functions, number of bound states, and the Fermi energy have been also investigated. Our calculation revealed that the number of wells in a multiple quantum well is a criterion with which we can control the amount of nonlinearity. This study showed that for the third order refractive index change there is two regimes of variations and the critical well number was six. In our calculations, we have used the same wells and barrier thicknesses to construct the multiple quantum wells system. - Highlights: ► OptiOptical Non-Linear. ► Total Effective Length. ► Multiple Quantum Wells System - genetic algorithm ► Schrödinger equation solution. ► Nanostructure.

Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression

KAUST Repository

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.

Linear systems and multiplicity of ideals

International Nuclear Information System (INIS)

Le Dung Trang

2008-06-01

Using a geometric interpretation of the multiplicity, we give a geometric way to calculate the multiplicity. We consider the particular case of a non-singular complex surface and give an example with a geometric proof of a result. Most of this note is written in the language of complex analytic spaces, but the results can be stated and proved in the case of schemes of finite type over an infinite field with equi-characteristic local rings

Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

Science.gov (United States)

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.

Base Isolation for Seismic Retrofitting of a Multiple Building Structure: Evaluation of Equivalent Linearization Method

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.

MAGDM linear-programming models with distinct uncertain preference structures.

Science.gov (United States)

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.

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

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

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

A multiple objective mixed integer linear programming model for power generation expansion planning

Energy Technology Data Exchange (ETDEWEB)

Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)

2004-03-01

Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)

Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws.

Science.gov (United States)

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 © 2010 Elsevier Ireland Ltd. All rights reserved.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

Science.gov (United States)

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Reduction of interferences in graphite furnace atomic absorption spectrometry by multiple linear regression modelling

Science.gov (United States)

Grotti, Marco; Abelmoschi, Maria Luisa; Soggia, Francesco; Tiberiade, Christian; Frache, Roberto

2000-12-01

The multivariate effects of Na, K, Mg and Ca as nitrates on the electrothermal atomisation of manganese, cadmium and iron were studied by multiple linear regression modelling. Since the models proved to efficiently predict the effects of the considered matrix elements in a wide range of concentrations, they were applied to correct the interferences occurring in the determination of trace elements in seawater after pre-concentration of the analytes. In order to obtain a statistically significant number of samples, a large volume of the certified seawater reference materials CASS-3 and NASS-3 was treated with Chelex-100 resin; then, the chelating resin was separated from the solution, divided into several sub-samples, each of them was eluted with nitric acid and analysed by electrothermal atomic absorption spectrometry (for trace element determinations) and inductively coupled plasma optical emission spectrometry (for matrix element determinations). To minimise any other systematic error besides that due to matrix effects, accuracy of the pre-concentration step and contamination levels of the procedure were checked by inductively coupled plasma mass spectrometric measurements. Analytical results obtained by applying the multiple linear regression models were compared with those obtained with other calibration methods, such as external calibration using acid-based standards, external calibration using matrix-matched standards and the analyte addition technique. Empirical models proved to efficiently reduce interferences occurring in the analysis of real samples, allowing an improvement of accuracy better than for other calibration methods.

Using virtual reality to distinguish subjects with multiple- but not single-domain amnestic mild cognitive impairment from normal elderly subjects.

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Mohammadi, Alireza; Kargar, Mahmoud; Hesami, Ehsan

2018-03-01

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.

On the linear programming bound for linear Lee codes.

Science.gov (United States)

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.

Pharmacokinetics of lansoprazole and its main metabolites after single and multiple intravenous doses in healthy Chinese subjects.

Science.gov (United States)

Zhang, Dan; Zhang, Yanan; Liu, Man; Wang, Xiaolin; Yang, Man; Han, Jing; Liu, Huichen

2013-09-01

The aim of the study was to evaluate and compare the pharmacokinetics of lansoprazole (LPZ) and its main metabolites, 5'-hydroxy lansoprazole (HLPZ) and lansoprazole sulfone (LPZS), after single and multiple intravenous (i.v.) doses of LPZ in healthy Chinese subjects. Twelve subjects (six males and six females) were given a single dose of LPZ by i.v. infusion on day 1, and multiple doses from day 2 to day 6. Blood samples were collected at designated time points for analysis of plasma concentrations of LPZ, HLPZ and LPZS by an LC-MS/MS method. LPZ was generally well tolerated in healthy Chinese subjects. After single and multiple i.v. doses of 30 mg LPZ, the C max values of LPZ, HLPZ and LPZS were 1490 ± 290 and 1450 ± 280, 175 ± 71 and 154 ± 56, and 51.3 ± 82.9 and 74.1 ± 158.7 ng/mL, with the AUC0-t values 3280 ± 2550 and 4260 ± 3880, 381 ± 128 and 389 ± 111, and 389 ± 1204 and 700 ± 2255 ng h/mL, respectively. The t 1/2 and CL values of LPZ after single and multiple i.v. doses were 1.48 ± 1.03 and 2.19 ± 1.03 h, and 11.67 ± 4.49 and 9.56 ± 4.08 L/h, respectively. Compared with the pharmacokinetics of LPZ after a single dose, t 1/2 increased markedly, CL decreased significantly and AUC increased by over 20 % after multiple doses. The results indicated that there was drug accumulation of LPZ after multiple i.v. doses, and there was no gender-related difference in pharmacokinetics of LPZ and its two metabolites.

Ventricular enlargement in multiple sclerosis: a comparison of three-dimensional and linear MRI estimates

International Nuclear Information System (INIS)

Turner, B.; Blumhardt, L.D.; Ramli, N.; Jaspan, T.

2001-01-01

Atrophy of central white matter is related to irreversible clinical disability in multiple sclerosis (MS) and ventricular enlargement may be a sensitive marker of this tissue loss. Therapeutic trials in MS have provided MRI data for investigation of cerebral atrophy in MS. These studies use almost exclusively two-dimensional (2-D) images, which may be limited in the assessment of three-dimensional (3-D) structures. We used 3-D MRI data to estimate ventricular volumes in 40 patients with MS and 10 healthy controls, to look at associations with clinical disability and the stage of the disease. We then compared simple linear measures of ventricular size from conventional 2-D images, with 3-D volume estimates to establish the best available linear indices of ventricular volume. Mean ventricular volumes were increased in the patients and significantly larger in the more disabled patients. The estimated volume of the third ventricle obtained from 3-D MRI showed the strongest association with the clinical stage of the disease, duration of symptoms and levels of disability. Finally, we confirmed that in patients with MS accurate data on ventricular size can be obtained from 2-D images by two simple and convenient linear measures, the width of the third ventricle and of the anterior horn of the lateral ventricle. (orig.)

Detection and Classification of Multiple Objects using an RGB-D Sensor and Linear Spatial Pyramid Matching

DEFF Research Database (Denmark)

Dimitriou, Michalis; Kounalakis, Tsampikos; Vidakis, Nikolaos

2013-01-01

, 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......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...... is making machines see and understand objects like humans do. To this goal, the new RGB-D sensors can be utilized since they provide real-time depth map which can be used along with the RGB images for our tasks. In our system we employ effective depth map processing techniques, along with edge detection...

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 ...

Using Linear and Non-Linear Temporal Adjustments to Align Multiple Phenology Curves, Making Vegetation Status and Health Directly Comparable

Science.gov (United States)

Hargrove, W. W.; Norman, S. P.; Kumar, J.; Hoffman, F. M.

2017-12-01

National-scale polar analysis of MODIS NDVI allows quantification of degree of seasonality expressed by local vegetation, and also selects the most optimum start/end of a local "phenological year" that is empirically customized for the vegetation that is growing at each location. Interannual differences in timing of phenology make direct comparisons of vegetation health and performance between years difficult, whether at the same or different locations. By "sliding" the two phenologies in time using a Procrustean linear time shift, any particular phenological event or "completion milestone" can be synchronized, allowing direct comparison of differences in timing of other remaining milestones. Going beyond a simple linear translation, time can be "rubber-sheeted," compressed or dilated. Considering one phenology curve to be a reference, the second phenology can be "rubber-sheeted" to fit that baseline as well as possible by stretching or shrinking time to match multiple control points, which can be any recognizable phenological events. Similar to "rubber sheeting" to georectify a map inside a GIS, rubber sheeting a phenology curve also yields a warping signature that shows at every time and every location how many days the adjusted phenology is ahead or behind the phenological development of the reference vegetation. Using such temporal methods to "adjust" phenologies may help to quantify vegetation impacts from frost, drought, wildfire, insects and diseases by permitting the most commensurate quantitative comparisons with unaffected vegetation.

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.

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

Science.gov (United States)

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

2010-10-01

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

Multiple continuous coverage of the earth based on multi-satellite systems with linear structure

Science.gov (United States)

Saulskiy, V. K.

2009-04-01

A new and wider definition is given to multi-satellite systems with linear structure (SLS), and efficiency of their application to multiple continuous coverage of the Earth is substantiated. Owing to this widening, SLS have incorporated already well-recognized “polar systems” by L. Rider and W.S. Adams, “kinematically regular systems” by G.V. Mozhaev, and “delta-systems” by J.G. Walker, as well as “near-polar systems” by Yu.P. Ulybyshev, and some other satellite constellations unknown before. A universal method of SLS optimization is presented, valid for any values of coverage multiplicity and the number of satellites in a system. The method uses the criterion of minimum radius of a circle seen from a satellite on the surface of the globe. Among the best SLS found in this way there are both systems representing the well-known classes mentioned above and new orbit constellations of satellites.

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

Science.gov (United States)

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.

Effect of Linear and Non-linear Resistance Exercise on Anaerobic Performance among Young Women

OpenAIRE

Homa Esmaeili; Ali Reza Amani; Taher Afsharnezhad

2015-01-01

The main goals of strength training are improving muscle strength, power and muscle endurance. The objective of the current study is to compare two popular linear and nonlinear resistance exercises interventions on the anaerobic power.  Previous research has shown differences intervention by the linear and non-linear resistance exercise in performance and strength in male athletes. By the way there are not enough data regarding female subjects. Eighteen young women subjects participated in th...

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...

[Multiple linear regression and ROC curve analysis of the factors of lumbar spine bone mineral density].

Science.gov (United States)

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.

The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation.

Directory of Open Access Journals (Sweden)

Shuo Wang

Full Text Available Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie's stochastic simulation algorithm (SSA. Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role.

White matter damage impairs access to consciousness in multiple sclerosis.

Science.gov (United States)

Reuter, Françoise; Del Cul, Antoine; Malikova, Irina; Naccache, Lionel; Confort-Gouny, Sylviane; Cohen, Laurent; Cherif, André Ali; Cozzone, Patrick J; Pelletier, Jean; Ranjeva, Jean-Philippe; Dehaene, Stanislas; Audoin, Bertrand

2009-01-15

Global neuronal workspace theory predicts that damage to long-distance white matter (WM) tracts should impair access to consciousness during the perception of brief stimuli. To address this issue, we studied visual backward masking in 18 patients at the very first clinical stage of multiple sclerosis (MS), a neurological disease characterized by extensive WM damage, and in 18 matched healthy subjects. In our masking paradigm, the visibility of a digit stimulus increases non-linearly as a function of the interval duration between this target and a subsequent mask. In order to characterize quantitatively, for each subject, the transition between non-conscious and conscious perception of the stimulus, we used non-linear regression to fit a sigmoid curve to objective performance and subjective visibility reports as a function of target-mask delay. The delay corresponding to the inflexion point of the sigmoid, where visibility suddenly increases, was termed the "non-linear transition threshold" and used as a summary measure of masking efficiency. Objective and subjective non-linear transition thresholds were highly correlated across subjects in both groups, and were higher in patients compared to controls. In patients, variations in the non-linear transition threshold were inversely correlated to the Magnetization transfer ratio (MTR) values inside the right dorsolateral prefrontal WM, the right occipito-frontal fasciculus and the left cerebellum. This study provides clinical evidence of a relationship between impairments of conscious access and integrity of large WM bundles, particularly involving prefrontal cortex, as predicted by global neuronal workspace theory.

The effect of self-assessed fatigue and subjective cognitive impairment on work capacity: The case of multiple sclerosis.

Science.gov (United States)

Kobelt, Gisela; Langdon, Dawn; Jönsson, Linus

2018-04-01

The impact of physical disability in multiple sclerosis on employment is well documented but the effect of neurological symptoms has been less well studied. We investigated the independent effect of self-reported fatigue and cognitive difficulties on work. In a large European cost of illness survey, self-reported fatigue, subjective cognitive impairment (SCI), and productivity at work were assessed with visual analogue scales (VAS 0-10). The analysis controlled for country, age, age at diagnosis, gender, education, and physical disability. A total of 13,796 patients were of working age and 6,598 were working. Physical disability had a powerful impact on the probability of working, as did education. The probability of working was reduced by 8.7% and 4.4% for each point increase on the VAS for SCI and fatigue, respectively ( p work hours decreased linearly with increasing severity of fatigue and cognitive problems, while sick leave during the 3 months preceding the assessment increased. Finally, the severity of both symptoms was associated with the level at which productivity at work was affected ( p work capacity and highlight the importance of assessment in clinical practice.

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

Science.gov (United States)

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.

Analysis of the Multiple-Solution Response of a Flexible Rotor Supported on Non-Linear Squeeze Film Dampers

Science.gov (United States)

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.

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

Use of probabilistic weights to enhance linear regression myoelectric control

Science.gov (United States)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

On Solution of Total Least Squares Problems with Multiple Right-hand Sides

Czech Academy of Sciences Publication Activity Database

Hnětynková, I.; Plešinger, Martin; Strakoš, Zdeněk

2008-01-01

Roč. 8, č. 1 (2008), s. 10815-10816 ISSN 1617-7061 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : total least squares problem * multiple right-hand sides * linear approximation problem Subject RIV: BA - General Mathematics

Multiple linear regression to estimate time-frequency electrophysiological responses in single trials.

Science.gov (United States)

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

Development of a Multiple Linear Regression Model to Forecast Facility Electrical Consumption at an Air Force Base.

Science.gov (United States)

1981-09-01

corresponds to the same square footage that consumed the electrical energy. 3. The basic assumptions of multiple linear regres- sion, as enumerated in...7. Data related to the sample of bases is assumed to be representative of bases in the population. Limitations Basic limitations on this research were... Ratemaking --Overview. Rand Report R-5894, Santa Monica CA, May 1977. Chatterjee, Samprit, and Bertram Price. Regression Analysis by Example. New York: John

A comparison in young and elderly subjects of the pharmacokinetics and pharmacodynamics of single and multiple doses of benazepril.

Science.gov (United States)

Macdonald, N J; Elliott, H L; Hughes, D M; Reid, J L

1993-01-01

1. The pharmacokinetics and pharmacodynamics of single and multiple oral doses of the ACE inhibitor benazepril were investigated in young and elderly normotensive subjects. 2. Following multiple doses the trough concentrations were significantly higher in the elderly and the areas under the plasma concentration-time curves (AUC0-24) were significantly greater, by approximately 23%. 3. The fall in blood pressure tended to be greater in the elderly subjects but this is likely to be attributable to their higher initial blood pressures, although it may reflect the small differences in pharmacokinetics. 4. The age related differences in kinetics and dynamics following multiple dosing are quantitatively similar to those obtained with single doses. However, there appears to be a quantitative difference between benazepril and other ACE inhibitors in that the age related increases were of a relatively smaller magnitude. PMID:9114904

Linear algebra

CERN Document Server

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

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

Science.gov (United States)

Fisz, Jacek J

2006-12-07

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

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

Science.gov (United States)

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 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.

Linear algebra

CERN Document Server

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

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

Science.gov (United States)

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.

Comparison of multiple linear regression, partial least squares and artificial neural networks for prediction of gas chromatographic relative retention times of trimethylsilylated anabolic androgenic steroids.

Science.gov (United States)

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.

Microstructural response and grain refinement mechanism of commercially pure titanium subjected to multiple laser shock peening impacts

International Nuclear Information System (INIS)

Lu, J.Z.; Wu, L.J.; Sun, G.F.; Luo, K.Y.; Zhang, Y.K.; Cai, J.; Cui, C.Y.; Luo, X.M.

2017-01-01

The microstructural response and grain subdivision process in commercially pure (CP) titanium subjected to multiple laser shock peening (LSP) impacts were investigated by means of optical microscopy (OM), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) observations. The micro-hardness curves as a function of the impact time were also determined. The deformation-induced grain refinement mechanism of the close-packed hexagonal (hcp) material by laser shock wave was subsequently analyzed. Experimental results showed that uniform equiaxed grains with an average size of less than 50 nm were generated due to the ultra-high plastic strain induced by multiple LSP impacts. Special attention was paid to four types of novel deformation-induced microstructural features, including a layered slip band in the tension deformation zone, and inverse-transformation martensite, micro-twin grating and micro-twin collision in the compression deformation zone. Furthermore, the grain refinement mechanism in the near-surface layer of CP titanium subjected to multiple LSP impacts contains two types of simultaneous subdivision modes: multi-directional mechanical twin (MT)-MT intersections at (sub)micrometer scale, and the intersection between longitudinal secondary MTs and transverse dislocation walls at nanometer scale. In addition, both grain refinement (nanocrystallization) and the existence of a small amount of inverse-transformation martensite induced by multiple LSP impacts contribute to an increase in the micro-hardness of the near-surface layer.

Diabetes is the main factor accounting for hypomagnesemia in obese subjects.

Directory of Open Access Journals (Sweden)

Albert Lecube

Full Text Available OBJECTIVE: Type 2 diabetes (T2DM and obesity are associated with magnesium deficiency. We aimed to determine whether the presence of type 2 diabetes and the degree of metabolic control are related to low serum magnesium levels in obese individuals. METHODS: A Case-control study: 200 obese subjects [50 with T2DM (cases and 150 without diabetes (controls] prospectively recruited. B Interventional study: the effect of bariatric surgery on serum magnesium levels was examined in a subset of 120 obese subjects (40 with type 2 diabetes and 80 without diabetes. RESULTS: Type 2 diabetic patients showed lower serum magnesium levels [0.75±0.07 vs. 0.81±0.06 mmol/L; mean difference -0.06 (95% CI -0.09 to -0.04; p<0.001] than non-diabetic patients. Forty-eight percent of diabetic subjects, but only 15% of non-diabetic subjects showed a serum magnesium concentration lower than 0.75 mmol/L. Significant negative correlations between magnesium and fasting plasma glucose, HbA1c, HOMA-IR, and BMI were detected. Multiple linear regression analysis showed that fasting plasma glucose and HbA1c independently predicted serum magnesium. After bariatric surgery serum magnesium increased only in those patients in whom diabetes was resolved, but remain unchanged in those who not, without difference in loss weight between groups. Changes in serum magnesium negatively correlated with changes in fasting plasma glucose and HbA1c. Absolute changes in HbA1c independently predicted magnesium changes in the multiple linear regression analysis. CONCLUSIONS: Our results provide evidence that the presence of diabetes and the degree of metabolic control are essential in accounting for the lower levels of magnesium that exist in obese subjects.

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

Science.gov (United States)

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

2017-03-01

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

Multiple linear stepwise regression of liver lipid levels: proton MR spectroscopy study in vivo at 3.0 T

International Nuclear Information System (INIS)

Xu Li; Liang Changhong; Xiao Yuanqiu; Zhang Zhonglin

2010-01-01

Objective: To analyze the correlations between liver lipid level determined by liver 3.0 T 1 H-MRS in vivo and influencing factors using multiple linear stepwise regression. Methods: The prospective study of liver 1 H-MRS was performed with 3.0 T system and eight-channel torso phased-array coils using PRESS sequence. Forty-four volunteers were enrolled in this study. Liver spectra were collected with a TR of 1500 ms, TE of 30 ms, volume of interest of 2 cm×2 cm×2 cm, NSA of 64 times. The acquired raw proton MRS data were processed by using a software program SAGE. For each MRS measurement, using water as the internal reference, the amplitude of the lipid signal was normalized to the sum of the signal from lipid and water to obtain percentage lipid within the liver. The statistical description of height, weight, age and BMI, Line width and water suppression were recorded, and Pearson analysis was applied to test their relationships. Multiple linear stepwise regression was used to set the statistical model for the prediction of Liver lipid content. Results: Age (39.1±12.6) years, body weight (64.4±10.4) kg, BMI (23.3±3.1) kg/m 2 , linewidth (18.9±4.4) and the water suppression (90.7±6.5)% had significant correlation with liver lipid content (0.00 to 0.96%, median 0.02%), r were 0.11, 0.44, 0.40, 0.52, -0.73 respectively (P<0.05). But only age, BMI, line width, and the water suppression entered into the multiple linear regression equation. Liver lipid content prediction equation was as follows: Y= 1.395 - (0.021×water suppression) + (0.022×BMI) + (0.014×line width) - (0.004×age), and the coefficient of determination was 0. 613, corrected coefficient of determination was 0.59. Conclusion: The regression model fitted well, since the variables of age, BMI, width, and water suppression can explain about 60% of liver lipid content changes. (authors)

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

Science.gov (United States)

Clark, Adrian G; Thurbide, Kevin B

2014-01-24

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

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

Science.gov (United States)

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.

Using the Multiplicative Schwarz Alternating Algorithm (MSAA) for Solving the Large Linear System of Equations Related to Global Gravity Field Recovery up to Degree and Order 120

Science.gov (United States)

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

Fuzzy linear model for production optimization of mining systems with multiple entities

Science.gov (United States)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Multi-disease analysis of maternal antibody decay using non-linear mixed models accounting for censoring.

Science.gov (United States)

Goeyvaerts, Nele; Leuridan, Elke; Faes, Christel; Van Damme, Pierre; Hens, Niel

2015-09-10

Biomedical studies often generate repeated measures of multiple outcomes on a set of subjects. It may be of interest to develop a biologically intuitive model for the joint evolution of these outcomes while assessing inter-subject heterogeneity. Even though it is common for biological processes to entail non-linear relationships, examples of multivariate non-linear mixed models (MNMMs) are still fairly rare. We contribute to this area by jointly analyzing the maternal antibody decay for measles, mumps, rubella, and varicella, allowing for a different non-linear decay model for each infectious disease. We present a general modeling framework to analyze multivariate non-linear longitudinal profiles subject to censoring, by combining multivariate random effects, non-linear growth and Tobit regression. We explore the hypothesis of a common infant-specific mechanism underlying maternal immunity using a pairwise correlated random-effects approach and evaluating different correlation matrix structures. The implied marginal correlation between maternal antibody levels is estimated using simulations. The mean duration of passive immunity was less than 4 months for all diseases with substantial heterogeneity between infants. The maternal antibody levels against rubella and varicella were found to be positively correlated, while little to no correlation could be inferred for the other disease pairs. For some pairs, computational issues occurred with increasing correlation matrix complexity, which underlines the importance of further developing estimation methods for MNMMs. Copyright © 2015 John Wiley & Sons, Ltd.

A primer on linear models

CERN Document Server

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

Towards the prediction of multiple necking during dynamic extension of round bar: linear stability approach versus finite element calculations

International Nuclear Information System (INIS)

Maï, S El; Petit, J; Mercier, S; Molinari, A

2014-01-01

The fragmentation of structures subject to dynamic conditions is a matter of interest for civil industries as well as for Defence institutions. Dynamic expansions of structures, such as cylinders or rings, have been performed to obtain crucial information on fragment distributions. Many authors have proposed to capture by FEA the experimental distribution of fragment size by introducing in the FE model a perturbation. Stability and bifurcation analyses have also been proposed to describe the evolution of the perturbation growth rate. In the proposed contribution, the multiple necking of a round bar in dynamic tensile loading is analysed by the FE method. A perturbation on the initial flow stress is introduced in the numerical model to trigger instabilities. The onset time and the dominant mode of necking have been characterized precisely and showed power law evolutions, with the loading velocities and moderately with the amplitudes and the cell sizes of the perturbations. In the second part of the paper, the development of linear stability analysis and the use of salient criteria in terms of the growth rate of perturbations enabled comparisons with the numerical results. A good correlation in terms of onset time of instabilities and of number of necks is shown.

H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

Directory of Open Access Journals (Sweden)

Caiyan Qin

2017-12-01

Full Text Available 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 synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in

Physical activity in subjects with multiple sclerosis with focus on gender differences: a survey.

Science.gov (United States)

Anens, Elisabeth; Emtner, Margareta; Zetterberg, Lena; Hellström, Karin

2014-03-10

There is increasing research that examines gender-issues in multiple sclerosis (MS), but little focus has been placed on gender-issues regarding physical activity. The aim of the present study was to describe levels of physical activity, self-efficacy for physical activity, fall-related self-efficacy, social support for physical activity, fatigue levels and the impact of MS on daily life, in addition to investigating gender differences. The sample for this cross-sectional cohort study consisted of 287 (84 men; 29.3%) adults with MS recruited from the Swedish Multiple Sclerosis Registry. A questionnaire was sent to the subjects consisting of the self-administrated measurements: Physical Activity Disability Survey - Revised, Exercise Self-Efficacy Scale, Falls-Efficacy Scale (Swedish version), Social Influences on Physical Activity, Fatigue Severity Scale and Multiple Sclerosis Impact Scale. Response rate was 58.2%. Men were less physically active, had lower self-efficacy for physical activity and lower fall-related self-efficacy than women. This was explained by men being more physically affected by the disease. Men also received less social support for physical activity from family members. The level of fatigue and psychological consequences of the disease were similar between the genders in the total sample, but subgroups of women with moderate MS and relapsing remitting MS experienced more fatigue than men. Men were less physically active, probably a result of being more physically affected by the disease. Men being more physically affected explained most of the gender differences found in this study. However, the number of men in the subgroup analyses was small and more research is needed. A gender perspective should be considered in strategies for promoting physical activity in subjects with MS, e.g. men may need more support to be physically active.

A subjective scheduler for subjective dedicated networks

Science.gov (United States)

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.

Linear quadratic optimization for positive LTI system

Science.gov (United States)

Muhafzan, Yenti, Syafrida Wirma; Zulakmal

2017-05-01

Nowaday the linear quadratic optimization subject to positive linear time invariant (LTI) system constitute an interesting study considering it can become a mathematical model of variety of real problem whose variables have to nonnegative and trajectories generated by these variables must be nonnegative. In this paper we propose a method to generate an optimal control of linear quadratic optimization subject to positive linear time invariant (LTI) system. A sufficient condition that guarantee the existence of such optimal control is discussed.

Relationships between the structure of wheat gluten and ACE inhibitory activity of hydrolysate: stepwise multiple linear regression analysis.

Science.gov (United States)

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.

Linear Algebra Thoroughly Explained

CERN Document Server

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.

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Science.gov (United States)

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Directory of Open Access Journals (Sweden)

Guan Yu

Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and

Perturbation Solutions for Random Linear Structural Systems subject to Random Excitation using Stochastic Differential Equations

DEFF Research Database (Denmark)

Köyluoglu, H.U.; Nielsen, Søren R.K.; Cakmak, A.S.

1994-01-01

perturbation method using stochastic differential equations. The joint statistical moments entering the perturbation solution are determined by considering an augmented dynamic system with state variables made up of the displacement and velocity vector and their first and second derivatives with respect......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...... to the random parameters of the problem. Equations for partial derivatives are obtained from the partial differentiation of the equations of motion. The zero time-lag joint statistical moment equations for the augmented state vector are derived from the Itô differential formula. General formulation is given...

Risks of falls in subjects with multiple sclerosis.

Science.gov (United States)

Cattaneo, Davide; De Nuzzo, Carmela; Fascia, Teresa; Macalli, Marco; Pisoni, Ivana; Cardini, Roldano

2002-06-01

To quantify fall risk among patients with multiple sclerosis (MS) and to report the importance of variables associated with falls. Retrospective case-control study design with a 2-group sample of convenience. A hospital and home settings in Italy. A convenience sample of 50 people with MS divided into 2 groups according to their reports of falls. Not applicable. Subjects were assessed with questionnaires for cognitive ability and were measured on their ability to maintain balance, to walk, and to perform daily life activities. Data regarding patients' strength, spasticity, and transfer skills impairment were also collected. No statistical differences were found between groups of fallers and nonfallers using variables pertaining to years after onset, age, gender, and Mini-Mental State Examination. Near statistically significant differences were found in activities of daily living and transfer skills (Pfall status: balance, ability to walk, and use of a cane (Pcane differed between fallers and nonfallers groups and the incidence of those variables can be used as a predictive model to quantify fall risk in patients suffering from MS. These findings emphasize the multifactorial nature of falls in this patient population. Assessment of different aspects of motor impairment and the accurate determination of factors contributing to falls are necessary for individual patient management and therapy and for the development of a prevention program for falls. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

Science.gov (United States)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

Dynamics of heart rate variability analysed through nonlinear and linear dynamics is already impaired in young type 1 diabetic subjects.

Science.gov (United States)

Souza, Naiara M; Giacon, Thais R; Pacagnelli, Francis L; Barbosa, Marianne P C R; Valenti, Vitor E; Vanderlei, Luiz C M

2016-10-01

Autonomic diabetic neuropathy is one of the most common complications of type 1 diabetes mellitus, and studies using heart rate variability to investigate these individuals have shown inconclusive results regarding autonomic nervous system activation. Aims To investigate the dynamics of heart rate in young subjects with type 1 diabetes mellitus through nonlinear and linear methods of heart rate variability. We evaluated 20 subjects with type 1 diabetes mellitus and 23 healthy control subjects. We obtained the following nonlinear indices from the recurrence plot: recurrence rate (REC), determinism (DET), and Shanon entropy (ES), and we analysed indices in the frequency (LF and HF in ms2 and normalised units - nu - and LF/HF ratio) and time domains (SDNN and RMSSD), through analysis of 1000 R-R intervals, captured by a heart rate monitor. There were reduced values (p<0.05) for individuals with type 1 diabetes mellitus compared with healthy subjects in the following indices: DET, REC, ES, RMSSD, SDNN, LF (ms2), and HF (ms2). In relation to the recurrence plot, subjects with type 1 diabetes mellitus demonstrated lower recurrence and greater variation in their plot, inter-group and intra-group, respectively. Young subjects with type 1 diabetes mellitus have autonomic nervous system behaviour that tends to randomness compared with healthy young subjects. Moreover, this behaviour is related to reduced sympathetic and parasympathetic activity of the autonomic nervous system.

[Study on retention and stability of linear occlusal complete dentures].

Science.gov (United States)

Zhang, Ping; Xu, Jun

2003-01-01

To learn retention and stability of linear occlusal complete dentures by investigating the subjective feelings of patient and the value of retention force. Static retention forces of maxillary and mandibular dentures were measured for 25 patients wearing linear occlusal dentures by using Hz-1 retention dynamometer. The subjective feelings of patients in functional state were gained simultaneously through questionnaire. Linear occlusal dentures demonstrate good retention in static and dynamic state. Among patients with severe resorption of residual ridge (RRR), mandibular linear occlusal dentures (shown good retentive subjective feelings) demonstrate significantly smaller retention force than those with slight or medium degree of RRR. There is no correlation between the subjective feelings and the values of retention forces of mandibular dentures. The subjective feelings of patients wearing new linear occlusal dentures are much better than that of old anatomic occlusal dentures. Linear occlusal dentures improve the performances of dentures by enhancing their stability during mastication movement.

Prolonged-release fampridine treatment improved subject-reported impact of multiple sclerosis: Item-level analysis of the MSIS-29.

Science.gov (United States)

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.

LPmerge: an R package for merging genetic maps by linear programming.

Science.gov (United States)

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Useful tools for non-linear systems: Several non-linear integral inequalities

Czech Academy of Sciences Publication Activity Database

Agahi, H.; Mohammadpour, A.; Mesiar, Radko; Vaezpour, M. S.

2013-01-01

Roč. 49, č. 1 (2013), s. 73-80 ISSN 0950-7051 R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : Monotone measure * Comonotone functions * Integral inequalities * Universal integral Subject RIV: BA - General Mathematics Impact factor: 3.058, year: 2013 http://library.utia.cas.cz/separaty/2013/E/mesiar-useful tools for non-linear systems several non-linear integral inequalities.pdf

Ranking Forestry Investments With Parametric Linear Programming

Science.gov (United States)

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.

Elements of linear space

CERN Document Server

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

Matrices and linear transformations

CERN Document Server

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

Identification of an Equivalent Linear Model for a Non-Linear Time-Variant RC-Structure

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Andersen, P.; Brincker, Rune

are investigated and compared with ARMAX models used on a running window. The techniques are evaluated using simulated data generated by the non-linear finite element program SARCOF modeling a 10-storey 3-bay concrete structure subjected to amplitude modulated Gaussian white noise filtered through a Kanai......This paper considers estimation of the maximum softening for a RC-structure subjected to earthquake excitation. The so-called Maximum Softening damage indicator relates the global damage state of the RC-structure to the relative decrease of the fundamental eigenfrequency in an equivalent linear...

A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

Science.gov (United States)

Marzban, Hamid Reza

2018-05-01

In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.

Science.gov (United States)

Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K

2014-11-26

The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.

2 ~ 5 times tunable repetition-rate multiplication of a 10 GHz pulse source using a linearly tunable, chirped fiber Bragg grating.

Science.gov (United States)

Lee, Ju Han; Chang, You; Han, Young-Geun; Kim, Sang; Lee, Sang

2004-08-23

We experimentally demonstrate a simple scheme for the tunable pulse repetition-rate multiplication based on the fractional Talbot effect in a linearly tunable, chirped fiber Bragg grating (FBG). The key component in this scheme is our linearly tunable, chirped FBG with no center wavelength shift, which was fabricated with the S-bending method using a uniform FBG. By simply tuning the group velocity dispersion of the chirped FBG, we readily multiply an original 8.5 ps, 10 GHz soliton pulse train by a factor of 2 ~ 5 to obtain high quality pulses at repetition-rates of 20 ~ 50 GHz without significantly changing the system configuration.

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

Science.gov (United States)

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.

Swallowing abnormalities in multiple sclerosis: correlation between videofluoroscopy and subjective symptoms

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.)

A linear evolution for non-linear dynamics and correlations in realistic nuclei

International Nuclear Information System (INIS)

Levin, E.; Lublinsky, M.

2004-01-01

A new approach to high energy evolution based on a linear equation for QCD generating functional is developed. This approach opens a possibility for systematic study of correlations inside targets, and, in particular, inside realistic nuclei. Our results are presented as three new equations. The first one is a linear equation for QCD generating functional (and for scattering amplitude) that sums the 'fan' diagrams. For the amplitude this equation is equivalent to the non-linear Balitsky-Kovchegov equation. The second equation is a generalization of the Balitsky-Kovchegov non-linear equation to interactions with realistic nuclei. It includes a new correlation parameter which incorporates, in a model-dependent way, correlations inside the nuclei. The third equation is a non-linear equation for QCD generating functional (and for scattering amplitude) that in addition to the 'fan' diagrams sums the Glauber-Mueller multiple rescatterings

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

Science.gov (United States)

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…

Weibull and lognormal Taguchi analysis using multiple linear regression

International Nuclear Information System (INIS)

Piña-Monarrez, Manuel R.; Ortiz-Yañez, Jesús F.

2015-01-01

The paper provides to reliability practitioners with a method (1) to estimate the robust Weibull family when the Taguchi method (TM) is applied, (2) to estimate the normal operational Weibull family in an accelerated life testing (ALT) analysis to give confidence to the extrapolation and (3) to perform the ANOVA analysis to both the robust and the normal operational Weibull family. On the other hand, because the Weibull distribution neither has the normal additive property nor has a direct relationship with the normal parameters (µ, σ), in this paper, the issues of estimating a Weibull family by using a design of experiment (DOE) are first addressed by using an L_9 (3"4) orthogonal array (OA) in both the TM and in the Weibull proportional hazard model approach (WPHM). Then, by using the Weibull/Gumbel and the lognormal/normal relationships and multiple linear regression, the direct relationships between the Weibull and the lifetime parameters are derived and used to formulate the proposed method. Moreover, since the derived direct relationships always hold, the method is generalized to the lognormal and ALT analysis. Finally, the method’s efficiency is shown through its application to the used OA and to a set of ALT data. - Highlights: • It gives the statistical relations and steps to use the Taguchi Method (TM) to analyze Weibull data. • It gives the steps to determine the unknown Weibull family to both the robust TM setting and the normal ALT level. • It gives a method to determine the expected lifetimes and to perform its ANOVA analysis in TM and ALT analysis. • It gives a method to give confidence to the extrapolation in an ALT analysis by using the Weibull family of the normal level.

Cortical Contribution to Linear, Non-linear and Frequency Components of Motor Variability Control during Standing.

Science.gov (United States)

König Ignasiak, Niklas; Habermacher, Lars; Taylor, William R; Singh, Navrag B

2017-01-01

Motor variability is an inherent feature of all human movements and reflects the quality of functional task performance. Depending on the requirements of the motor task, the human sensory-motor system is thought to be able to flexibly govern the appropriate level of variability. However, it remains unclear which neurophysiological structures are responsible for the control of motor variability. In this study, we tested the contribution of cortical cognitive resources on the control of motor variability (in this case postural sway) using a dual-task paradigm and furthermore observed potential changes in control strategy by evaluating Ia-afferent integration (H-reflex). Twenty healthy subjects were instructed to stand relaxed on a force plate with eyes open and closed, as well as while trying to minimize sway magnitude and performing a "subtracting-sevens" cognitive task. In total 25 linear and non-linear parameters were used to evaluate postural sway, which were combined using a Principal Components procedure. Neurophysiological response of Ia-afferent reflex loop was quantified using the Hoffman reflex. In order to assess the contribution of the H-reflex on the sway outcome in the different standing conditions multiple mixed-model ANCOVAs were performed. The results suggest that subjects were unable to further minimize their sway, despite actively focusing to do so. The dual-task had a destabilizing effect on PS, which could partly (by 4%) be counter-balanced by increasing reliance on Ia-afferent information. The effect of the dual-task was larger than the protective mechanism of increasing Ia-afferent information. We, therefore, conclude that cortical structures, as compared to peripheral reflex loops, play a dominant role in the control of motor variability.

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

International Nuclear Information System (INIS)

Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina

2009-01-01

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

Using Example Generation to Explore Students' Understanding of the Concepts of Linear Dependence/Independence in Linear Algebra

Science.gov (United States)

Aydin, Sinan

2014-01-01

Linear algebra is a basic mathematical subject taught in mathematics and science depar-tments of universities. The teaching and learning of this course has always been difficult. This study aims to contribute to the research in linear algebra education, focusing on linear dependence and independence concepts. This was done by introducing…

Fast linear solver for radiative transport equation with multiple right hand sides in diffuse optical tomography

International Nuclear Information System (INIS)

Jia, Jingfei; Kim, Hyun K.; Hielscher, Andreas H.

2015-01-01

It is well known that radiative transfer equation (RTE) provides more accurate tomographic results than its diffusion approximation (DA). However, RTE-based tomographic reconstruction codes have limited applicability in practice due to their high computational cost. In this article, we propose a new efficient method for solving the RTE forward problem with multiple light sources in an all-at-once manner instead of solving it for each source separately. To this end, we introduce here a novel linear solver called block biconjugate gradient stabilized method (block BiCGStab) that makes full use of the shared information between different right hand sides to accelerate solution convergence. Two parallelized block BiCGStab methods are proposed for additional acceleration under limited threads situation. We evaluate the performance of this algorithm with numerical simulation studies involving the Delta–Eddington approximation to the scattering phase function. The results show that the single threading block RTE solver proposed here reduces computation time by a factor of 1.5–3 as compared to the traditional sequential solution method and the parallel block solver by a factor of 1.5 as compared to the traditional parallel sequential method. This block linear solver is, moreover, independent of discretization schemes and preconditioners used; thus further acceleration and higher accuracy can be expected when combined with other existing discretization schemes or preconditioners. - Highlights: • We solve the multiple-right-hand-side problem in DOT with a block BiCGStab method. • We examine the CPU times of the block solver and the traditional sequential solver. • The block solver is faster than the sequential solver by a factor of 1.5–3.0. • Multi-threading block solvers give additional speedup under limited threads situation.

Multivariate linear regression of high-dimensional fMRI data with multiple target variables.

Science.gov (United States)

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.

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

Science.gov (United States)

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.

Progression of regional grey matter atrophy in multiple sclerosis.

Science.gov (United States)

Eshaghi, Arman; Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Prados, Ferran; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-06-01

See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article.Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple

Progression of regional grey matter atrophy in multiple sclerosis

Science.gov (United States)

Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-01-01

Abstract See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article. Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse

The art of linear electronics

CERN Document Server

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

Introduction to generalized linear models

CERN Document Server

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 ...

Program LINEAR (version 79-1): linearize data in the evaluated nuclear data file/version B (ENDF/B) format

International Nuclear Information System (INIS)

Cullen, D.E.

1979-01-01

Program LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form (i.e., removes points not needed for linear interpolability). The main advantage of the code is that it allows subsequent codes to consider only linear-linear data. A listing of the source deck is available on request

pKa prediction for acidic phosphorus-containing compounds using multiple linear regression with computational descriptors.

Science.gov (United States)

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.

Transmedia Storytelling in Science Communication: One Subject, Multiple Media, Multiple Stories

Science.gov (United States)

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.

Linear regression

CERN Document Server

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...

Matrices and linear algebra

CERN Document Server

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

Solvability of the Core Problem with Multiple Right-Hand Sides in the TLS Sense

Czech Academy of Sciences Publication Activity Database

Hnětynková, Iveta; Plešinger, M.; Sima, D.M.

2016-01-01

Roč. 37, č. 3 (2016), s. 861-876 ISSN 0895-4798 R&D Projects: GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : total least squares (TLS) problem * multiple right-hand sides * core problem * linear approximation problem * error-in-variables modeling * orthogonal regression * classical TLS algorithm Subject RIV: BA - General Mathematics Impact factor: 2.194, year: 2016

Population pharmacokinetics of artesunate and dihydroartemisinin following single- and multiple-dosing of oral artesunate in healthy subjects

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

Advanced linear algebra for engineers with Matlab

CERN Document Server

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

A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

Science.gov (United States)

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.

Multi-stratified multiple regression tests of the linear/no-threshold theory of radon-induced lung cancer

International Nuclear Information System (INIS)

Cohen, B.L.

1992-01-01

A plot of lung-cancer rates versus radon exposures in 965 US counties, or in all US states, has a strong negative slope, b, in sharp contrast to the strong positive slope predicted by linear/no-threshold theory. The discrepancy between these slopes exceeds 20 standard deviations (SD). Including smoking frequency in the analysis substantially improves fits to a linear relationship but has little effect on the discrepancy in b, because correlations between smoking frequency and radon levels are quite weak. Including 17 socioeconomic variables (SEV) in multiple regression analysis reduces the discrepancy to 15 SD. Data were divided into segments by stratifying on each SEV in turn, and on geography, and on both simultaneously, giving over 300 data sets to be analyzed individually, but negative slopes predominated. The slope is negative whether one considers only the most urban counties or only the most rural; only the richest or only the poorest; only the richest in the South Atlantic region or only the poorest in that region, etc., etc.,; and for all the strata in between. Since this is an ecological study, the well-known problems with ecological studies were investigated and found not to be applicable here. The open-quotes ecological fallacyclose quotes was shown not to apply in testing a linear/no-threshold theory, and the vulnerability to confounding is greatly reduced when confounding factors are only weakly correlated with radon levels, as is generally the case here. All confounding factors known to correlate with radon and with lung cancer were investigated quantitatively and found to have little effect on the discrepancy

Estimating the input function non-invasively for FDG-PET quantification with multiple linear regression analysis: simulation and verification with in vivo data

International Nuclear Information System (INIS)

Fang, Yu-Hua; Kao, Tsair; Liu, Ren-Shyan; Wu, Liang-Chih

2004-01-01

A novel statistical method, namely Regression-Estimated Input Function (REIF), is proposed in this study for the purpose of non-invasive estimation of the input function for fluorine-18 2-fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) quantitative analysis. We collected 44 patients who had undergone a blood sampling procedure during their FDG-PET scans. First, we generated tissue time-activity curves of the grey matter and the whole brain with a segmentation technique for every subject. Summations of different intervals of these two curves were used as a feature vector, which also included the net injection dose. Multiple linear regression analysis was then applied to find the correlation between the input function and the feature vector. After a simulation study with in vivo data, the data of 29 patients were applied to calculate the regression coefficients, which were then used to estimate the input functions of the other 15 subjects. Comparing the estimated input functions with the corresponding real input functions, the averaged error percentages of the area under the curve and the cerebral metabolic rate of glucose (CMRGlc) were 12.13±8.85 and 16.60±9.61, respectively. Regression analysis of the CMRGlc values derived from the real and estimated input functions revealed a high correlation (r=0.91). No significant difference was found between the real CMRGlc and that derived from our regression-estimated input function (Student's t test, P>0.05). The proposed REIF method demonstrated good abilities for input function and CMRGlc estimation, and represents a reliable replacement for the blood sampling procedures in FDG-PET quantification. (orig.)

Variable selection in multiple linear regression: The influence of ...

African Journals Online (AJOL)

provide an indication of whether the fit of the selected model improves or ... and calculate M(−i); quantify the influence of case i in terms of a function, f(•), of M and ..... [21] Venter JH & Snyman JLJ, 1997, Linear model selection based on risk ...

QSAR study of HCV NS5B polymerase inhibitors using the genetic algorithm-multiple linear regression (GA-MLR).

Science.gov (United States)

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.

Seismic analysis of equipment system with non-linearities such as gap and friction using equivalent linearization method

International Nuclear Information System (INIS)

Murakami, H.; Hirai, T.; Nakata, M.; Kobori, T.; Mizukoshi, K.; Takenaka, Y.; Miyagawa, N.

1989-01-01

Many of the equipment systems of nuclear power plants contain a number of non-linearities, such as gap and friction, due to their mechanical functions. It is desirable to take such non-linearities into account appropriately for the evaluation of the aseismic soundness. However, in usual design works, linear analysis method with rough assumptions is applied from engineering point of view. An equivalent linearization method is considered to be one of the effective analytical techniques to evaluate non-linear responses, provided that errors to a certain extent are tolerated, because it has greater simplicity in analysis and economization in computing time than non-linear analysis. The objective of this paper is to investigate the applicability of the equivalent linearization method to evaluate the maximum earthquake response of equipment systems such as the CANDU Fuelling Machine which has multiple non- linearities

Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints

International Nuclear Information System (INIS)

Zhang Yunong; Li Zhan

2009-01-01

In this Letter, by following Zhang et al.'s method, a recurrent neural network (termed as Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying convex quadratic-programming problem subject to time-varying linear-equality constraints. Different from conventional gradient-based neural networks (GNN), such a ZNN model makes full use of the time-derivative information of time-varying coefficient. The resultant ZNN model is theoretically proved to have global exponential convergence to the time-varying theoretical optimal solution of the investigated time-varying convex quadratic program. Computer-simulation results further substantiate the effectiveness, efficiency and novelty of such ZNN model and method.

Clinical Parameters following Multiple Oral Dose Administration of a Standardized Andrographis paniculata Capsule in Healthy Thai Subjects.

Science.gov (United States)

Suriyo, Tawit; Pholphana, Nanthanit; Ungtrakul, Teerapat; Rangkadilok, Nuchanart; Panomvana, Duangchit; Thiantanawat, Apinya; Pongpun, Wanwisa; Satayavivad, Jutamaad

2017-06-01

Andrographis paniculata has been widely used in Scandinavian and Asian counties for the treatment of the common cold, fever, and noninfectious diarrhea. The present study was carried out to investigate the physiological effects of short-term multiple dose administration of a standardized A. paniculata capsule used for treatment of the common cold and uncomplicated upper respiratory tract infections, including blood pressure, electrocardiogram, blood chemistry, hematological profiles, urinalysis, and blood coagulation in healthy Thai subjects. Twenty healthy subjects (10 males and 10 females) received 12 capsules per day orally of 4.2 g of a standardized A. paniculata crude powder (4 capsules of 1.4 g of A. paniculata , 3 times per day, 8 h intervals) for 3 consecutive days. The results showed that all of the measured clinical parameters were found to be within normal ranges for a healthy person. However, modulation of some parameters was observed after the third day of treatment, for example, inductions of white blood cells and absolute neutrophil count in the blood, a reduction of plasma alkaline phosphatase, and an induction of urine pH. A rapid and transient reduction in blood pressure was observed at 30 min after capsule administration, resulting in a significant reduction of mean systolic blood pressure. There were no serious adverse events observed in the subjects during the treatment period. In conclusion, this study suggests that multiple oral dosing of A. paniculata at the normal therapeutic dose for the common cold and uncomplicated upper respiratory tract infections modulates various clinical parameters within normal ranges for a healthy person. Georg Thieme Verlag KG Stuttgart · New York.

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

Science.gov (United States)

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.

Survival in commercially insured multiple sclerosis patients and comparator subjects in the U.S.

Science.gov (United States)

Kaufman, D W; Reshef, S; Golub, H L; Peucker, M; Corwin, M J; Goodin, D S; Knappertz, V; Pleimes, D; Cutter, G

2014-05-01

Compare survival in patients with multiple sclerosis (MS) from a U.S. commercial health insurance database with a matched cohort of non-MS subjects. 30,402 MS patients and 89,818 non-MS subjects (comparators) in the OptumInsight Research (OIR) database from 1996 to 2009 were included. An MS diagnosis required at least 3 consecutive months of database reporting, with two or more ICD-9 codes of 340 at least 30 days apart, or the combination of 1 ICD-9-340 code and at least 1 MS disease-modifying treatment (DMT) code. Comparators required the absence of ICD-9-340 and DMT codes throughout database reporting. Up to three comparators were matched to each patient for: age in the year of the first relevant code (index year - at least 3 months of reporting in that year were required); sex; region of residence in the index year. Deaths were ascertained from the National Death Index and the Social Security Administration Death Master File. Subjects not identified as deceased were assumed to be alive through the end of 2009. Annual mortality rates were 899/100,000 among MS patients and 446/100,000 among comparators. Standardized mortality ratios compared to the U.S. population were 1.70 and 0.80, respectively. Kaplan-Meier analysis yielded a median survival from birth that was 6 years lower among MS patients than among comparators. The results show, for the first time in a U.S. population, a survival disadvantage for contemporary MS patients compared to non-MS subjects from the same healthcare system. The 6-year decrement in lifespan parallels a recent report from British Columbia. Copyright © 2013 Elsevier B.V. All rights reserved.

On the estimation of multiple random integrals and U-statistics

CERN Document Server

Major, Péter

2013-01-01

This work starts with the study of those limit theorems in probability theory for which classical methods do not work. In many cases some form of linearization can help to solve the problem, because the linearized version is simpler. But in order to apply such a method we have to show that the linearization causes a negligible error. The estimation of this error leads to some important large deviation type problems, and the main subject of this work is their investigation. We provide sharp estimates of the tail distribution of multiple integrals with respect to a normalized empirical measure and so-called degenerate U-statistics and also of the supremum of appropriate classes of such quantities. The proofs apply a number of useful techniques of modern probability that enable us to investigate the non-linear functionals of independent random variables. This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when stand...

Log-gamma linear-mixed effects models for multiple outcomes with application to a longitudinal glaucoma study

Science.gov (United States)

Zhang, Peng; Luo, Dandan; Li, Pengfei; Sharpsten, Lucie; Medeiros, Felipe A.

2015-01-01

Glaucoma is a progressive disease due to damage in the optic nerve with associated functional losses. Although the relationship between structural and functional progression in glaucoma is well established, there is disagreement on how this association evolves over time. In addressing this issue, we propose a new class of non-Gaussian linear-mixed models to estimate the correlations among subject-specific effects in multivariate longitudinal studies with a skewed distribution of random effects, to be used in a study of glaucoma. This class provides an efficient estimation of subject-specific effects by modeling the skewed random effects through the log-gamma distribution. It also provides more reliable estimates of the correlations between the random effects. To validate the log-gamma assumption against the usual normality assumption of the random effects, we propose a lack-of-fit test using the profile likelihood function of the shape parameter. We apply this method to data from a prospective observation study, the Diagnostic Innovations in Glaucoma Study, to present a statistically significant association between structural and functional change rates that leads to a better understanding of the progression of glaucoma over time. PMID:26075565

Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise

Science.gov (United States)

Thompson, William F.; Kuske, Rachel A.; Monahan, Adam H.

2017-11-01

Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process. We use (semi)-analytical approximations combined with numerical illustrations to compare the averaged process to one that is forced by a white α-stable process, demonstrating consistent properties in the case of large time-scale separation. We identify the conditions required for the fast linear CAM process to have such an influence in driving a slower process and then derive an (effectively) equivalent fast, infinite-variance process for which an existing stochastic averaging approximation is readily applied. The results are illustrated using numerical simulations of a set of example systems.

Optimal Willingness to Supply Wholesale Electricity Under Asymmetric Linearized Marginal Costs

Directory of Open Access Journals (Sweden)

David Hudgins

2012-01-01

Full Text Available This analysis derives the profit-maximizing willingness to supply functions for single-plant and multi-plant wholesale electricity suppliers that all incur linear marginal costs. The optimal strategy must result in linear residual demand functions in the absence of capacity constraints. This necessarily leads to a linear pricing rule structure that can be used by firm managers to construct their offer curves and to serve as a benchmark to evaluate firm profit-maximizing behavior. The procedure derives the cost functions and the residual demand curves for merged or multi-plant generators, and uses these to construct the individual generator plant offer curves for a multi-plant firm.

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 ...

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

Science.gov (United States)

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

2006-02-15

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

Development of multiple linear regression models as predictive tools for fecal indicator concentrations in a stretch of the lower Lahn River, Germany.

Science.gov (United States)

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.

Distributed 3D Source Localization from 2D DOA Measurements Using Multiple Linear Arrays

Directory of Open Access Journals (Sweden)

Antonio Canclini

2017-01-01

Full Text Available This manuscript addresses the problem of 3D source localization from direction of arrivals (DOAs in wireless acoustic sensor networks. In this context, multiple sensors measure the DOA of the source, and a central node combines the measurements to yield the source location estimate. Traditional approaches require 3D DOA measurements; that is, each sensor estimates the azimuth and elevation of the source by means of a microphone array, typically in a planar or spherical configuration. The proposed methodology aims at reducing the hardware and computational costs by combining measurements related to 2D DOAs estimated from linear arrays arbitrarily displaced in the 3D space. Each sensor measures the DOA in the plane containing the array and the source. Measurements are then translated into an equivalent planar geometry, in which a set of coplanar equivalent arrays observe the source preserving the original DOAs. This formulation is exploited to define a cost function, whose minimization leads to the source location estimation. An extensive simulation campaign validates the proposed approach and compares its accuracy with state-of-the-art methodologies.

Associations between subjective sleep quality and brain volume in Gulf War veterans.

Science.gov (United States)

Chao, Linda L; Mohlenhoff, Brian S; Weiner, Michael W; Neylan, Thomas C

2014-03-01

To investigate whether subjective sleep quality is associated with brain volume independent of comorbid psychiatric conditions. Cross-sectional. Department of Veterans Affairs (VA) Medical Center. One hundred forty-four Gulf War Veterans (mean age 45 years; range: 31-70 years; 14% female). None. Total cortical, lobar gray matter, and hippocampal volumes were quantified from 1.5 Tesla magnetic resonance images using Freesurfer version 4.5. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Multiple linear regressions were used to determine the association of sleep quality with total and regional brain volumes. The global PSQI score was positively correlated with lifetime and current posttraumatic stress disorder (PTSD) and current depressive symptoms (P sleep quality. Poorer subjective sleep quality was associated with reduced total cortical and regional frontal lobe volumes independent of comorbid psychiatric conditions. Future work will be needed to examine if effective treatment of disturbed sleep leads to improved structural and functional integrity of the frontal lobes.

A note on the linear memory Baum-Welch algorithm

DEFF Research Database (Denmark)

Jensen, Jens Ledet

2009-01-01

We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject.......We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject....

Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

Directory of Open Access Journals (Sweden)

T. Youssef

2013-01-01

Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

Linear ubiquitination in immunity.

Science.gov (United States)

Shimizu, Yutaka; Taraborrelli, Lucia; Walczak, Henning

2015-07-01

Linear ubiquitination is a post-translational protein modification recently discovered to be crucial for innate and adaptive immune signaling. The function of linear ubiquitin chains is regulated at multiple levels: generation, recognition, and removal. These chains are generated by the linear ubiquitin chain assembly complex (LUBAC), the only known ubiquitin E3 capable of forming the linear ubiquitin linkage de novo. LUBAC is not only relevant for activation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases (MAPKs) in various signaling pathways, but importantly, it also regulates cell death downstream of immune receptors capable of inducing this response. Recognition of the linear ubiquitin linkage is specifically mediated by certain ubiquitin receptors, which is crucial for translation into the intended signaling outputs. LUBAC deficiency results in attenuated gene activation and increased cell death, causing pathologic conditions in both, mice, and humans. Removal of ubiquitin chains is mediated by deubiquitinases (DUBs). Two of them, OTULIN and CYLD, are constitutively associated with LUBAC. Here, we review the current knowledge on linear ubiquitination in immune signaling pathways and the biochemical mechanisms as to how linear polyubiquitin exerts its functions distinctly from those of other ubiquitin linkage types. © 2015 The Authors. Immunological Reviews Published by John Wiley & Sons Ltd.

A Reduced Dantzig-Wolfe Decomposition for a Suboptimal Linear MPC

DEFF Research Database (Denmark)

Standardi, Laura; Poulsen, Niels Kjølstad; Jørgensen, John Bagterp

2014-01-01

Linear Model Predictive Control (MPC) is an efficient control technique that repeatedly solves online constrained linear programs. In this work we propose an economic linear MPC strategy for operation of energy systems consisting of multiple and independent power units. These systems cooperate...

40 CFR 721.10094 - Decene, branched and linear.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Decene, branched and linear. 721.10094... Substances § 721.10094 Decene, branched and linear. (a) Chemical substance and significant new uses subject to reporting. (1) The chemical substance identified as decene, branched and linear (PMN P-03-272; CAS...

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...... of homogeneous distributions, tensor products and halfspace extensions have been revised. Examples include the von Karman equation....

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Application of single-step genomic best linear unbiased prediction with a multiple-lactation random regression test-day model for Japanese Holsteins.

Science.gov (United States)

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.

Linear approximation model network and its formation via ...

Indian Academy of Sciences (India)

To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

Visuo-manual tracking: does intermittent control with aperiodic sampling explain linear power and non-linear remnant without sensorimotor noise?

Science.gov (United States)

Gollee, Henrik; Gawthrop, Peter J; Lakie, Martin; Loram, Ian D

2017-11-01

A human controlling an external system is described most easily and conventionally as linearly and continuously translating sensory input to motor output, with the inevitable output remnant, non-linearly related to the input, attributed to sensorimotor noise. Recent experiments show sustained manual tracking involves repeated refractoriness (insensitivity to sensory information for a certain duration), with the temporary 200-500 ms periods of irresponsiveness to sensory input making the control process intrinsically non-linear. This evidence calls for re-examination of the extent to which random sensorimotor noise is required to explain the non-linear remnant. This investigation of manual tracking shows how the full motor output (linear component and remnant) can be explained mechanistically by aperiodic sampling triggered by prediction error thresholds. Whereas broadband physiological noise is general to all processes, aperiodic sampling is associated with sensorimotor decision making within specific frontal, striatal and parietal networks; we conclude that manual tracking utilises such slow serial decision making pathways up to several times per second. The human operator is described adequately by linear translation of sensory input to motor output. Motor output also always includes a non-linear remnant resulting from random sensorimotor noise from multiple sources, and non-linear input transformations, for example thresholds or refractory periods. Recent evidence showed that manual tracking incurs substantial, serial, refractoriness (insensitivity to sensory information of 350 and 550 ms for 1st and 2nd order systems respectively). Our two questions are: (i) What are the comparative merits of explaining the non-linear remnant using noise or non-linear transformations? (ii) Can non-linear transformations represent serial motor decision making within the sensorimotor feedback loop intrinsic to tracking? Twelve participants (instructed to act in three prescribed

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

On the Relationship Between Confidence Sets and Exchangeable Weights in Multiple Linear Regression.

Science.gov (United States)

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.

Radii of Solvability and Unsolvability of Linear Systems

Czech Academy of Sciences Publication Activity Database

Hladík, M.; Rohn, Jiří

2016-01-01

Roč. 503, 15 August (2016), s. 120-134 ISSN 0024-3795 Institutional support: RVO:67985807 Keywords : interval matrix * linear equations * linear inequalities * matrix norm Subject RIV: BA - General Mathematics Impact factor: 0.973, year: 2016

Gratitude and Adolescents' Subjective Well-Being in School: The Multiple Mediating Roles of Basic Psychological Needs Satisfaction at School.

Science.gov (United States)

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.

Gratitude and Adolescents’ Subjective Well-Being in School: The Multiple Mediating Roles of Basic Psychological Needs Satisfaction at School

Science.gov (United States)

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

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

Linear algebra a first course with applications

CERN Document Server

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

The relationship between apical root resorption and orthodontic tooth movement in growing subjects.

Science.gov (United States)

Xu, Tianmin; Baumrind, S

2002-07-01

To investigate the relationship between apical root resorption and orthodontic tooth movement in growing subjects. 58 growing subjects were collected randomly into the study sample and another 40 non-treated cases were used as control. The apical resoption of the upper central incisors was measured on periapical film and the incisor displacement was measured on lateral cephalogram. Using multiple linear regression analysis to examine the relationship between root resoption and the displacement of the upper incisor apex in each of four direction (retraction, advancement, intrusion and extrusion). The statistically significant negative association were found between resorption and both intrusion (P < 0.001) and extrusion (P < 0.05), but no significant association was found between resorption and both retraction and advancement. The regression analysis implied an average of 2.29 mm resorption in the absence of apical displacement. The likelihood that the magnitude of displacement of the incisor root is positively associated with root resoption in the population of treated growing subjects is very small.

Eliciting Subjective Probabilities with Binary Lotteries

DEFF Research Database (Denmark)

Harrison, Glenn W.; Martínez-Correa, Jimmy; Swarthout, J. Todd

objective probabilities. Drawing a sample from the same subject population, we find evidence that the binary lottery procedure induces linear utility in a subjective probability elicitation task using the Quadratic Scoring Rule. We also show that the binary lottery procedure can induce direct revelation...

Handbook of linear algebra

CERN Document Server

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

Generalized linear mixed model for binary outcomes when covariates are subject to measurement errors and detection limits.

Science.gov (United States)

Xie, Xianhong; Xue, Xiaonan; Strickler, Howard D

2018-01-15

Longitudinal measurement of biomarkers is important in determining risk factors for binary endpoints such as infection or disease. However, biomarkers are subject to measurement error, and some are also subject to left-censoring due to a lower limit of detection. Statistical methods to address these issues are few. We herein propose a generalized linear mixed model and estimate the model parameters using the Monte Carlo Newton-Raphson (MCNR) method. Inferences regarding the parameters are made by applying Louis's method and the delta method. Simulation studies were conducted to compare the proposed MCNR method with existing methods including the maximum likelihood (ML) method and the ad hoc approach of replacing the left-censored values with half of the detection limit (HDL). The results showed that the performance of the MCNR method is superior to ML and HDL with respect to the empirical standard error, as well as the coverage probability for the 95% confidence interval. The HDL method uses an incorrect imputation method, and the computation is constrained by the number of quadrature points; while the ML method also suffers from the constrain for the number of quadrature points, the MCNR method does not have this limitation and approximates the likelihood function better than the other methods. The improvement of the MCNR method is further illustrated with real-world data from a longitudinal study of local cervicovaginal HIV viral load and its effects on oncogenic HPV detection in HIV-positive women. Copyright © 2017 John Wiley & Sons, Ltd.

Toric Codes, Multiplicative Structure and Decoding

DEFF Research Database (Denmark)

Hansen, Johan Peder

2017-01-01

Long linear codes constructed from toric varieties over finite fields, their multiplicative structure and decoding. The main theme is the inherent multiplicative structure on toric codes. The multiplicative structure allows for \\emph{decoding}, resembling the decoding of Reed-Solomon codes and al...

Input/Output linearizing control of a nuclear reactor

International Nuclear Information System (INIS)

Perez C, V.

1994-01-01

The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)

The non-linear dynamics of vortices subjected to correlated and ...

Indian Academy of Sciences (India)

Understanding the dynamics of vortex matter subjected to random and .... The authors thank the support provided by a joint grant (USIF-funds) from the ... of Naval Research and the Department of Science and Technology, Government of India ...

Simultaneous Balancing and Model Reduction of Switched Linear Systems

NARCIS (Netherlands)

Monshizadeh, Nima; Trentelman, Hendrikus; Camlibel, M.K.

2011-01-01

In this paper, first, balanced truncation of linear systems is revisited. Then, simultaneous balancing of multiple linear systems is investigated. Necessary and sufficient conditions are introduced to identify the case where simultaneous balancing is possible. The validity of these conditions is not

Linear fixed-field multipass arcs for recirculating linear accelerators

Directory of Open Access Journals (Sweden)

V. S. Morozov

2012-06-01

Full Text Available Recirculating linear accelerators (RLA’s provide a compact and efficient way of accelerating particle beams to medium and high energies by reusing the same linac for multiple passes. In the conventional scheme, after each pass, the different energy beams coming out of the linac are separated and directed into appropriate arcs for recirculation, with each pass requiring a separate fixed-energy arc. In this paper we present a concept of an RLA return arc based on linear combined-function magnets, in which two and potentially more consecutive passes with very different energies are transported through the same string of magnets. By adjusting the dipole and quadrupole components of the constituting linear combined-function magnets, the arc is designed to be achromatic and to have zero initial and final reference orbit offsets for all transported beam energies. We demonstrate the concept by developing a design for a droplet-shaped return arc for a dogbone RLA capable of transporting two beam passes with momenta different by a factor of 2. We present the results of tracking simulations of the two passes and lay out the path to end-to-end design and simulation of a complete dogbone RLA.

Religiosity and Spirituality as Predictors of Subjectively Perceived Happiness in University Students in Slovakia

Directory of Open Access Journals (Sweden)

Peter Babinčák

2016-03-01

Full Text Available Several research projects discuss the existence of weak to moderately strong positive relation between religiosity/spirituality on the one hand and subjective well-being, life satisfaction or quality of life on the other hand (see Kelley & Miller, 2007. Variables related to religiosity and spirituality of a person may be perceived in two ways: as protective factors of attaining subjective well-being or as barriers limiting its attainment. The objective of this study is verification of mutual relationship between the indicators of religiosity and spirituality with regard to subjectively perceived happiness and verification of predictive strength of these indicators with regard to subjective happiness. The sample of research participants consisted of 194 university students aged 18 to 26. The research used 4 tools: The Expressions of Spirituality Inventory-Revised (MacDonald, 2000, The Salience in Religious Commitment Scale (Roof & Perkins, 1975, Subjective Happiness Scale (Lyubomirsky & Lepper, 1999 and The Oxford Happiness Questionnaire (Hills & Argyle, 2002. Using multiple hierarchical linear regression (stepwise, we obtained 2 dimensions of spirituality as significant predictors of subjective happiness – Existential Well-Being and Experiential/Phenomenological Dimension. Demographic data and confession types were not proved as predictors of happiness.

Linear complexity for multidimensional arrays - a numerical invariant

DEFF Research Database (Denmark)

Gomez-Perez, Domingo; Høholdt, Tom; Moreno, Oscar

2015-01-01

Linear complexity is a measure of how complex a one dimensional sequence can be. In this paper we extend the concept of linear complexity to multiple dimensions and present a definition that is invariant under well-orderings of the arrays. As a result we find that our new definition for the proce...

The linearized inversion of the generalized interferometric multiple imaging

KAUST Repository

Aldawood, Ali; Hoteit, Ibrahim; Alkhalifah, Tariq Ali

2016-01-01

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

Game Theory and its Relationship with Linear Programming Models ...

African Journals Online (AJOL)

Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.

Study on TVD parameters sensitivity of a crankshaft using multiple scale and state space method considering quadratic and cubic non-linearities

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.

A note on the relationships between multiple imputation, maximum likelihood and fully Bayesian methods for missing responses in linear regression models.

Science.gov (United States)

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.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

Science.gov (United States)

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Linearly polarized photons at ELSA

Energy Technology Data Exchange (ETDEWEB)

Eberhardt, Holger [Physikalisches Institut, Universitaet Bonn (Germany)

2009-07-01

To investigate the nucleon resonance regime in meson photoproduction, double polarization experiments are currently performed at the electron accelerator ELSA in Bonn. The experiments make use of a polarized target and circularly or linearly polarized photon beams. Linearly polarized photons are produced by coherent bremsstrahlung from an accurately aligned diamond crystal. The orientation of the crystal with respect to the electron beam is measured using the Stonehenge-Technique. Both, the energy of maximum polarization and the plane of polarization, can be deliberately chosen for the experiment. The linearly polarized beam provides the basis for the measurement of azimuthal beam asymmetries, such as {sigma} (unpolarized target) and G (polarized target). These observables are extracted in various single and multiple meson photoproduction channels.

Comparison of a neural network with multiple linear regression for quantitative analysis in ICP-atomic emission spectroscopy

International Nuclear Information System (INIS)

Schierle, C.; Otto, M.

1992-01-01

A two layer perceptron with backpropagation of error is used for quantitative analysis in ICP-AES. The network was trained by emission spectra of two interfering lines of Cd and As and the concentrations of both elements were subsequently estimated from mixture spectra. The spectra of the Cd and As lines were also used to perform multiple linear regression (MLR) via the calculation of the pseudoinverse S + of the sensitivity matrix S. In the present paper it is shown that there exist close relations between the operation of the perceptron and the MLR procedure. These are most clearly apparent in the correlation between the weights of the backpropagation network and the elements of the pseudoinverse. Using MLR, the confidence intervals over the predictions are exploited to correct for the optical device of the wavelength shift. (orig.)

A clinico-MRI study of extrapyramidal symptoms in multiple system atrophy; Linear hyperintensity in the outer margin of the putamen

Energy Technology Data Exchange (ETDEWEB)

Konagaya, Masaaki; Iida, Mitsuo [Suzuka National Hospital, Mie (Japan); Konagaya, Yoko; Honda, Hitoshi

1993-06-01

We studied extrapyramidal symptoms and T2-weighted MRI findings of the putamen in 20 patients with multiple system atrophy (MSA) and 25 with idiopathic Parkinson's disease. Nine of the 20 MSA patients showed extrapyramidal symptoms. We could not observe cerebellar ataxia in two of the 9 patients because of severe rigidity and skinesia. Eight of the 9 MSA patients with extrapyramidal symptoms showed linear hyperintensity in the outer margin of the putamen. This abnormal intensity was bilateral and symmetric in most patients. However, in MSA patients without extrapyramidal symptoms, only one patient showed the linear hyperintensity. We could not find such abnormal intensity in any of the patients with Parkinson's disease. On proton density MRI, the signal intensity in the lesion was higher than that in the gray matter, which leads the speculation that the hyperintensity is gliosis of the putamen or increased extracellular fluid space caused by severe shrinkage of the putamen. These characteristic MRI findings may distinguish MSA with extrapyramidal symptoms from Parkinson's disease. (J.P.N.).

QSAR Study of Insecticides of Phthalamide Derivatives Using Multiple Linear Regression and Artificial Neural Network Methods

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.

Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

Science.gov (United States)

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.

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

Science.gov (United States)

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

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

NARCIS (Netherlands)

Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.

2014-01-01

Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate

Verification of Linear (In)Dependence in Finite Precision Arithmetic

Czech Academy of Sciences Publication Activity Database

Rohn, Jiří

2014-01-01

Roč. 8, č. 3-4 (2014), s. 323-328 ISSN 1661-8289 Institutional support: RVO:67985807 Keywords : linear dependence * linear independence * pseudoinverse matrix * finite precision arithmetic * verification * MATLAB file Subject RIV: BA - General Mathematics

Fuzzy Stabilization for Nonlinear Discrete Ship Steering Stochastic Systems Subject to State Variance and Passivity Constraints

Directory of Open Access Journals (Sweden)

Wen-Jer Chang

2014-01-01

Full Text Available For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.

Linear accelerators of the future

International Nuclear Information System (INIS)

Loew, G.A.

1986-07-01

Some of the requirements imposed on future linear accelerators to be used in electron-positron colliders are reviewed, as well as some approaches presently being examined for meeting those requirements. RF sources for use in these linacs are described, as well as wakefields, single bunches, and multiple-bunch trains

Stability and performance analysis of a jump linear control system subject to digital upsets

Science.gov (United States)

Wang, Rui; Sun, Hui; Ma, Zhen-Yang

2015-04-01

This paper focuses on the methodology analysis for the stability and the corresponding tracking performance of a closed-loop digital jump linear control system with a stochastic switching signal. The method is applied to a flight control system. A distributed recoverable platform is implemented on the flight control system and subject to independent digital upsets. The upset processes are used to stimulate electromagnetic environments. Specifically, the paper presents the scenarios that the upset process is directly injected into the distributed flight control system, which is modeled by independent Markov upset processes and independent and identically distributed (IID) processes. A theoretical performance analysis and simulation modelling are both presented in detail for a more complete independent digital upset injection. The specific examples are proposed to verify the methodology of tracking performance analysis. The general analyses for different configurations are also proposed. Comparisons among different configurations are conducted to demonstrate the availability and the characteristics of the design. Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61403395), the Natural Science Foundation of Tianjin, China (Grant No. 13JCYBJC39000), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, China, the Tianjin Key Laboratory of Civil Aircraft Airworthiness and Maintenance in Civil Aviation of China (Grant No. 104003020106), and the Fund for Scholars of Civil Aviation University of China (Grant No. 2012QD21x).

Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

Energy Technology Data Exchange (ETDEWEB)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1997-12-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

Linear and nonlinear analysis of heart rate variability in healthy subjects and after acute myocardial infarction in patients

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.

Fabricating off-diagonal components of frequency-dependent linear and nonlinear polarizabilities of doped quantum dots by Gaussian white noise

International Nuclear Information System (INIS)

Saha, Surajit; Ganguly, Jayanta; Ghosh, Manas

2015-01-01

We make a rigorous exploration of the profiles of off-diagonal components of frequency-dependent linear (α xy , α yx ), first nonlinear (β xyy , β yxx ), and second nonlinear (γ xxyy , γ yyxx ) polarizabilities of quantum dots driven by Gaussian white noise. The quantum dot is doped with repulsive Gaussian impurity. Noise has been applied additively and multiplicatively to the system. An external oscillatory electric field has also been applied to the system. Gradual variations of external frequency, dopant location, and noise strength give rise to interesting features of polarizability components. The observations reveal intricate interplay between noise strength and dopant location which designs the polarizability profiles. Moreover, the mode of application of noise also modulates the polarizability components. Interestingly, in case of additive noise the noise strength has no role on polarizabilities whereas multiplicative noise invites greater delicacy in them. The said interplay provides a rather involved framework to attain stable, enhanced, and often maximized output of linear and nonlinear polarizabilities. - Highlights: • Linear and nonlinear polarizabilities of quantum dot are studied. • The polarizability components are off-diagonal and frequency-dependent. • Quantum dot is doped with a repulsive impurity. • Doped system is subject to Gaussian white noise. • Mode of noise application affects polarizabilities

Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

Science.gov (United States)

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…

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

Science.gov (United States)

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

2014-01-01

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

Inverse estimation of multiple muscle activations based on linear logistic regression.

Science.gov (United States)

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.

MULTIPLE OBJECTS

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

Forecasting on the total volumes of Malaysia's imports and exports by multiple linear regression

Science.gov (United States)

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.

A consensus successive projections algorithm--multiple linear regression method for analyzing near infrared spectra.

Science.gov (United States)

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.

Linear Fixed-Field Multi-Pass Arcs for Recirculating Linear Accelerators

International Nuclear Information System (INIS)

Morozov, V.S.; Bogacz, S.A.; Roblin, Y.R.; Beard, K.B.

2012-01-01

Recirculating Linear Accelerators (RLA's) provide a compact and efficient way of accelerating particle beams to medium and high energies by reusing the same linac for multiple passes. In the conventional scheme, after each pass, the different energy beams coming out of the linac are separated and directed into appropriate arcs for recirculation, with each pass requiring a separate fixed-energy arc. In this paper we present a concept of an RLA return arc based on linear combined-function magnets, in which two and potentially more consecutive passes with very different energies are transported through the same string of magnets. By adjusting the dipole and quadrupole components of the constituting linear combined-function magnets, the arc is designed to be achromatic and to have zero initial and final reference orbit offsets for all transported beam energies. We demonstrate the concept by developing a design for a droplet-shaped return arc for a dog-bone RLA capable of transporting two beam passes with momenta different by a factor of two. We present the results of tracking simulations of the two passes and lay out the path to end-to-end design and simulation of a complete dog-bone RLA.

Dynamic analysis of multiple nuclear-coupled boiling channels based on a multi-point reactor model

International Nuclear Information System (INIS)

Lee, J.D.; Pan Chin

2005-01-01

This work investigates the non-linear dynamics and stabilities of a multiple nuclear-coupled boiling channel system based on a multi-point reactor model using the Galerkin nodal approximation method. The nodal approximation method for the multiple boiling channels developed by Lee and Pan [Lee, J.D., Pan, C., 1999. Dynamics of multiple parallel boiling channel systems with forced flows. Nucl. Eng. Des. 192, 31-44] is extended to address the two-phase flow dynamics in the present study. The multi-point reactor model, modified from Uehiro et al. [Uehiro, M., Rao, Y.F., Fukuda, K., 1996. Linear stability analysis on instabilities of in-phase and out-of-phase modes in boiling water reactors. J. Nucl. Sci. Technol. 33, 628-635], is employed to study a multiple-channel system with unequal steady-state neutron density distribution. Stability maps, non-linear dynamics and effects of major parameters on the multiple nuclear-coupled boiling channel system subject to a constant total flow rate are examined. This study finds that the void-reactivity feedback and neutron interactions among subcores are coupled and their competing effects may influence the system stability under different operating conditions. For those cases with strong neutron interaction conditions, by strengthening the void-reactivity feedback, the nuclear-coupled effect on the non-linear dynamics may induce two unstable oscillation modes, the supercritical Hopf bifurcation and the subcritical Hopf bifurcation. Moreover, for those cases with weak neutron interactions, by quadrupling the void-reactivity feedback coefficient, period-doubling and complex chaotic oscillations may appear in a three-channel system under some specific operating conditions. A unique type of complex chaotic attractor may evolve from the Rossler attractor because of the coupled channel-to-channel thermal-hydraulic and subcore-to-subcore neutron interactions. Such a complex chaotic attractor has the imbedding dimension of 5 and the

Embodied, Symbolic and Formal Thinking in Linear Algebra

Science.gov (United States)

Stewart, Sepideh; Thomas, Michael O. J.

2007-01-01

Students often find their first university linear algebra experience very challenging. While coping with procedural aspects of the subject, solving linear systems and manipulating matrices, they may struggle with crucial conceptual ideas underpinning them, making it very difficult to progress in more advanced courses. This research has sought to…

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

Linearized theory of inhomogeneous multiple 'water-bag' plasmas

Science.gov (United States)

Bloomberg, H. W.; Berk, H. L.

1973-01-01

Equations are derived for describing the inhomogeneous equilibrium and small deviations from the equilibrium, giving particular attention to systems with trapped particles. An investigation is conducted of periodic systems with a single trapped-particle water bag, taking into account the behavior of the perturbation equations at the turning points. An outline is provided concerning a procedure for obtaining the eigenvalues. The results of stability calculations connected with the sideband effects are considered along with questions regarding the general applicability of the multiple water-bag approach in stability calculations.

Universal features of multiplicity distributions

International Nuclear Information System (INIS)

Balantekin, A.B.; Washington Univ., Seattle, WA

1994-01-01

Universal features of multiplicity distributions are studied and combinants, certain linear combinations of ratios of probabilities, are introduced. It is argued that they can be a useful tool in analyzing multiplicity distributions of hadrons emitted in high energy collisions and large scale structure of galaxy distributions

Pharmacodynamic consequences of administration of VLA-4 antagonist CDP323 to multiple sclerosis subjects: a randomized, double-blind phase 1/2 study.

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.

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

Science.gov (United States)

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.

Performance Prediction Modelling for Flexible Pavement on Low Volume Roads Using Multiple Linear Regression Analysis

Directory of Open Access Journals (Sweden)

C. Makendran

2015-01-01

Full Text Available Prediction models for low volume village roads in India are developed to evaluate the progression of different types of distress such as roughness, cracking, and potholes. Even though the Government of India is investing huge quantum of money on road construction every year, poor control over the quality of road construction and its subsequent maintenance is leading to the faster road deterioration. In this regard, it is essential that scientific maintenance procedures are to be evolved on the basis of performance of low volume flexible pavements. Considering the above, an attempt has been made in this research endeavor to develop prediction models to understand the progression of roughness, cracking, and potholes in flexible pavements exposed to least or nil routine maintenance. Distress data were collected from the low volume rural roads covering about 173 stretches spread across Tamil Nadu state in India. Based on the above collected data, distress prediction models have been developed using multiple linear regression analysis. Further, the models have been validated using independent field data. It can be concluded that the models developed in this study can serve as useful tools for the practicing engineers maintaining flexible pavements on low volume roads.

Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.

Science.gov (United States)

Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J

2016-10-03

Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Text and Subject Position after Althusser

Directory of Open Access Journals (Sweden)

Antony Easthope

1994-01-01

Full Text Available Althusser's achievement is that he redefined Marxism. He reconceptualizes history and totality in terms of different times, construes knowledge as the outcome of a process of construction, and interprets subjectivity as an effect of ideology and unconscious processes. Unfortunately, Althusser's functionalist view of ideology claims that the subject recognizes itself as a subject because it duplicates— reflects—an absolute subject. However, Lacan's notion of the mirror stage remedies this fault. Lacan's subject always misrecognizes itself in a process of contradiction that threatens the stability of any given social order. Moreover, unlike Foucault's subject, which is limited in that subjectivity is folded back into a vaguely expanded notion of "power," this revised Althusserian subject allows careful reading of texts. The critic does not simply read against the grain; he or she exposes the multiple points of identification offered the reader. For example, Wordsworth's "The Solitary Reaper" installs the reader in multiple positions: a devotee of high culture and the national canon, a lover of the verbal signifier and its play, a consumer of confessional discourse, and a masculine "I" desiring a laboring, singing woman.

Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks

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Masaru Yokoe

2009-03-01

Full Text Available This paper proposes a method to quantitatively measure and evaluate finger tapping movements for the assessment of motor function using log-linearized Gaussian mixture networks (LLGMNs. First, finger tapping movements are measured using magnetic sensors, and eleven indices are computed for evaluation. After standardizing these indices based on those of normal subjects, they are input to LLGMNs to assess motor function. Then, motor ability is probabilistically discriminated to determine whether it is normal or not using a classifier combined with the output of multiple LLGMNs based on bagging and entropy. This paper reports on evaluation and discrimination experiments performed on finger tapping movements in 33 Parkinson’s disease (PD patients and 32 normal elderly subjects. The results showed that the patients could be classified correctly in terms of their impairment status with a high degree of accuracy (average rate: 93:1 § 3:69% using 12 LLGMNs, which was about 5% higher than the results obtained using a single LLGMN.

Association among retinol-binding protein 4, small dense LDL cholesterol and oxidized LDL levels in dyslipidemia subjects.

Science.gov (United States)

Wu, Jia; Shi, Yong-hui; Niu, Dong-mei; Li, Han-qing; Zhang, Chun-ni; Wang, Jun-jun

2012-06-01

To investigate retinol-binding protein 4 (RBP4), small dense low-density lipoprotein cholesterol (sdLDL-C) and oxidized low-density lipoprotein (ox-LDL) levels and their associations in dyslipidemia subjects. We determined RBP4, sdLDL-C, ox-LDL levels in 150 various dyslipidemia subjects and 50 controls. The correlation analysis and multiple linear regression analysis were performed. The RBP4, sdLDL-C and ox-LDL levels were found increased in various dyslipidemia subjects. The sdLDL-C levels were positively correlated with RBP4 (r=0.273, P=0.001) and ox-LDL (r=0.273, P=0.001). RBP4 levels were also correlated with ox-LDL (r=0.167, P=0.043). The multiple regression analysis showed that only sdLDL-C was a significant independent predictor for RBP4 (β coefficient=0.219, P=0.009; adjusted R(2)=0.041) and ox-LDL (β coefficient=0.253, P=0.003; adjusted R(2)=0.057) levels, respectively. The independent associations of sdLDL-C with RBP4 and ox-LDL were observed in dyslipidemia subjects. RBP4 may play an important role in lipid metabolism of atherosclerosis, particularly in formation of sdLDL. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

The Use of Linear Programming for Prediction.

Science.gov (United States)

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)

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

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.

Linearly Refined Session Types

Directory of Open Access Journals (Sweden)

Pedro Baltazar

2012-11-01

Full Text Available Session types capture precise protocol structure in concurrent programming, but do not specify properties of the exchanged values beyond their basic type. Refinement types are a form of dependent types that can address this limitation, combining types with logical formulae that may refer to program values and can constrain types using arbitrary predicates. We present a pi calculus with assume and assert operations, typed using a session discipline that incorporates refinement formulae written in a fragment of Multiplicative Linear Logic. Our original combination of session and refinement types, together with the well established benefits of linearity, allows very fine-grained specifications of communication protocols in which refinement formulae are treated as logical resources rather than persistent truths.

Selenium status, thyroid volume, and multiple nodule formation in an area with mild iodine deficiency

DEFF Research Database (Denmark)

Rasmussen, Lone Banke; Schomburg, Lutz; Kohrle, Josef

2011-01-01

) introduction of iodine fortification. Serum selenium concentration and urinary iodine were measured, and the thyroid gland was examined by ultrasonography in the same subjects. Associations between serum selenium concentration and thyroid parameters were examined in multiple linear regression models...... or logistic regression models.Results: Serum selenium concentration was found to be significantly, negatively associated with thyroid volume (P=0.006), and a low selenium status significantly increased the risk for thyroid enlargement (P=0.007). Furthermore, low serum selenium status had a tendency...

Linear scleroderma following Blaschko′s lines

Directory of Open Access Journals (Sweden)

Mukhopadhyay Amiya

2005-01-01

Full Text Available Blaschko′s lines form a pattern, which many diseases are found to follow, but linear scleroderma following Blaschko′s lines is a controversial entity rarely reported in the literature. A 24-year-old man presented with multiple linear, atrophic, hyperpigmented lesions punctuated by areas of depigmentations on the left half of the trunk distributed on the anterior, lateral and posterior aspects. The lesions were distributed in a typical S-shaped line. Antinuclear antibody and antihistone antibody tests were negative. Histopathological examination of the skin from the affected area showed features suggestive of scleroderma. Here, we present a case of linear scleroderma following Blaschko′s lines in a male patient - an entity reported only three times so far.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

Science.gov (United States)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

Diagnostic accuracy of full-body linear X-ray scanning in multiple trauma patients in comparison to computed tomography

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.

Modeling Non-Linear Material Properties in Composite Materials

Science.gov (United States)

2016-06-28

Technical Report ARWSB-TR-16013 MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS Michael F. Macri Andrew G...REPORT TYPE Technical 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS ...systems are increasingly incorporating composite materials into their design. Many of these systems subject the composites to environmental conditions

An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt

Science.gov (United States)

Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir

2018-04-01

Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.

EDITORIAL: Non-linear and non-Gaussian cosmological perturbations Non-linear and non-Gaussian cosmological perturbations

Science.gov (United States)

Sasaki, Misao; Wands, David

2010-06-01

In recent years there has been a resurgence of interest in the study of non-linear perturbations of cosmological models. This has been the result of both theoretical developments and observational advances. New theoretical challenges arise at second and higher order due to mode coupling and the need to develop new gauge-invariant variables beyond first order. In particular, non-linear interactions lead to deviations from a Gaussian distribution of primordial perturbations even if initial vacuum fluctuations are exactly Gaussian. These non-Gaussianities provide an important probe of models for the origin of structure in the very early universe. We now have a detailed picture of the primordial distribution of matter from surveys of the cosmic microwave background, notably NASA's WMAP satellite. The situation will continue to improve with future data from the ESA Planck satellite launched in 2009. To fully exploit these data cosmologists need to extend non-linear cosmological perturbation theory beyond the linear theory that has previously been sufficient on cosmological scales. Another recent development has been the realization that large-scale structure, revealed in high-redshift galaxy surveys, could also be sensitive to non-linearities in the primordial curvature perturbation. This focus section brings together a collection of invited papers which explore several topical issues in this subject. We hope it will be of interest to theoretical physicists and astrophysicists alike interested in understanding and interpreting recent developments in cosmological perturbation theory and models of the early universe. Of course it is only an incomplete snapshot of a rapidly developing field and we hope the reader will be inspired to read further work on the subject and, perhaps, fill in some of the missing pieces. This focus section is dedicated to the memory of Lev Kofman (1957-2009), an enthusiastic pioneer of inflationary cosmology and non-Gaussian perturbations.

[Sense of coherence and subjective overload, anxiety and depression in caregivers of elderly relatives].

Science.gov (United States)

López-Martínez, Catalina; Frías-Osuna, Antonio; Del-Pino-Casado, Rafael

2017-11-23

To analyze the relationship between the sense of coherence and subjective overload, anxiety and depression in caregivers of dependent elderly relatives. Cross-sectional study in an area of the province of Jaén (Andalusia, Spain) with a probabilistic sample of 132 caregivers of dependent elderly. sense of coherence (Life Orientation Questionnaire), subjective burden (Caregiver Strain Index), anxiety and depression (Goldberg Scale), objective burden (Dedication to Care Scale), sex and kinship. Main analyses: bivariate analysis using the Pearson correlation coefficient and multivariate analysis using multiple linear regression. Most of the caregivers studied were women (86.4%), daughter or son of the care recipient (74.2%) and shared home with the latter (69.7%). When controlling for objective burden, sex and kinship, we found that the sense of coherence was inversely related to subjective burden (β = -0.46; p <0.001), anxiety (β = -0.57; p = 0.001) and depression (β = -0.66; p <0.001). The sense of coherence might be an important protective factor of subjective burden, anxiety and depression in caregivers of dependent elderly relatives. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Annotated bibliography on high-intensity linear accelerators

International Nuclear Information System (INIS)

Jameson, R.A.; Roybal, E.U.

1978-01-01

A technical bibliography covering subjects important to the design of high-intensity beam transport systems and linear accelerators is presented. Space charge and emittance growth are stressed. Subject and author concordances provide cross-reference to detailed citations, which include an abstract and notes on the material. The bibliography resides in a computer database that can be searched for key words and phrases

Integrated structural analysis tool using the linear matching method part 1 – Software development

International Nuclear Information System (INIS)

Ure, James; Chen, Haofeng; Tipping, David

2014-01-01

A number of direct methods based upon the Linear Matching Method (LMM) framework have been developed to address structural integrity issues for components subjected to cyclic thermal and mechanical load conditions. This paper presents a new integrated structural analysis tool using the LMM framework for the assessment of load carrying capacity, shakedown limit, ratchet limit and steady state cyclic response of structures. First, the development of the LMM for the evaluation of design limits in plasticity is introduced. Second, preliminary considerations for the development of the LMM into a tool which can be used on a regular basis by engineers are discussed. After the re-structuring of the LMM subroutines for multiple central processing unit (CPU) solution, the LMM software tool for the assessment of design limits in plasticity is implemented by developing an Abaqus CAE plug-in with graphical user interfaces. Further demonstration of this new LMM analysis tool including practical application and verification is presented in an accompanying paper. - Highlights: • A new structural analysis tool using the Linear Matching Method (LMM) is developed. • The software tool is able to evaluate the design limits in plasticity. • Able to assess limit load, shakedown, ratchet limit and steady state cyclic response. • Re-structuring of the LMM subroutines for multiple CPU solution is conducted. • The software tool is implemented by developing an Abaqus CAE plug-in with GUI

Development of a predictive model for distribution coefficient (Kd) of 13'7Cs and 60Co in marine sediments using multiple linear regression analysis

International Nuclear Information System (INIS)

Kumar, Ajay; Ravi, P.M.; Guneshwar, S.L.; Rout, Sabyasachi; Mishra, Manish K.; Pulhani, Vandana; Tripathi, R.M.

2018-01-01

Numerous common methods (batch laboratory, the column laboratory, field-batch method, field modeling and K 0c method) are used frequently for determination of K d values. Recently, multiple regression models are considered as new best estimates for predicting the K d of radionuclides in the environment. It is also well known fact that the K d value is highly influenced by physico-chemical properties of sediment. Due to the significant variability in influencing parameters, the measured K d values can range over several orders of magnitude under different environmental conditions. The aim of this study is to develop a predictive model for K d values of 137 Cs and 60 Co based on the sediment properties using multiple linear regression analysis

Approximating the Pareto set of multiobjective linear programs via robust optimization

NARCIS (Netherlands)

Gorissen, B.L.; den Hertog, D.

2012-01-01

We consider problems with multiple linear objectives and linear constraints and use adjustable robust optimization and polynomial optimization as tools to approximate the Pareto set with polynomials of arbitrarily large degree. The main difference with existing techniques is that we optimize a

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

Science.gov (United States)

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

2018-05-01

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

Non-linear nuclear engineering models as genetic programming application

International Nuclear Information System (INIS)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

1997-01-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

Linear and non-linear interdependence of EEG and HRV frequency bands in human sleep.

Science.gov (United States)

Chaparro-Vargas, Ramiro; Dissanayaka, P Chamila; Patti, Chanakya Reddy; Schilling, Claudia; Schredl, Michael; Cvetkovic, Dean

2014-01-01

The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests upon 10 overnight polysomnographic (PSG) recordings, allowed the computation of wavelet coherence and phase locking values, in order to identify discerning features amongst the clinical healthy subjects. Our findings showed that neuronal oscillations θ, α and σ interact with cardiac power bands at mid-to-high rank of coherence and phase locking, particularly during NREM sleep stages.

A multiplicity logic unit

International Nuclear Information System (INIS)

Bialkowski, J.; Moszynski, M.; Zagorski, A.

1981-01-01

The logic diagram principle of operation and some details of the design of the multiplicity logic unit are presented. This unit was specially designed to fulfil the requirements of a multidetector arrangement for gamma-ray multiplicity measurements. The unit is equipped with 16 inputs controlled by a common coincidence gate. It delivers a linear output pulse with the height proportional to the multiplicity of coincidences and logic pulses corresponding to 0, 1, ... up to >= 5-fold coincidences. These last outputs are used to steer the routing unit working with the multichannel analyser. (orig.)

Joint source based analysis of multiple brain structures in studying major depressive disorder

Science.gov (United States)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Matlab linear algebra

CERN Document Server

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

A non-linear programming approach to the computer-aided design of regulators using a linear-quadratic formulation

Science.gov (United States)

Fleming, P.

1985-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.

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

Science.gov (United States)

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

2016-03-01

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

Optimized simultaneous inversion of primary and multiple reflections; Inversion linearisee simultanee des reflexions primaires et des reflexions multiples

Energy Technology Data Exchange (ETDEWEB)

Pelle, L.

2003-12-01

The removal of multiple reflections remains a real problem in seismic imaging. Many preprocessing methods have been developed to attenuate multiples in seismic data but none of them is satisfactory in 3D. The objective of this thesis is to develop a new method to remove multiples, extensible in 3D. Contrary to the existing methods, our approach is not a preprocessing step: we directly include the multiple removal in the imaging process by means of a simultaneous inversion of primaries and multiples. We then propose to improve the standard linearized inversion so as to make it insensitive to the presence of multiples in the data. We exploit kinematics differences between primaries and multiples. We propose to pick in the data the kinematics of the multiples we want to remove. The wave field is decomposed into primaries and multiples. Primaries are modeled by the Ray+Born operator from perturbations of the logarithm of impedance, given the velocity field. Multiples are modeled by the Transport operator from an initial trace, given the picking. The inverse problem simultaneously fits primaries and multiples to the data. To solve this problem with two unknowns, we take advantage of the isometric nature of the Transport operator, which allows to drastically reduce the CPU time: this simultaneous inversion is this almost as fast as the standard linearized inversion. This gain of time opens the way to different applications to multiple removal and in particular, allows to foresee the straightforward 3D extension. (author)

A linear concatenation strategy to construct 5'-enriched amplified cDNA libraries using multiple displacement amplification.

Science.gov (United States)

Gadkar, Vijay J; Filion, Martin

2013-06-01

In various experimental systems, limiting available amounts of RNA may prevent a researcher from performing large-scale analyses of gene transcripts. One way to circumvent this is to 'pre-amplify' the starting RNA/cDNA, so that sufficient amounts are available for any downstream analysis. In the present study, we report the development of a novel protocol for constructing amplified cDNA libraries using the Phi29 DNA polymerase based multiple displacement amplification (MDA) system. Using as little as 200 ng of total RNA, we developed a linear concatenation strategy to make the single-stranded cDNA template amenable for MDA. The concatenation, made possible by the template switching property of the reverse transcriptase enzyme, resulted in the amplified cDNA library with intact 5' ends. MDA generated micrograms of template, allowing large-scale polymerase chain reaction analyses or other large-scale downstream applications. As the amplified cDNA library contains intact 5' ends, it is also compatible with 5' RACE analyses of specific gene transcripts. Empirical validation of this protocol is demonstrated on a highly characterized (tomato) and an uncharacterized (corn gromwell) experimental system.

Validation of Individual Non-Linear Predictive Pharmacokinetic ...

African Journals Online (AJOL)

3Department of Veterinary Medicine, Faculty of Agriculture, University of Novi Sad, Novi Sad, Republic of Serbia ... Purpose: To evaluate the predictive performance of phenytoin multiple dosing non-linear pharmacokinetic ... status epilepticus affects an estimated 152,000 ..... causal factors, i.e., infection, inflammation, tissue.

Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

Science.gov (United States)

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.

Multiple Linear Regression and Artificial Neural Network to Predict Blood Glucose in Overweight Patients.

Science.gov (United States)

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.

Non-linear Dynamics of Speech in Schizophrenia

DEFF Research Database (Denmark)

Fusaroli, Riccardo; Simonsen, Arndis; Weed, Ethan

(regularity and complexity) of speech. Our aims are (1) to achieve a more fine-grained understanding of the speech patterns in schizophrenia than has previously been achieved using traditional, linear measures of prosody and fluency, and (2) to employ the results in a supervised machine-learning process......-effects inference. SANS and SAPS scores were predicted using a 10-fold cross-validated multiple linear regression. Both analyses were iterated 1000 to test for stability of results. Results: Voice dynamics allowed discrimination of patients with schizophrenia from healthy controls with a balanced accuracy of 85...

Beamstrahlung spectra in next generation linear colliders

Energy Technology Data Exchange (ETDEWEB)

Barklow, T.; Chen, P. (Stanford Linear Accelerator Center, Menlo Park, CA (United States)); Kozanecki, W. (DAPNIA-SPP, CEN-Saclay (France))

1992-04-01

For the next generation of linear colliders, the energy loss due to beamstrahlung during the collision of the e{sup +}e{sup {minus}} beams is expected to substantially influence the effective center-of-mass energy distribution of the colliding particles. In this paper, we first derive analytical formulae for the electron and photon energy spectra under multiple beamstrahlung processes, and for the e{sup +}e{sup {minus}} and {gamma}{gamma} differential luminosities. We then apply our formulation to various classes of 500 GeV e{sup +}e{sup {minus}} linear collider designs currently under study.

2D Quantitative Structure-Property Relationship Study of Mycotoxins by Multiple Linear Regression and Support Vector Machine

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.

Possible limits of plasma linear colliders

Science.gov (United States)

Zimmermann, F.

2017-07-01

Plasma linear colliders have been proposed as next or next-next generation energy-frontier machines for high-energy physics. I investigate possible fundamental limits on energy and luminosity of such type of colliders, considering acceleration, multiple scattering off plasma ions, intrabeam scattering, bremsstrahlung, and betatron radiation. The question of energy efficiency is also addressed.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

Science.gov (United States)

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.

Subjective Well-Being in Obese Individuals: The Multiple Roles of Exercise

Science.gov (United States)

Berger, Bonnie G.

2004-01-01

This paper focuses on the tangled web of obesity and exercise as it relates to subjective well-being. Many overweight individuals have low levels of subjective well-being as a reflection of "anti-fat" biases and sociocultural considerations. Since exercise helps balance the energy intake-output equation and is associated with mood benefits,…

The influence of perceived discrimination, sense of control, self-esteem and multiple discrepancies on the mental health and subjective well-being in Serbian immigrants in Canada

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.

A comparative study between the use of artificial neural networks and multiple linear regression for caustic concentration prediction in a stage of alumina production

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.

Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain using analogues and analogues followed by random forests and multiple linear regression

Directory of Open Access Journals (Sweden)

G. Ibarra-Berastegi

2011-06-01

Full Text Available In this paper, reanalysis fields from the ECMWF have been statistically downscaled to predict from large-scale atmospheric fields, surface moisture flux and daily precipitation at two observatories (Zaragoza and Tortosa, Ebro Valley, Spain during the 1961–2001 period. Three types of downscaling models have been built: (i analogues, (ii analogues followed by random forests and (iii analogues followed by multiple linear regression. The inputs consist of data (predictor fields taken from the ERA-40 reanalysis. The predicted fields are precipitation and surface moisture flux as measured at the two observatories. With the aim to reduce the dimensionality of the problem, the ERA-40 fields have been decomposed using empirical orthogonal functions. Available daily data has been divided into two parts: a training period used to find a group of about 300 analogues to build the downscaling model (1961–1996 and a test period (1997–2001, where models' performance has been assessed using independent data. In the case of surface moisture flux, the models based on analogues followed by random forests do not clearly outperform those built on analogues plus multiple linear regression, while simple averages calculated from the nearest analogues found in the training period, yielded only slightly worse results. In the case of precipitation, the three types of model performed equally. These results suggest that most of the models' downscaling capabilities can be attributed to the analogues-calculation stage.

Control system analysis for the perturbed linear accelerator rf system

CERN Document Server

Sung Il Kwon

2002-01-01

This paper addresses the modeling problem of the linear accelerator RF system in SNS. Klystrons are modeled as linear parameter varying systems. The effect of the high voltage power supply ripple on the klystron output voltage and the output phase is modeled as an additive disturbance. The cavity is modeled as a linear system and the beam current is modeled as the exogenous disturbance. The output uncertainty of the low level RF system which results from the uncertainties in the RF components and cabling is modeled as multiplicative uncertainty. Also, the feedback loop uncertainty and digital signal processing signal conditioning subsystem uncertainties are lumped together and are modeled as multiplicative uncertainty. Finally, the time delays in the loop are modeled as a lumped time delay. For the perturbed open loop system, the closed loop system performance, and stability are analyzed with the PI feedback controller.

CONTROL SYSTEM ANALYSIS FOR THE PERTURBED LINEAR ACCELERATOR RF SYSTEM

International Nuclear Information System (INIS)

SUNG-IL KWON; AMY H. REGAN

2002-01-01

This paper addresses the modeling problem of the linear accelerator RF system in SNS. Klystrons are modeled as linear parameter varying systems. The effect of the high voltage power supply ripple on the klystron output voltage and the output phase is modeled as an additive disturbance. The cavity is modeled as a linear system and the beam current is modeled as the exogenous disturbance. The output uncertainty of the low level RF system which results from the uncertainties in the RF components and cabling is modeled as multiplicative uncertainty. Also, the feedback loop uncertainty and digital signal processing signal conditioning subsystem uncertainties are lumped together and are modeled as multiplicative uncertainty. Finally, the time delays in the loop are modeled as a lumped time delay. For the perturbed open loop system, the closed loop system performance, and stability are analyzed with the PI feedback controller

Combining vibrational linear-by-part dynamics and kinetic-based decoupling of the dynamics for multiple elastoplastic smooth impacts

Energy Technology Data Exchange (ETDEWEB)

Barjau, Ana, E-mail: ana.barjau@upc.edu; Batlle, Joaquim A., E-mail: agullo.batlle@upc.edu; Font-Llagunes, Josep M., E-mail: josep.m.font@upc.edu [Universitat Politècnica de Catalunya, Department of Mechanical Engineering and Biomedical Engineering Research Centre (Spain)

2015-11-15

This article proposes a linear-by-part approach for elastoplastic 3D multiple-point smooth impacts in multibody systems with perfect constraints. The model is an extension of a previous version, restricted to the perfectly elastic case, able to account for the high sensitivity to initial conditions and for redundancy without assuming any particular collision sequence (Barjau et al., Multibody Syst. Dyn. 31:497–517, 2014). Energy losses associated with compression and expansion in percussive analysis is a matter as complex as the physical phenomena involved, at the nanoscale level, for different materials. Simplified models can be developed for specific purposes, which can retain the most relevant trends of internal damping and at the same time be suitable for a particular analytical approach of impact mechanics. In the context of this article, energy dissipation due to material deformation is introduced through a linear-by-part elastoplastic model consisting on two elementary sets of springs and dry-friction dampers. The first set accounts for inelastic behavior (energy loss without permanent indentation), whereas the second one introduces plasticity (that is, permanent indentation). In inelastic and plastic collisions, instantaneous unilateral constraints may appear, thus reducing the number of degrees of freedom (DOF) of the system. The calculation of the corresponding normal contact force at the constrained points is then necessary in order to detect whether the constraint holds or disappears (either because a new compression or an expansion phase starts, or because contact is lost). Different simulated application examples are presented and thoroughly discussed.

Methods in half-linear asymptotic theory

Czech Academy of Sciences Publication Activity Database

Řehák, Pavel

2016-01-01

Roč. 2016, Č. 267 (2016), s. 1-27 ISSN 1072-6691 Institutional support: RVO:67985840 Keywords : half-linear differential equation * nonoscillatory solution * regular variation Subject RIV: BA - General Mathematics Impact factor: 0.954, year: 2016 http://ejde.math.txstate.edu/Volumes/2016/267/abstr.html

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of

Simultaneous Balancing and Model Reduction of Switched Linear Systems

OpenAIRE

Monshizadeh, Nima; Trentelman, Hendrikus; Camlibel, M.K.

2011-01-01

In this paper, first, balanced truncation of linear systems is revisited. Then, simultaneous balancing of multiple linear systems is investigated. Necessary and sufficient conditions are introduced to identify the case where simultaneous balancing is possible. The validity of these conditions is not limited to a certain type of balancing, and they are applicable for different types of balancing corresponding to different equations, like Lyapunov or Riccati equations. The results obtained are ...

Distributed Fusion Estimation for Multisensor Multirate Systems with Stochastic Observation Multiplicative Noises

Directory of Open Access Journals (Sweden)

Peng Fangfang

2014-01-01

Full Text Available This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.

The multiplication constant of a microorganism in a colony is normally reduced by irradiation, but still remains as a characteristic constant: a new approach to determining irradiation pasteurization doses

International Nuclear Information System (INIS)

Yarman, T.; Kiyak, N.

1991-01-01

This work is based on a previous observation and on a related mathematical modeling regarding the ‘linear growth’ of a colony of microorganisms under given conditions. We had previously shown that the growth rate of the colony is merely proportional to the ‘individual exponential multiplication constant’, β, of the microorganisms. Tiny colonies of penicillium are subjected to different doses of irradiation. The subsequent observation of the colonies' growth rate beautifully furnishes a measure of how the multiplication constant, β, of the microorganism is affected by irradiation. The plot of β with respect to the irradiation dose, shows a linear interdependence between the two quantities. The extrapolation of this plot easily yields the radiation pasteurization dose of the microorganisms in hand

Learning a common dictionary for subject-transfer decoding with resting calibration.

Science.gov (United States)

Morioka, Hiroshi; Kanemura, Atsunori; Hirayama, Jun-ichiro; Shikauchi, Manabu; Ogawa, Takeshi; Ikeda, Shigeyuki; Kawanabe, Motoaki; Ishii, Shin

2015-05-01

Brain signals measured over a series of experiments have inherent variability because of different physical and mental conditions among multiple subjects and sessions. Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain-machine interface (BMI). To accommodate the variability in brain signals, we propose 1) a method for extracting spatial bases (or a dictionary) shared by multiple subjects, by employing a signal-processing technique of dictionary learning modified to compensate for variations between subjects and sessions, and 2) an approach to subject-transfer decoding that uses the resting-state activity of a previously unseen target subject as calibration data for compensating for variations, eliminating the need for a standard calibration based on task sessions. Applying our methodology to a dataset of electroencephalography (EEG) recordings during a selective visual-spatial attention task from multiple subjects and sessions, where the variability compensation was essential for reducing the redundancy of the dictionary, we found that the extracted common brain activities were reasonable in the light of neuroscience knowledge. The applicability to subject-transfer decoding was confirmed by improved performance over existing decoding methods. These results suggest that analyzing multisubject brain activities on common bases by the proposed method enables information sharing across subjects with low-burden resting calibration, and is effective for practical use of BMI in variable environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Linear Processing Design of Amplify-and-Forward Relays for Maximizing the System Throughput

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Qiang Wang

2018-01-01

Full Text Available In this paper, firstly, we study the linear processing of amplify-and-forward (AF relays for the multiple relays multiple users scenario. We regard all relays as one special “relay”, and then the subcarrier pairing, relay selection and channel assignment can be seen as a linear processing of the special “relay”. Under fixed power allocation, the linear processing of AF relays can be regarded as a permutation matrix. Employing the partitioned matrix, we propose an optimal linear processing design for AF relays to find the optimal permutation matrix based on the sorting of the received SNR over the subcarriers from BS to relays and from relays to users, respectively. Then, we prove the optimality of the proposed linear processing scheme. Through the proposed linear processing scheme, we can obtain the optimal subcarrier paring, relay selection and channel assignment under given power allocation in polynomial time. Finally, we propose an iterative algorithm based on the proposed linear processing scheme and Lagrange dual domain method to jointly optimize the joint optimization problem involving the subcarrier paring, relay selection, channel assignment and power allocation. Simulation results illustrate that the proposed algorithm can achieve a perfect performance.

Neuropsychological Performance and Subjective Symptom Reporting in Military Service Members With a History of Multiple Concussions: Comparison With a Single Concussion, Posttraumatic Stress Disorder, and Orthopedic Trauma.

Science.gov (United States)

Cooper, Douglas B; Curtiss, Glenn; Armistead-Jehle, Patrick; Belanger, Heather G; Tate, David F; Reid, Matthew; Bowles, Amy O; Velez, Carmen S; Kennedy, Jan E; Vanderploeg, Rodney D

To examine differences in objective neurocognitive performance and subjective cognitive symptoms in individuals with a history of a single concussion, multiple concussions, orthopedic injuries, and posttraumatic stress disorder (PTSD). Participants included 116 military service members who sustained a mild traumatic brain injury (mTBI) during combat deployment. Subjects were subdivided into groups based on concussion frequency: a single concussion (n = 42), 2 concussions (n = 21), and 3 or more concussions (n = 53). Eighty-one subjects sustained an orthopedic injury (n = 60) during deployment or were diagnosed with PTSD (n = 21), but had no history of mTBI. Subjects completed a battery of neuropsychological tests and self-report measures of postconcussive symptoms, PTSD symptoms, and psychopathology. No differences were found among the concussion groups on a composite neuropsychological measure. The PTSD group had the highest number of symptom complaints, with the 2-concussion and 3-plus-concussion groups being most similar to the PTSD group. The concussion groups showed a nonsignificant pattern of increasing distress with increasing number of concussions. The current findings are consistent with meta-analytic results showing no differential effect on neuropsychological functioning due to multiple concussions. Results also support the burden of adversity hypothesis suggesting increasing symptom levels with increasing psychological or physically traumatic exposures.

On index-2 linear implicit difference equations

NARCIS (Netherlands)

Nguyen Huu Du, [No Value; Le Cong Loi, [No Value; Trinh Khanh Duy, [No Value; Vu Tien Viet, [No Value

2011-01-01

This paper deals with an index-2 notion for linear implicit difference equations (LIDEs) and with the solvability of initial value problems (IVPs) for index-2 LIDEs. Besides, the cocycle property as well as the multiplicative ergodic theorem of Oseledets type are also proved. (C) 2010 Elsevier Inc.

Noise limitations in optical linear algebra processors.

Science.gov (United States)

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

1990-05-10

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

State-dependent linear-optical qubit amplifier

Czech Academy of Sciences Publication Activity Database

Bartkiewicz, K.; Černoch, Antonín; Lemr, K.

2013-01-01

Roč. 88, č. 6 (2013), "062304-1"-"062304-7" ISSN 1050-2947 R&D Projects: GA ČR GAP205/12/0382 Institutional support: RVO:68378271 Keywords : linear-optical qubit amplifier * quantum cloning * quantum cryptography Subject RIV: BH - Optics, Masers, Lasers Impact factor: 2.991, year: 2013

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this

Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

Science.gov (United States)

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.

QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

Science.gov (United States)

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.

Using hierarchical linear models to test differences in Swedish results from OECD’s PISA 2003: Integrated and subject-specific science education

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.

Subjective memory complaints among patients on sick leave are associated with symptoms of fatigue and anxiety

Directory of Open Access Journals (Sweden)

Julie Kristine Aasvik

2015-09-01

Full Text Available Abstract: Objective: The aim of this study was to identify symptoms associated with subjective memory complaints among subjects who are currently on sick leave due to symptoms of chronic pain, fatigue, depression, anxiety and insomnia. Methods: This was a cross-sectional study, subjects (n = 167 who were currently on sick leave were asked to complete an extensive survey consisting of the following: items addressing their sociodemographics, one item from the SF-8 health survey measuring pain, Chalder Fatigue Questionnaire, Hospital Anxiety and Depression Scale, Insomnia Severity Index and Everyday Memory Questionnaire – Revised. General linear modeling (GLM was used to analyze variables associated with SMCs. Results: Symptoms of fatigue (p-value <= 0.001 and anxiety (p-value = 0.001 were uniquely and significantly associated with perceived memory failures. The associations with symptoms of pain, depression and insomnia were not statistically significant. Conclusions: Subjective memory complaints should be recognized as part of the complex symptomatology among patients who report multiple symptoms, especially in cases of fatigue and anxiety. Self-report questionnaires measuring perceived memory failures may be a quick and easy way to incorporate and extend this knowledge into clinical practice.

Multiple Linear Regression Analysis Indicates Association of P-Glycoprotein Substrate or Inhibitor Character with Bitterness Intensity, Measured with a Sensor.

Science.gov (United States)

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.

Right ventricular ejection fraction during exercise in normal subjects and in coronary artery disease patients: assessment by multiple-gated equilibrium scintigraphy

International Nuclear Information System (INIS)

Maddahi, J.; Berman, D.S.; Matsuoka, D.T.; Waxman, A.D.; Forrester, J.S.; Swan, H.J.C.

1980-01-01

The response of right ventricular ejection fraction (RVEF) during exercise and its relationship to the location and extent of coronary artery disease are not fully understood. We have recently developed and validated a new method for scintigraphic evaluation of RVEF using rapid multiple-gated equilibrium scintigraphy and multiple right ventricular regions of interest. The technique has been applied during upright bicycle exercise in 10 normal subjects and 20 patients with coronary artery disease. Resting RVEF was not significantly different between the groups (0.49 +- 0.04 vs 0.47 +- 0.09, respectively, mean +- SD). In all 10 normal subjects RVEF rose (0.49 +- 0.04 to 0.66 +- 0.08, p < 0.01) at peak exercise. At peak exercise in coronary artery disease patients, the group RVEF remained unchanged (0.47 +- 0.09 to 0.50 +- 0.11, p = NS), but the individual responses varied. In the coronary artery disease patients, the relationship between RVEF response to exercise and exercise left ventricular function, septal motion and right coronary artery stenosis were studied. Significant statistical association was found only between exercise RVEF and right coronary artery stenosis. RVEF rose during exercise in seven of seven patients without right coronary artery stenosis (0.42 +- 0.06 to 0.58 +- 0.08, p = 0.001) and was unchanged or fell in 12 of 13 patients with right coronary artery stenosis (0.50 +- 0.09 to 0.45 +- 0.10, p = NS). We conclude that (1) in normal subjects RVEF increases during upright exercise and (2) although RVEF at rest is not necessarily affected by coronary artery disease, failure of RVEF to increase during exercise, in the absence of chronic obstructive pulmonary disease or valvular heart disease, may be related to the presence of significant right coronary artery stenosis

Right ventricular ejection fraction during exercise in normal subjects and in coronary artery disease patients: assessment by multiple-gated equilibrium scintigraphy

Energy Technology Data Exchange (ETDEWEB)

Maddahi, J.; Berman, D.S.; Matsuoka, D.T.; Waxman, A.D.; Forrester, J.S.; Swan, H.J.C.

1980-07-01

The response of right ventricular ejection fraction (RVEF) during exercise and its relationship to the location and extent of coronary artery disease are not fully understood. We have recently developed and validated a new method for scintigraphic evaluation of RVEF using rapid multiple-gated equilibrium scintigraphy and multiple right ventricular regions of interest. The technique has been applied during upright bicycle exercise in 10 normal subjects and 20 patients with coronary artery disease. Resting RVEF was not significantly different between the groups (0.49 +- 0.04 vs 0.47 +- 0.09, respectively, mean +- SD). In all 10 normal subjects RVEF rose (0.49 +- 0.04 to 0.66 +- 0.08, p < 0.01) at peak exercise. At peak exercise in coronary artery disease patients, the group RVEF remained unchanged (0.47 +- 0.09 to 0.50 +- 0.11, p = NS), but the individual responses varied. In the coronary artery disease patients, the relationship between RVEF response to exercise and exercise left ventricular function, septal motion and right coronary artery stenosis were studied. Significant statistical association was found only between exercise RVEF and right coronary artery stenosis. RVEF rose during exercise in seven of seven patients without right coronary artery stenosis (0.42 +- 0.06 to 0.58 +- 0.08, p = 0.001) and was unchanged or fell in 12 of 13 patients with right coronary artery stenosis (0.50 +- 0.09 to 0.45 +- 0.10, p = NS). We conclude that (1) in normal subjects RVEF increases during upright exercise and (2) although RVEF at rest is not necessarily affected by coronary artery disease, failure of RVEF to increase during exercise, in the absence of chronic obstructive pulmonary disease or valvular heart disease, may be related to the presence of significant right coronary artery stenosis.

Subjective Expected Utility Theory without States of the World

OpenAIRE

Edi Karni

2005-01-01

This paper develops an axiomatic theory of decision making under uncertainty that dispenses with the state space. The results are subjective expected utility models with unique, action-dependent, subjective probabilities, and a utility function defined over wealth-effect pairs that is unique up to positive linear transformation.

Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects?

Directory of Open Access Journals (Sweden)

Lu Liping

2011-01-01

Full Text Available Abstract Background Obesity is associated with metabolic risk factors. Body mass index (BMI, waist circumference, waist-hip ratio (WHR and waist-height ratio (WHtR are used to predict the risk of obesity related diseases. However, it has not been examined whether these four indicators can detect the clustering of metabolic risk factors in Chinese subjects. Methods There are 772 Chinese subjects in the present study. Metabolic risk factors including high blood pressure, dyslipidemia, and glucose intolerance were identified according to the criteria from WHO. All statistical analyses were performed separately according to sex by using the SPSS 12.0. Results BMI, waist circumference and WHtR values were all significantly associated with blood pressure, glucose, triglyceride and also with the number of metabolic risk factors in both male and female subjects (all of P Conclusion The BMI, waist circumference and WHtR values can similarly predict the presence of multiple metabolic risk factors in Chinese subjects.

Janus field theories from non-linear BF theories for multiple M2-branes

International Nuclear Information System (INIS)

Ryang, Shijong

2009-01-01

We integrate the nonpropagating B μ gauge field for the non-linear BF Lagrangian describing N M2-branes which includes terms with even number of the totally antisymmetric tensor M IJK in arXiv:0808.2473 and for the two-types of non-linear BF Lagrangians which include terms with odd number of M IJK as well in arXiv:0809:0985. For the former Lagrangian we derive directly the DBI-type Lagrangian expressed by the SU(N) dynamical A μ gauge field with a spacetime dependent coupling constant, while for the low-energy expansions of the latter Lagrangians the B μ integration is iteratively performed. The derived Janus field theory Lagrangians are compared.

Weak regularizability and pole assignment for non-square linear systems

Czech Academy of Sciences Publication Activity Database

Korotka, Tetiana; Loiseau, J. J.; Zagalak, Petr

2012-01-01

Roč. 48, č. 6 (2012), s. 1065-1088 ISSN 0023-5954 R&D Projects: GA ČR GAP103/12/2431 Keywords : linear systems * linear state feedback * pole assignment Subject RIV: BC - Control Systems Theory Impact factor: 0.619, year: 2012 http://library.utia.cas.cz/separaty/2013/AS/korotka-0386325.pdf

Robustness of Linear Systems towards Multi-Dissipative Pertubations

DEFF Research Database (Denmark)

Thygesen, Uffe Høgsbro; Poulsen, Niels Kjølstad

1997-01-01

We consider the question of robust stability of a linear time invariant plant subject to dynamic perturbations, which are dissipative in the sense of Willems with respect to several quadratic supply rates. For instance, parasitic dynamics are often both small gain and passive. We reduce several...... robustness analysis questions to linear matrix inequalities: robust stability, robust H2 performance and robust performance in presence of disturbances with finite signal-to-noise ratios...

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

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

Science.gov (United States)

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

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

Depression and fatigue in patients with multiple sclerosis.

Science.gov (United States)

Greeke, Emily E; Chua, Alicia S; Healy, Brian C; Rintell, David J; Chitnis, Tanuja; Glanz, Bonnie I

2017-09-15

Previous research has examined the components of depression and fatigue in multiple sclerosis (MS), but the findings have been inconsistent. The aim of this study was to explore the associations between overall and subscale scores of the Center for Epidemiologic Studies-Depression Scale (CES-D) and the Modified Fatigue Impact Scale (MFIS) as well as the longitudinal changes in scores in a large cohort of MS patients. MS subjects who completed a battery of patient reported outcome (PRO) measures including the CES-D and MFIS (N=435) were included in our analysis. At the first available MFIS measurement, Pearson's correlation coefficient was used to estimate the association between the CES-D and MFIS in terms of both total scores and subscale scores. In addition, the longitudinal change in each total score and subscale score was estimated using a linear mixed model, and the association between the measures in terms of longitudinal change was estimated using Pearson's correlation coefficient and linear mixed models. At baseline, 15% of subjects were classified as high on both depression and fatigue scales, 16% were classified as high on the fatigue scale only, and 9% were classified as high on the depression scale only. There was a high correlation between CES-D and MFIS total scores (r=0.62). High correlations were also observed between the somatic and retarded activity subscales of the CES-D and each of the MFIS subscales (r≥0.60). In terms of longitudinal change, the change over the first year between the CES-D and MFIS total scores showed a moderate correlation (r=0.49). Subjects with high fatigue scores but low depression scores at baseline were more likely than subjects with low baseline fatigue and depression scores to develop high depression scores at follow-up. Our study demonstrated that depression and fatigue in MS share several features and have a similar longitudinal course. But using cut-off scores to define depression and fatigue, our study also found

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

Science.gov (United States)

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.

Social Identity Mapping: A procedure for visual representation and assessment of subjective multiple group memberships.

Science.gov (United States)

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.

Nonlinear dynamic response of whole pool multiple spent fuel racks subject to three-dimensional excitations

International Nuclear Information System (INIS)

Zhao, Y.; Wilson, P.R.; Stevenson, J.D.

1995-01-01

The seismic evaluation of submerged free standing spent fuel storage racks is more complicated than most other nuclear structural systems. When subjected to three dimensional (3-D) floor seismic excitations the dynamic responses of racks in a pool are hydro dynamically coupled with each other, with the fuel assemblies water in gaps. The motion behavior of the racks is significantly different from that observed using a 3D single rack mode. Few seismic analyses using 3-D whole pool multiple rack models are available in the literature. I this paper an analysis was performed for twelve racks using potential theory for the fluid-structure interaction, and using a 3-D whole pool multi-rack finite element model developed herein. The analysis includes the potential nonlinear dynamic behavior of the impact of fuel-rack, rack-rack and rack-pool wall, the tilting or uplift and the frictional sliding of rack supports, and the impact of the rack supports to the pool floor. (author). 12 refs., 7 figs., 1 tab

Influence of plant root morphology and tissue composition on phenanthrene uptake: Stepwise multiple linear regression analysis

International Nuclear Information System (INIS)

Zhan, Xinhua; Liang, Xiao; Xu, Guohua; Zhou, Lixiang

2013-01-01

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. -- Highlights: •There is no correlation between phenanthrene uptake and total root length, and water. •Specific surface area and lipid are the most crucial factors for phenanthrene uptake. •The contribution of specific surface area is greater than that of lipid. -- The contribution of specific surface area is greater than that of lipid in the two most important root morphological and compositional factors affecting phenanthrene uptake

Multiple linear regression to develop strength scaled equations for knee and elbow joints based on age, gender and segment mass

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...... 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 (PGender, thigh mass and age best...... predicted KPT (R2=0.60). Gender, forearm mass and age best predicted EPT (R2=0.75). Good crossvalidation was established for both elbow and knee models. Conclusion: This cross-sectional study of muscle strength created and validated strength scaled equations of EPT and KPT using only gender, segment mass...

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

Science.gov (United States)

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

2015-01-01

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

Pharmacokinetics of rilmenidine in healthy subjects

International Nuclear Information System (INIS)

Genissel, P.; Bromet, N.; Fourtillan, J.B.; Mignot, A.; Albin, H.

1988-01-01

Rilmenidine is a novel alpha 2-adrenoceptor agonist, used in the treatment of mild or moderate hypertension at the oral dose of 1 mg once or twice daily. The pharmacokinetic parameters were investigated after single or repeated administration in healthy subjects, using labeled and unlabeled compounds. Rilmenidine was rapidly and extensively absorbed, with an absolute bioavailability factor close to 1 and a maximal plasma concentration achieved within 2 hours. Rilmenidine was not subject to presystemic metabolism. Distribution was independent of the free fraction because rilmenidine was weakly bound to plasma proteins (less than 10%). The volume of distribution was approximately 5 l.kg-1 (315 liters). Elimination was rapid with a total body plasma clearance of approximately 450 ml.min-1 and an elimination half-life of approximately 8 hours. Renal excretion was the major elimination process (two-thirds of the total clearance). Metabolism was very poor, with a renal elimination of rilmenidine as the parent drug (urinary fraction of rilmenidine was about 65% and no metabolite plasma levels were detected). Linear pharmacokinetics were demonstrated for rilmenidine from 0.5 to 2 mg but, at 3 mg, a slight deviation from linearity was observed. In repeated administration, the linear disposition of rilmenidine with dose was confirmed

Formalized Linear Algebra over Elementary Divisor Rings in Coq

OpenAIRE

Cano , Guillaume; Cohen , Cyril; Dénès , Maxime; Mörtberg , Anders; Siles , Vincent

2016-01-01

International audience; This paper presents a Coq formalization of linear algebra over elementary divisor rings, that is, rings where every matrix is equivalent to a matrix in Smith normal form. The main results are the formalization that these rings support essential operations of linear algebra, the classification theorem of finitely pre-sented modules over such rings and the uniqueness of the Smith normal form up to multiplication by units. We present formally verified algorithms comput-in...

The role of dendritic non-linearities in single neuron computation

Directory of Open Access Journals (Sweden)

Boris Gutkin

2014-05-01

Full Text Available Experiment has demonstrated that summation of excitatory post-synaptic protientials (EPSPs in dendrites is non-linear. The sum of multiple EPSPs can be larger than their arithmetic sum, a superlinear summation due to the opening of voltage-gated channels and similar to somatic spiking. The so-called dendritic spike. The sum of multiple of EPSPs can also be smaller than their arithmetic sum, because the synaptic current necessarily saturates at some point. While these observations are well-explained by biophysical models the impact of dendritic spikes on computation remains a matter of debate. One reason is that dendritic spikes may fail to make the neuron spike; similarly, dendritic saturations are sometime presented as a glitch which should be corrected by dendritic spikes. We will provide solid arguments against this claim and show that dendritic saturations as well as dendritic spikes enhance single neuron computation, even when they cannot directly make the neuron fire. To explore the computational impact of dendritic spikes and saturations, we are using a binary neuron model in conjunction with Boolean algebra. We demonstrate using these tools that a single dendritic non-linearity, either spiking or saturating, combined with somatic non-linearity, enables a neuron to compute linearly non-separable Boolean functions (lnBfs. These functions are impossible to compute when summation is linear and the exclusive OR is a famous example of lnBfs. Importantly, the implementation of these functions does not require the dendritic non-linearity to make the neuron spike. Next, We show that reduced and realistic biophysical models of the neuron are capable of computing lnBfs. Within these models and contrary to the binary model, the dendritic and somatic non-linearity are tightly coupled. Yet we show that these neuron models are capable of linearly non-separable computations.

Multiple linear regression and artificial neural networks for delta-endotoxin and protease yields modelling of Bacillus thuringiensis.

Science.gov (United States)

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.

Electron non-linearities in Langmuir waves with application to beat-wave experiments

International Nuclear Information System (INIS)

Bell, A.R.; Gibbon, P.

1988-01-01

Non-linear Langmuir waves are examined in the context of the beat-wave accelerator. With a background of immobile ions the waves in one dimension are subject to the relativistic non-linearity of Rosenbluth, M.N. and Liu, C.S., Phys. Rev. Lett., 1972, 29, 701. In two or three dimensions, other electron non-linearities occur which involve electric and magnetic fields. The quasi-linear equations for these non-linearities are developed and solved numerically in a geometry representative of laser-driven beat waves. (author)

40 CFR 721.10143 - Amines, bis (C11-14-branched and linear alkyl).

Science.gov (United States)

2010-07-01

... linear alkyl). 721.10143 Section 721.10143 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Specific Chemical Substances § 721.10143 Amines, bis (C11-14-branched and linear alkyl). (a) Chemical..., bis (C11-14-branched and linear alkyl) (PMN P-06-733; CAS No. 900169-60-0) is subject to reporting...

40 CFR 721.2088 - Carboxylic acids, (C6-C9) branched and linear.

Science.gov (United States)

2010-07-01

... linear. 721.2088 Section 721.2088 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... Specific Chemical Substances § 721.2088 Carboxylic acids, (C6-C9) branched and linear. (a) Chemical... as carboxylic acids, (C6-C9) branched and linear (PMNs P-93-313, 314, 315, and 316) are subject to...

The influence of non-linear frequency compression on the perception of music by adults with a moderate to sever hearing loss: subjective impressions.

Science.gov (United States)

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.

The influence of non-linear frequency compression on the perception of music by adults with a moderate to severe hearing loss: Subjective impressions

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.

Beamstrahlung spectra in next generation linear colliders. Revision

Energy Technology Data Exchange (ETDEWEB)

Barklow, T.; Chen, P. [Stanford Linear Accelerator Center, Menlo Park, CA (United States); Kozanecki, W. [DAPNIA-SPP, CEN-Saclay (France)

1992-04-01

For the next generation of linear colliders, the energy loss due to beamstrahlung during the collision of the e{sup +}e{sup {minus}} beams is expected to substantially influence the effective center-of-mass energy distribution of the colliding particles. In this paper, we first derive analytical formulae for the electron and photon energy spectra under multiple beamstrahlung processes, and for the e{sup +}e{sup {minus}} and {gamma}{gamma} differential luminosities. We then apply our formulation to various classes of 500 GeV e{sup +}e{sup {minus}} linear collider designs currently under study.

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease

Directory of Open Access Journals (Sweden)

Xiaoli Liu

2018-01-01

Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.

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

Science.gov (United States)

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

2013-01-01

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

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

Science.gov (United States)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

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.

Mediation Analysis with Multiple Mediators

OpenAIRE

VanderWeele, T.J.; Vansteelandt, S.

2014-01-01

Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects throu...

Automated longitudinal intra-subject analysis (ALISA) for diffusion MRI tractography

DEFF Research Database (Denmark)

Aarnink, Saskia H; Vos, Sjoerd B; Leemans, Alexander

2014-01-01

the inter-subject and intra-subject automation in this situation are intended for subjects without gross pathology. In this work, we propose such an automated longitudinal intra-subject analysis (dubbed ALISA) approach, and assessed whether ALISA could preserve the same level of reliability as obtained....... The major disadvantage of manual FT segmentations, unfortunately, is that placing regions-of-interest for tract selection can be very labor-intensive and time-consuming. Although there are several methods that can identify specific WM fiber bundles in an automated way, manual FT segmentations across...... multiple subjects performed by a trained rater with neuroanatomical expertise are generally assumed to be more accurate. However, for longitudinal DTI analyses it may still be beneficial to automate the FT segmentation across multiple time points, but then for each individual subject separately. Both...

Is Walking Capacity in Subjects with Multiple Sclerosis Primarily Related to Muscle Oxidative Capacity or Maximal Muscle Strength? A Pilot Study

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.

The Implementation of APIQ Creative Mathematics Game Method in the Subject Matter of Greatest Common Factor and Least Common Multiple in Elementary School

Science.gov (United States)

Rahman, Abdul; Saleh Ahmar, Ansari; Arifin, A. Nurani M.; Upu, Hamzah; Mulbar, Usman; Alimuddin; Arsyad, Nurdin; Ruslan; Rusli; Djadir; Sutamrin; Hamda; Minggi, Ilham; Awi; Zaki, Ahmad; Ahmad, Asdar; Ihsan, Hisyam

2018-01-01

One of causal factors for uninterested feeling of the students in learning mathematics is a monotonous learning method, like in traditional learning method. One of the ways for motivating students to learn mathematics is by implementing APIQ (Aritmetika Plus Intelegensi Quantum) creative mathematics game method. The purposes of this research are (1) to describe students’ responses toward the implementation of APIQ creative mathematics game method on the subject matter of Greatest Common Factor (GCF) and Least Common Multiple (LCM) and (2) to find out whether by implementing this method, the student’s learning completeness will improve or not. Based on the results of this research, it is shown that the responses of the students toward the implementation of APIQ creative mathematics game method in the subject matters of GCF and LCM were good. It is seen in the percentage of the responses were between 76-100%. (2) The implementation of APIQ creative mathematics game method on the subject matters of GCF and LCM improved the students’ learning.

Toward Customer-Centric Organizational Science: A Common Language Effect Size Indicator for Multiple Linear Regressions and Regressions With Higher-Order Terms.

Science.gov (United States)

Krasikova, Dina V; Le, Huy; Bachura, Eric

2018-01-22

To address a long-standing concern regarding a gap between organizational science and practice, scholars called for more intuitive and meaningful ways of communicating research results to users of academic research. In this article, we develop a common language effect size index (CLβ) that can help translate research results to practice. We demonstrate how CLβ can be computed and used to interpret the effects of continuous and categorical predictors in multiple linear regression models. We also elaborate on how the proposed CLβ index is computed and used to interpret interactions and nonlinear effects in regression models. In addition, we test the robustness of the proposed index to violations of normality and provide means for computing standard errors and constructing confidence intervals around its estimates. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A point-wise fiber Bragg grating displacement sensing system and its application for active vibration suppression of a smart cantilever beam subjected to multiple impact loadings

International Nuclear Information System (INIS)

Chuang, Kuo-Chih; Ma, Chien-Ching; Liao, Heng-Tseng

2012-01-01

In this work, active vibration suppression of a smart cantilever beam subjected to disturbances from multiple impact loadings is investigated with a point-wise fiber Bragg grating (FBG) displacement sensing system. An FBG demodulator is employed in the proposed fiber sensing system to dynamically demodulate the responses obtained by the FBG displacement sensor with high sensitivity. To investigate the ability of the proposed FBG displacement sensor as a feedback sensor, velocity feedback control and delay control are employed to suppress the vibrations of the first three bending modes of the smart cantilever beam. To improve the control performance for the first bending mode when the cantilever beam is subjected to an impact loading, we improve the conventional velocity feedback controller by tuning the control gain online with the aid of information from a higher vibration mode. Finally, active control of vibrations induced by multiple impact loadings due to a plastic ball is performed with the improved velocity feedback control. The experimental results show that active vibration control of smart structures subjected to disturbances such as impact loadings can be achieved by employing the proposed FBG sensing system to feed back out-of-plane point-wise displacement responses with high sensitivity. (paper)

Subjective cognitive complaints, psychosocial factors and nursing work function in nurses providing direct patient care.

Science.gov (United States)

Barbe, Tammy; Kimble, Laura P; Rubenstein, Cynthia

2018-04-01

The aim of this study was to examine relationships among subjective cognitive complaints, psychosocial factors and nursing work function in nurses providing direct patient care. Cognitive functioning is a critical component for nurses in the assurance of error prevention, identification and correction when caring for patients. Negative changes in nurses' cognitive and psychosocial functioning can adversely affect nursing care and patient outcomes. A descriptive correlational design with stratified random sampling. The sample included 96 nurses from the major geographic regions of the United States. Over 9 months in 2016-2017, data were collected using a web-based survey. Stepwise multiple linear regression analyses were used to examine relationships among subjective cognitive complaints, psychosocial factors and nursing work function. Overall, participants reported minimal work function impairment and low levels of subjective cognitive complaints, depression and stress. In multivariate analyses, depression was not associated with nurses' work function. However, perceived stress and subjective concerns about cognitive function were associated with greater impairment of work function. Nurses experiencing subjective cognitive complaints should be encouraged to address personal and environmental factors that are associated with their cognitive status. Additionally, stress reduction in nurses should be a high priority as a potential intervention to promote optimal functioning of nurses providing direct patient care. Healthcare institutions should integrate individual and institutional strategies to reduce factors contributing to workplace stress. © 2017 John Wiley & Sons Ltd.

Characteristics and Properties of a Simple Linear Regression Model

Directory of Open Access Journals (Sweden)

Kowal Robert

2016-12-01

Full Text Available A simple linear regression model is one of the pillars of classic econometrics. Despite the passage of time, it continues to raise interest both from the theoretical side as well as from the application side. One of the many fundamental questions in the model concerns determining derivative characteristics and studying the properties existing in their scope, referring to the first of these aspects. The literature of the subject provides several classic solutions in that regard. In the paper, a completely new design is proposed, based on the direct application of variance and its properties, resulting from the non-correlation of certain estimators with the mean, within the scope of which some fundamental dependencies of the model characteristics are obtained in a much more compact manner. The apparatus allows for a simple and uniform demonstration of multiple dependencies and fundamental properties in the model, and it does it in an intuitive manner. The results were obtained in a classic, traditional area, where everything, as it might seem, has already been thoroughly studied and discovered.

Leaf area estimation of cassava from linear dimensions

Directory of Open Access Journals (Sweden)

SAMARA ZANETTI

2017-08-01

Full Text Available ABSTRACT The objective of this study was to determine predictor models of leaf area of cassava from linear leaf measurements. The experiment was carried out in greenhouse in the municipality of Botucatu, São Paulo state, Brazil. The stem cuttings with 5-7 nodes of the cultivar IAC 576-70 were planted in boxes filled with about 320 liters of soil, keeping soil moisture at field capacity, monitored by puncturing tensiometers. At 80 days after planting, 140 leaves were randomly collected from the top, middle third and base of cassava plants. We evaluated the length and width of the central lobe of leaves, number of lobes and leaf area. The measurements of leaf areas were correlated with the length and width of the central lobe and the number of lobes of the leaves, and adjusted to polynomial and multiple regression models. The linear function that used the length of the central lobe LA = -69.91114 + 15.06462L and linear multiple functions LA = -69.9188 + 15.5102L + 0.0197726K - 0.0768998J or LA = -69.9346 + 15.0106L + 0.188931K - 0.0264323H are suitable models to estimate leaf area of cassava cultivar IAC 576-70.

Pharmacokinetics of colistin methanesulfonate (CMS) in healthy Chinese subjects after single and multiple intravenous doses.

Science.gov (United States)

Zhao, Miao; Wu, Xiao-Jie; Fan, Ya-Xin; Zhang, Ying-Yuan; Guo, Bei-Ning; Yu, Ji-Cheng; Cao, Guo-Ying; Chen, Yuan-Cheng; Wu, Ju-Fang; Shi, Yao-Guo; Li, Jian; Zhang, Jing

2018-05-01

The high prevalence of extensively drug-resistant Gram-negative pathogens has forced clinicians to use colistin as a last-line therapy. Knowledge on the pharmacokinetics of colistin methanesulfonate (CMS), an inactive prodrug, and colistin has increased substantially; however, the pharmacokinetics in the Chinese population is still unknown due to lack of a CMS product in China. This study aimed to evaluate the pharmacokinetics of a new CMS product developed in China in order to optimise dosing regimens. A total of 24 healthy subjects (12 female, 12 male) were enrolled in single- and multiple-dose pharmacokinetic (PK) studies. Concentrations of CMS and formed colistin in plasma and urine were measured, and PK analysis was conducted using a non-compartmental approach. Following a single CMS dose [2.36 mg colistin base activity (CBA) per kg, 1 h infusion], peak concentrations (C max ) of CMS and formed colistin were 18.0 mg/L and 0.661 mg/L, respectively. The estimated half-life (t 1/2 ) of CMS and colistin were 1.38 h and 4.49 h, respectively. Approximately 62.5% of the CMS dose was excreted via urine within 24 h after dosing, whilst only 1.28% was present in the form of colistin. Following multiple CMS doses, colistin reached steady-state within 24 h; there was no accumulation of CMS, but colistin accumulated slightly (R AUC  = 1.33). This study provides the first PK data in the Chinese population and is essential for designing CMS dosing regimens for use in Chinese hospitals. The urinary PK data strongly support the use of intravenous CMS for serious urinary tract infections. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

The development of multiple drug use among anabolic-androgenic steroid users: six subjective case reports

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.

Annotated bibliography on high-intensity linear accelerators. [240 citations

Energy Technology Data Exchange (ETDEWEB)

Jameson, R.A.; Roybal, E.U.

1978-01-01

A technical bibliography covering subjects important to the design of high-intensity beam transport systems and linear accelerators is presented. Space charge and emittance growth are stressed. Subject and author concordances provide cross-reference to detailed citations, which include an abstract and notes on the material. The bibliography resides in a computer database that can be searched for key words and phrases.

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

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.

Linear mixed models for longitudinal data

CERN Document Server

Molenberghs, Geert

2000-01-01

This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...

Axial linear patellar displacement: a new measurement of patellofemoral congruence.

Science.gov (United States)

Urch, Scott E; Tritle, Benjamin A; Shelbourne, K Donald; Gray, Tinker

2009-05-01

The tools for measuring the congruence angle with digital radiography software can be difficult to use; therefore, the authors sought to develop a new, easy, and reliable method for measuring patellofemoral congruence. The abstract goes here and covers two columns. The abstract goes The linear displacement measurement will correlate well with the congruence angle measurement. here and covers two columns. Cohort study (diagnosis); Level of evidence, 2. On Merchant view radiographs obtained digitally, the authors measured the congruence angle and a new linear displacement measurement on preoperative and postoperative radiographs of 31 patients who suffered unilateral patellar dislocations and 100 uninjured subjects. The linear displacement measurement was obtained by drawing a reference line across the medial and lateral trochlear facets. Perpendicular lines were drawn from the depth of the sulcus through the reference line and from the apex of the posterior tip of the patella through the reference line. The distance between the perpendicular lines was the linear displacement measurement. The measurements were obtained twice at different sittings. The observer was blinded as to the previous measurements to establish reliability. Measurements were compared to determine whether the linear displacement measurement correlated with congruence angle. Intraobserver reliability was above r(2) = .90 for all measurements. In patients with patellar dislocations, the mean congruence angle preoperatively was 33.5 degrees , compared with 12.1 mm for linear displacement (r(2) = .92). The mean congruence angle postoperatively was 11.2 degrees, compared with 4.0 mm for linear displacement (r(2) = .89). For normal subjects, the mean congruence angle was -3 degrees and the mean linear displacement was 0.2 mm. The linear displacement measurement was found to correlate with congruence angle measurements and may be an easy and useful tool for clinicians to evaluate patellofemoral

On Performance of Linear Multiuser Detectors for Wireless Multimedia Applications

Science.gov (United States)

Agarwal, Rekha; Reddy, B. V. R.; Bindu, E.; Nayak, Pinki

In this paper, performance of different multi-rate schemes in DS-CDMA system is evaluated. The analysis of multirate linear multiuser detectors with multiprocessing gain is analyzed for synchronous Code Division Multiple Access (CDMA) systems. Variable data rate is achieved by varying the processing gain. Our conclusion is that bit error rate for multirate and single rate systems can be made same with a tradeoff with number of users in linear multiuser detectors.

40 CFR 721.10103 - Naphtha (Fischer-Tropsch), C4-11-alkane, branched and linear.

Science.gov (United States)

2010-07-01

...-alkane, branched and linear. 721.10103 Section 721.10103 Protection of Environment ENVIRONMENTAL..., branched and linear. (a) Chemical substance and significant new uses subject to reporting. (1) The chemical substance identified as naphtha (fischer-tropsch), C4-11-alkane, branched and linear (PMN P-04-235; CAS No...

Asymptotic properties for half-linear difference equations

Czech Academy of Sciences Publication Activity Database

Cecchi, M.; Došlá, Z.; Marini, M.; Vrkoč, Ivo

2006-01-01

Roč. 131, č. 4 (2006), s. 347-363 ISSN 0862-7959 R&D Projects: GA ČR(CZ) GA201/04/0580 Institutional research plan: CEZ:AV0Z10190503 Keywords : half-linear second order difference equation * nonoscillatory solutions * Riccati difference equation Subject RIV: BA - General Mathematics

A non-linear dissipative model of magnetism

Czech Academy of Sciences Publication Activity Database

Durand, P.; Paidarová, Ivana

2010-01-01

Roč. 89, č. 6 (2010), s. 67004 ISSN 1286-4854 R&D Projects: GA AV ČR IAA100400501 Institutional research plan: CEZ:AV0Z40400503 Keywords : non-linear dissipative model of magnetism * thermodynamics * physical chemistry Subject RIV: CF - Physical ; Theoretical Chemistry http://epljournal.edpsciences.org/

régression linéaire multiple

African Journals Online (AJOL)

Mots clés: Alcools et phénols – Représentation numérique de la structure chimique – Facteur acentrique – Régression linéaire multiple – Modèle RSP hybride. English Title: Structure / acentric factor relationship of alcohols and phenols: genetic algorithm – multiple linear regression approach. English Abstract. The acentric ...

Increased prolactin levels are associated with impaired processing speed in subjects with early psychosis.

Science.gov (United States)

Montalvo, Itziar; Gutiérrez-Zotes, Alfonso; Creus, Marta; Monseny, Rosa; Ortega, Laura; Franch, Joan; Lawrie, Stephen M; Reynolds, Rebecca M; Vilella, Elisabet; Labad, Javier

2014-01-01

Hyperprolactinaemia, a common side effect of some antipsychotic drugs, is also present in drug-naïve psychotic patients and subjects at risk for psychosis. Recent studies in non-psychiatric populations suggest that increased prolactin may have negative effects on cognition. The aim of our study was to explore whether high plasma prolactin levels are associated with poorer cognitive functioning in subjects with early psychoses. We studied 107 participants: 29 healthy subjects and 78 subjects with an early psychosis (55 psychotic disorders with levels were determined as well as total cortisol levels in plasma. Psychopathological status was assessed and the use of psychopharmacological treatments (antipsychotics, antidepressants, benzodiazepines) recorded. Prolactin levels were negatively associated with cognitive performance in processing speed, in patients with a psychotic disorder and high-risk subjects. In the latter group, increased prolactin levels were also associated with impaired reasoning and problem solving and poorer general cognition. In a multiple linear regression analysis conducted in both high-risk and psychotic patients, controlling for potential confounders, prolactin and benzodiazepines were independently related to poorer cognitive performance in the speed of processing domain. A mediation analysis showed that both prolactin and benzodiazepine treatment act as mediators of the relationship between risperidone/paliperidone treatment and speed of processing. These results suggest that increased prolactin levels are associated with impaired processing speed in early psychosis. If these results are confirmed in future studies, strategies targeting reduction of prolactin levels may improve cognition in this population.

Eye movement desensitisation and reprocessing therapy for posttraumatic stress disorder in a child and an adolescent with mild to borderline intellectual disability: A multiple baseline across subjects study

NARCIS (Netherlands)

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

Eye movement desensitisation and reprocessing therapy for posttraumatic stress disorder in a child and an adolescent with mild to borderline intellectual disability : A multiple baseline across subjects study

NARCIS (Netherlands)

Mevissen, L.; Didden, R.; Korzilius, H.; de Jongh, A.

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

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...

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

Science.gov (United States)

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

Science.gov (United States)

Yang, Changju; Kim, Hyongsuk

2016-08-19

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

A Linear Electromagnetic Piston Pump

Science.gov (United States)

Hogan, Paul H.

Advancements in mobile hydraulics for human-scale applications have increased demand for a compact hydraulic power supply. Conventional designs couple a rotating electric motor to a hydraulic pump, which increases the package volume and requires several energy conversions. This thesis investigates the use of a free piston as the moving element in a linear motor to eliminate multiple energy conversions and decrease the overall package volume. A coupled model used a quasi-static magnetic equivalent circuit to calculate the motor inductance and the electromagnetic force acting on the piston. The force was an input to a time domain model to evaluate the mechanical and pressure dynamics. The magnetic circuit model was validated with finite element analysis and an experimental prototype linear motor. The coupled model was optimized using a multi-objective genetic algorithm to explore the parameter space and maximize power density and efficiency. An experimental prototype linear pump coupled pistons to an off-the-shelf linear motor to validate the mechanical and pressure dynamics models. The magnetic circuit force calculation agreed within 3% of finite element analysis, and within 8% of experimental data from the unoptimized prototype linear motor. The optimized motor geometry also had good agreement with FEA; at zero piston displacement, the magnetic circuit calculates optimized motor force within 10% of FEA in less than 1/1000 the computational time. This makes it well suited to genetic optimization algorithms. The mechanical model agrees very well with the experimental piston pump position data when tuned for additional unmodeled mechanical friction. Optimized results suggest that an improvement of 400% of the state of the art power density is attainable with as high as 85% net efficiency. This demonstrates that a linear electromagnetic piston pump has potential to serve as a more compact and efficient supply of fluid power for the human scale.

Introducing linear functions: an alternative statistical approach

Science.gov (United States)

Nolan, Caroline; Herbert, Sandra

2015-12-01

The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.

Use of Subjective Global Assessment, Patient-Generated Subjective Global Assessment and Nutritional Risk Screening 2002 to evaluate the nutritional status of non-critically ill patients on parenteral nutrition.

Science.gov (United States)

Badia-Tahull, M B; Cobo-Sacristán, S; Leiva-Badosa, E; Miquel-Zurita, M E; Méndez-Cabalerio, N; Jódar-Masanés, R; Llop-Talaverón, J

2014-02-01

To evaluate the nutritional status of non-critically ill digestive surgery patients at the moment of parenteral nutrition initiation using three different nutritional test tools and to study their correlation. To study the association between the tests and the clinical and laboratory parameters used in the follow-up of PN treatment. Prospective study over 4 months. Anthropometric and clinical variables were recorded. Results of Subjective Global Assessment; Patient-Generated Subjective Global Assessment; and Nutritional Risk Screening 2002 were compared applying kappa test. Relationship between the clinical and laboratory parameters with Subjective Global Assessment was studied by multinominal regression and with the other two tests by multiple linear regression models. Age and sex were included as adjustment variables. Malnutrition in 45 studied patients varied from 51% to 57%. Subjective Global Assessment correlated well with Patient-Generated Subjective Global Assessment and Nutritional Risk Screening 2002 (κ = 0531 p = 0.000). The test with the greatest correlation with the clinical and analytical variables was the Nutritional Risk Screening 2002. Worse nutritional state in this test was associated with worse results in albumin (B = -0.087; CI = -0.169/-0.005], prealbumin (B = -0.005; CI = [-0.011/-0.001]), C-reactive protein (B = 0.006;CI = [0.001/ 0.011]) and leukocytes (B = 0.134; CI = [0.031/0.237]) at the en of parenteral nutrition treatment. Half of the digestive surgery patients were at malnutritional risk at the moment of initiating parenteral nutrition. Nutritional Risk Screening 2002 was the test with best association with the parameters used in the clinical follow-up of parenteral nutrition treated patients. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis.

Science.gov (United States)

Granberg, Tobias; Fan, Qiuyun; Treaba, Constantina Andrada; Ouellette, Russell; Herranz, Elena; Mangeat, Gabriel; Louapre, Céline; Cohen-Adad, Julien; Klawiter, Eric C; Sloane, Jacob A; Mainero, Caterina

2017-11-01

t-test). Cortical thickness did not differ significantly between multiple sclerosis subjects and controls. Higher orientation dispersion in the left primary motor-somatosensory cortex was associated with increased Expanded Disability Status Scale scores in surface-based general linear modelling (P < 0.05). Microstructural pathology was frequent in early multiple sclerosis, and present mainly focally in cortical lesions, whereas more diffusely in white matter. These results suggest early demyelination with loss of cells and/or cell volumes in cortical and white matter lesions, with additional axonal dispersion in white matter lesions. In the cortex, focal lesion changes might precede diffuse atrophy with cortical thinning. Findings in the normal-appearing white matter reveal early axonal pathology outside inflammatory demyelinating lesions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis.

Science.gov (United States)

Oguntunde, Philip G; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

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.

Rise of mean multiplicity depending on transverse momentum

International Nuclear Information System (INIS)

Troshin, S.M.

1977-01-01

Dependence of mean multiplicity on the transversal momentum transfer is studied. In framework of the model in view, based on possible probabilitic interpretation of the unitarity condition, and assuming a weak correlation between the recoil particle momenta in the intermediate n-particle state, it is shown that mean multiplicity increases linearly with rise of the transversal momentum. Behaviour of the mean multiplicity depending on the impact parameter is also studied

Multiple environments: South Indian children’s environmental subjectivities in formation

NARCIS (Netherlands)

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

Subjective Expected Utility Theory with "Small Worlds"

DEFF Research Database (Denmark)

Gyntelberg, Jacob; Hansen, Frank

which is a more general construction than a state space. We retain preference axioms similar in spirit to the Savage axioms and obtain, without abandoning linearity of expectations, a subjective expected utility theory which allows for an intuitive distinction between risk and uncertainty. We also...

Increased determinism in brain electrical activity occurs in association with multiple sclerosis.

Science.gov (United States)

Carrubba, Simona; Minagar, Alireza; Chesson, Andrew L; Frilot, Clifton; Marino, Andrew A

2012-04-01

Increased determinism (decreased complexity) of brain electrical activity has been associated with some brain diseases. Our objective was to determine whether a similar association occurred for multiple sclerosis (MS). Ten subjects with a relapsing-remitting course of MS who were in remission were studied; the controls were age- and gender-matched clinically normal subjects. Recurrence plots were calculated using representative electroencephalogram (EEG) epochs (1-7 seconds) from six derivations; the plots were quantified using the nonlinear variables percent recurrence (%R) and percent determinism (%D). The results were averaged over all derivations for each participant, and the means were compared between the groups. As a linear control procedure the groups were also compared using spectral analysis. The mean±SD of %R for the MS subjects was 6·6±1·3%, compared with 5·1±1·3% in the normal group (P = 0·017), indicating that brain activity in the subjects with MS was less complex, as hypothesized. The groups were not distinguishable using %D or spectral analysis. Taken together with our earlier report that %R could be used to discriminate between MS and normal subjects based on the ability to exhibit evoked potentials, the evidence suggests that complexity analysis of the EEG has potential for development as a diagnostic test for MS.

Detent Force Reduction of a C-Core Linear Flux-Switching Permanent Magnet Machine with Multiple Additional Teeth

Directory of Open Access Journals (Sweden)

Yi Du

2017-03-01

Full Text Available C-core linear flux-switching permanent magnet (PM machines (LFSPMs are attracting more and more attention due to their advantages of simplicity and robustness of the secondary side, high power density and high torque density, in which both PMs and armature windings are housed in the primary side. The primary salient tooth wound with a concentrated winding consists of C-shaped iron core segments between which PMs are sandwiched and the magnetization directions of these PMs are adjacent and alternant in the horizontal direction. On the other hand, the secondary side is composed of a simple iron core with salient teeth so that it is very suitable for long stroke applications. However, the detent force of the C-core LFSPM machine is relatively high and the magnetic circuit is unbalanced due to the end effect. Thus, a new multiple additional tooth which consists of an active and a traditional passive additional tooth, is employed at each end side of the primary in this paper, so that the asymmetry due to end effect can be depressed and the detent force can be reduced by adjusting the passive additional tooth position. By using the finite element method, the characteristics and performances of the proposed machine are analyzed and verified.

Lack of association between systolic blood pressure and blood viscosity in normotensive healthy subjects.

Science.gov (United States)

Irace, Concetta; Carallo, Claudio; Scavelli, Faustina; Loprete, Antonio; Merante, Valentina; Gnasso, Agostino

2012-01-01

A direct relationship between blood pressure and viscosity has frequently been reported, although clear data are not available. To better understand the relationship between these two variables, we evaluated blood viscosity and blood pressure in a group of healthy subjects without cardiovascular risk factors. Healthy subjects were selected from participants in a campaign of prevention of cardiovascular disease (n = 103). They underwent blood sampling for measurement of plasma and blood viscosity, haematocrit, blood lipids and glucose. The quantity and distribution of body fat was assessed by body mass index and waist/hip ratio, respectively. Systolic blood pressure (SBP) correlated significantly with age (r = 0.222) and waist/hip ratio (r = 0.374). Diastolic blood pressure (DBP) correlated significantly with waist/hip ratio (r = 0.216), haematocrit (r = 0.333) and blood viscosity (r = 0.258). Multiple linear regression analyses demonstrated that the only variable significantly associated with SBP was age, while haematocrit was the only variable significantly associated with DBP. Blood viscosity was closely related to waist/hip ratio. These findings show that SBP, in healthy subjects, is not influenced by haematocrit and blood viscosity. In contrast, DBP is related to the values of haematocrit. Among classical cardiovascular risk factors, waist/hip ratio is closely related to blood viscosity.

Linear Algebra and Smarandache Linear Algebra

OpenAIRE

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 vector spaces over finite p...

Safety and pharmacokinetics of single and multiple intravenous bolus doses of diclofenac sodium compared with oral diclofenac potassium 50 mg: A randomized, parallel-group, single-center study in healthy subjects.

Science.gov (United States)

Munjal, Sagar; Gautam, Anirudh; Okumu, Franklin; McDowell, James; Allenby, Kent

2016-01-01

In a randomized, parallel-group, single-center study in 42 healthy adults, the safety and pharmacokinetic parameters of an intravenous formulation of 18.75 and 37.5 mg diclofenac sodium (DFP-08) following single- and multiple-dose bolus administration were compared with diclofenac potassium 50 mg oral tablets. Mean AUC0-inf values for a 50-mg oral tablet and an 18.75-mg intravenous formulation were similar (1308.9 [393.0]) vs 1232.4 [147.6]). As measured by the AUC, DFP-08 18.75 mg and 37.5 mg demonstrated dose proportionality for extent of exposure. One subject in each of the placebo and DFP-08 18.75-mg groups and 2 subjects in the DFP-08 37.5-mg group reported adverse events that were considered by the investigator to be related to the study drug. All were mild in intensity and did not require treatment. Two subjects in the placebo group and 1 subject in the DFP-08 18.75-mg group reported grade 1 thrombophlebitis; no subjects reported higher than grade 1 thrombophlebitis after receiving a single intravenous dose. The 18.75- and 37.5-mg doses of intravenous diclofenac (single and multiple) were well tolerated for 7 days. Additional efficacy and safety studies are required to fully characterize the product. © 2015, The American College of Clinical Pharmacology.

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

Science.gov (United States)

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. PMID:24895666

Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

Science.gov (United States)

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.

State- or trait-like individual differences in dream recall: Preliminary findings from a within-subjects study of multiple nap REM sleep awakenings

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.

Mixed integer linear programming model for dynamic supplier selection problem considering discounts

Directory of Open Access Journals (Sweden)

Adi Wicaksono Purnawan

2018-01-01

Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.

Selectivity of calixarene-bonded silica phases in HPLC: Description of special characteristics with a multiple term linear equation at different methanol concentrations.

Science.gov (United States)

Schneider, Christian; Jira, Thomas

2010-10-01

Retention and selectivity characteristics of different calixarene-, resorcinarene- and alkyl-bonded stationary phases are examined by analyzing a set of test solutes covering the main interactions (hydrophobic, steric, ionic, polar) that apply in HPLC. Therefore Dolan and Snyder's multiple term linear equation has been adapted to fit the properties of calixarene-bonded columns. The obtained parameters are used to describe retention and selectivity of the novel Caltrex(®) phases and to elucidate underlying mechanisms of retention. Here, differences of stationary phase characteristics at different methanol concentrations in the mobile phases are examined. Both selectivity and retention were found to depend on the methanol content. Differences of these dependencies were found for different stationary phases and interactions. The differences between common alkyl-bonded and novel calixarene-bonded phases increase with increasing methanol content.

Gyrokinetic linearized Landau collision operator

DEFF Research Database (Denmark)

Madsen, Jens

2013-01-01

, which is important in multiple ion-species plasmas. Second, the equilibrium operator describes drag and diffusion of the magnetic field aligned component of the vorticity associated with the E×B drift. Therefore, a correct description of collisional effects in turbulent plasmas requires the equilibrium......The full gyrokinetic electrostatic linearized Landau collision operator is calculated including the equilibrium operator, which represents the effect of collisions between gyrokinetic Maxwellian particles. First, the equilibrium operator describes energy exchange between different plasma species...... operator, even for like-particle collisions....

Reversed-field multiple mirror concept

International Nuclear Information System (INIS)

Steinhauer, L.C.; Grossmann, W.; Seyler, C.E.

1978-01-01

The reversed-field multiple mirror (RFMM), is a promising technique for end-stoppering linear magnetic fusion plasmas. By this means the physics and engineering advantages of a linear plasma are gained while circumventing the endloss problem, allowing the projection of very short (less than or equal to 100 m) conceptual reactors. RFMM end-stoppering is accomplished by a string of closed field-line cells on the plasma column axis; these cells strongly retard the axial flow of particles and energy. We describe the reactor implications of the RFMM

Impurity strength and impurity domain modulated frequency-dependent linear and second non-linear response properties of doped quantum dots

Energy Technology Data Exchange (ETDEWEB)

Datta, Nirmal Kumar [Department of Physics, Suri Vidyasagar College, Suri, Birbhum 731 101, West Bengal (India); Ghosh, Manas [Department of Chemistry, Physical Chemistry Section, Visva Bharati University, Santiniketan, Birbhum 731 235, West Bengal (India)

2011-08-15

We explore the pattern of frequency-dependent linear and second non-linear optical responses of repulsive impurity doped quantum dots harmonically confined in two dimensions. The dopant impurity potential chosen assumes a Gaussian form and it is doped into an on-center location. The quantum dot is subject to a periodically oscillating external electric field. For some fixed values of transverse magnetic field strength ({omega}{sub c}) and harmonic confinement potential ({omega}{sub 0}), the influence of impurity strength (V{sub 0}) and impurity domain ({xi}) on the diagonal components of the frequency-dependent linear ({alpha}{sub xx} and {alpha}{sub yy}) and second non-linear ({gamma}{sub xxxx} and {gamma}{sub yyyy}) responses of the dot are computed through a linear variational route. The investigations reveal that the optical responses undergo enhancement with increase in both V{sub 0} and {xi} values. However, in the limitingly small dopant strength regime one observes a drop in the optical responses with increase in V{sub 0}. A time-average rate of energy transfer to the system is often invoked to support the findings. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Non-linear dielectric signatures of entropy changes in liquids subject to time dependent electric fields

Energy Technology Data Exchange (ETDEWEB)

Richert, Ranko [School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287-1604 (United States)

2016-03-21

A model of non-linear dielectric polarization is studied in which the field induced entropy change is the source of polarization dependent retardation time constants. Numerical solutions for the susceptibilities of the system are obtained for parameters that represent the dynamic and thermodynamic behavior of glycerol. The calculations for high amplitude sinusoidal fields show a significant enhancement of the steady state loss for frequencies below that of the low field loss peak. Also at relatively low frequencies, the third harmonic susceptibility spectrum shows a “hump,” i.e., a maximum, with an amplitude that increases with decreasing temperature. Both of these non-linear effects are consistent with experimental evidence. While such features have been used to conclude on a temperature dependent number of dynamically correlated particles, N{sub corr}, the present result demonstrates that the third harmonic susceptibility display a peak with an amplitude that tracks the variation of the activation energy in a model that does not involve dynamical correlations or spatial scales.

Application of non-linear discretetime feedback regulators with assignable closed-loop dynamics

Directory of Open Access Journals (Sweden)

Dubljević Stevan

2003-01-01

Full Text Available In the present work the application of a new approach is demonstrated to a discrete-time state feedback regulator synthesis with feedback linearization and pole-placement for non-linear discrete-time systems. Under the simultaneous implementation of a non-linear coordinate transformation and a non-linear state feedback law computed through the solution of a system of non-linear functional equations, both the feedback linearization and pole-placement design objectives were accomplished. The non-linear state feedback regulator synthesis method was applied to a continuous stirred tank reactor (CSTR under non-isothermal operating conditions that exhibits steady-state multiplicity. The control objective was to regulate the reactor at the middle unstable steady state by manipulating the rate of input heat in the reactor. Simulation studies were performed to evaluate the performance of the proposed non-linear state feedback regulator, as it was shown a non-linear state feedback regulator clearly outperformed a standard linear one, especially in the presence of adverse disturbance under which linear regulation at the unstable steady state was not feasible.

Latent constructs of adjustment to aging and subjective age in Portugal and Romania: a comparative multiple correspondence analysis

Directory of Open Access Journals (Sweden)

Sofia von Humboldt

Full Text Available Objective: To analyze the determinants of adjustment to aging (AtA and subjective age (SA identified by older adults and to investigate the differences of latent constructs that can work as major determinants in AtA and SA in an older Portuguese and Romanian population. Method: Measures were completed, including demographics and interviews. Complete data were available for 38 older adults aged between 74-90 years (M=80.6; SD = 5.4, from Portugal and Romenia. Data was subjected to content analysis. Representation of the associations and latent constructs were analyzed by a Multiple Correspondence Analysis (MCA. Results: The most prevalent response of the interviewed participants for determinants to AtA was ‘health status, physical and intellectual functioning’ (18.1%. ‘With apprehension’ and ‘good enough’ (both 27.0% were identified as the most frequent SA responses. Findings showed a model for each nationality. AtA and SA for Portuguese elderly were explained by a three-factor model: ‘regardful’, ‘engaged’ and ‘conciliated’. A three-dimension model formed by ‘perseverant’, ‘congruent’ and ‘enjoyers’ was indicated as a best-fit solution for Romanian elderly. Conclusion: AtA and SA are strongly explained by increased likelihood of specific constructs in its definition. AtA is related to SA in older adults in both countries, although in different degree.

Linear and Nonlinear Multiset Canonical Correlation Analysis (invited talk)

DEFF Research Database (Denmark)

Hilger, Klaus Baggesen; Nielsen, Allan Aasbjerg; Larsen, Rasmus

2002-01-01

This paper deals with decompositioning of multiset data. Friedman's alternating conditional expectations (ACE) algorithm is extended to handle multiple sets of variables of different mixtures. The new algorithm finds estimates of the optimal transformations of the involved variables that maximize...... the sum of the pair-wise correlations over all sets. The new algorithm is termed multi-set ACE (MACE) and can find multiple orthogonal eigensolutions. MACE is a generalization of the linear multiset correlations analysis (MCCA). It handles multivariate multisets of arbitrary mixtures of both continuous...

Serum 25-hydroxyvitamin D is associated with both arterial and ventricular stiffness in healthy subjects.

Science.gov (United States)

Şeker, Taner; Gür, Mustafa; Kuloğlu, Osman; Kalkan, Gülhan Yüksel; Şahin, Durmuş Yıldıray; Türkoğlu, Caner; Elbasan, Zafer; Baykan, Ahmet Oytun; Gözübüyük, Gökhan; Çaylı, Murat

2013-12-01

Vitamin D regulates the renin-angiotensin system, suppresses proliferation of vascular smooth muscle and improves endothelial cell dependent vasodilatation. These mechanisms may play a role on pathogenesis of arterial and left ventricular stiffness. We aimed to investigate the association between serum 25-hydroxyvitamin D with arterial and left ventricular stiffness in healthy subjects. We studied 125 healthy subjects without known cardiovascular risk factors or overt heart disease (mean age: 60.2 ± 11.9 years). Serum 25-hydroxyvitamin D was measured using a direct competitive chemiluminescent immunoassay. The subjects were divided into two groups according to the serum vitamin D level; vitamin D sufficient (≥ 20 ng/ml, n = 56) and vitamin D deficient (stiffness such as E/A and E/E' were measured. Pulse wave velocity (PWV), which reflects arterial stiffness, was calculated using the single-point method via the Mobil-O-Graph(®) ARC solver algorithm. Systolic blood pressure, level of serum calcium, PWV and E/E' values were higher and E/A values were lower in vitamin D deficient group compared with vitamin D sufficient group. Multiple linear regression analysis showed that vitamin D level was independently associated with E/E' (β = -0.364, pstiffness as well as systolic blood pressure in healthy subjects. Copyright © 2013 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Multiple Linear Regression Modeling To Predict the Stability of Polymer-Drug Solid Dispersions: Comparison of the Effects of Polymers and Manufacturing Methods on Solid Dispersion Stability.

Science.gov (United States)

Fridgeirsdottir, Gudrun A; Harris, Robert J; Dryden, Ian L; Fischer, Peter M; Roberts, Clive J

2018-03-29

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray-drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallization (onset of crystallization) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental data set obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature ( T g ) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.

Azerbaijan Technical University’s Experience in Teaching Linear Electrical Circuit Theory

Directory of Open Access Journals (Sweden)

G. A. Mamedov

2006-01-01

Full Text Available An experience in teaching linear electrical circuit theory at the Azerbaijan Technical University is presented in the paper. The paper describes structure of the Linear Electrical Circuit Theory course worked out by the authors that contains a section on electrical calculation of track circuits, information on electro-magnetic compatibility and typical tests for better understanding of the studied subject.

On Supra-Additive and Supra-Multiplicative Maps

OpenAIRE

Jin Xi Chen; Zi Li Chen

2013-01-01

Let A and B be ordered algebras over ℝ, where A has a generating positive cone and B satisfies the property that b2>0 if 0≠b∈B. We give some conditions for a map T:A→B which is supra-additive and supra-multiplicative for all positive and negative elements to be linear and multiplicative; that is, T is a homomorphism of algebras. Our results generalize some known results on supra-additive and supra-multiplicative maps between spaces of real functions.

Seismic response analysis of a piping system subjected to multiple support excitations in a base isolated NPP building

International Nuclear Information System (INIS)

Surh, Han-Bum; Ryu, Tae-Young; Park, Jin-Sung; Ahn, Eun-Woo; Choi, Chul-Sun; Koo, Ja Choon; Choi, Jae-Boong; Kim, Moon Ki

2015-01-01

Highlights: • Piping system in the APR 1400 NPP with a base isolation design is studied. • Seismic response of piping system in base isolated building are investigated. • Stress classification method is examined for piping subjected to seismic loading. • Primary stress of piping is reduced due to base isolation design. • Substantial secondary stress is observed in the main steam piping. - Abstract: In this study, the stress response of the piping system in the advanced power reactor 1400 (APR 1400) with a base isolation design subjected to seismic loading is addressed. The piping system located between the auxiliary building with base isolation and the turbine building with a fixed base is considered since it can be subjected to substantial relative support movement during seismic events. First, the support responses with respect to the base characteristic are investigated to perform seismic analysis for multiple support excitations. Finite element analyses are performed to predict the piping stress response through various analysis methods such as the response spectrum, seismic support movement and time history method. To separately evaluate the inertial effect and support movement effect on the piping stress, the stress is decomposed into a primary and secondary stress using the proposed method. Finally, influences of the base isolation design on the piping system in the APR 1400 are addressed. The primary stress based on the inertial loading is effectively reduced in a base isolation design, whereas a considerable amount of secondary stress is generated in the piping system connecting a base isolated building with a fixed base building. It is also confirmed that both the response spectrum analysis and seismic support movement analysis provide more conservative estimations of the piping stress compared to the time history analysis

Smoothing identification of systems with small non-linearities

Czech Academy of Sciences Publication Activity Database

Kozánek, Jan; Piranda, J.

2003-01-01

Roč. 38, č. 1 (2003), s. 71-84 ISSN 0025-6455 R&D Projects: GA ČR GA101/00/1471 Institutional research plan: CEZ:AV0Z2076919 Keywords : identification * small non-linearities * smoothing methods Subject RIV: BI - Acoustics Impact factor: 0.237, year: 2003

Gender differences in subjective health complaints in adolescence: The roles of self-esteem, stress from schoolwork and body dissatisfaction.

Science.gov (United States)

Aanesen, Fiona; Meland, Eivind; Torp, Steffen

2017-06-01

The aims of this study were to examine subjective health complaints among Norwegian adolescents and assess the development of gender differences in subjective health complaints between age 14 and 16; to investigate whether self-esteem, stress from schoolwork or body dissatisfaction affected adolescents' subjective health complaints; and determine whether these factors could explain the excess of subjective health complaints among girls. We used multiple linear regression analyses to analyse longitudinal survey data from 751 Norwegian adolescents at the ages of 14 and 16. The results from various cross-sectional and prospective analyses were compared. Girls reported more subjective health complaints than boys, and gender differences increased from age 14 to 16. Self-esteem and stress from schoolwork had cross-sectional and prospective associations with subjective health complaints. Stress from schoolwork at age 14 was also associated with changes in subjective health complaints from age 14 to 16. The cross-sectional mediation analyses indicated that self-esteem and stress from schoolwork accounted for 61% of the excess of subjective health complaints among girls at age 16. The same variables measured at age 14 accounted for 24% of the gender differences in subjective health complaints two years later. The investigated factors could not account for the increase in gender differences in subjective health complaints between ages 14 and 16. The findings showed that self-esteem and stress from schoolwork were associated with subjective health complaints during adolescence. These factors could partially explain the excess of subjective health complaints among girls.

Creating Discussions with Classroom Voting in Linear Algebra

Science.gov (United States)

Cline, Kelly; Zullo, Holly; Duncan, Jonathan; Stewart, Ann; Snipes, Marie

2013-01-01

We present a study of classroom voting in linear algebra, in which the instructors posed multiple-choice questions to the class and then allowed a few minutes for consideration and small-group discussion. After each student in the class voted on the correct answer using a classroom response system, a set of clickers, the instructor then guided a…

Reduction of Linear Programming to Linear Approximation

OpenAIRE

Vaserstein, Leonid N.

2006-01-01

It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.

Evolution of linear chromosomes and multipartite genomes in yeast mitochondria

Science.gov (United States)

Valach, Matus; Farkas, Zoltan; Fricova, Dominika; Kovac, Jakub; Brejova, Brona; Vinar, Tomas; Pfeiffer, Ilona; Kucsera, Judit; Tomaska, Lubomir; Lang, B. Franz; Nosek, Jozef

2011-01-01

Mitochondrial genome diversity in closely related species provides an excellent platform for investigation of chromosome architecture and its evolution by means of comparative genomics. In this study, we determined the complete mitochondrial DNA sequences of eight Candida species and analyzed their molecular architectures. Our survey revealed a puzzling variability of genome architecture, including circular- and linear-mapping and multipartite linear forms. We propose that the arrangement of large inverted repeats identified in these genomes plays a crucial role in alterations of their molecular architectures. In specific arrangements, the inverted repeats appear to function as resolution elements, allowing genome conversion among different topologies, eventually leading to genome fragmentation into multiple linear DNA molecules. We suggest that molecular transactions generating linear mitochondrial DNA molecules with defined telomeric structures may parallel the evolutionary emergence of linear chromosomes and multipartite genomes in general and may provide clues for the origin of telomeres and pathways implicated in their maintenance. PMID:21266473

Single-Subject Research Methodology: An Underutilized Tool in the Field of Deafness.

Science.gov (United States)

Bullis, Michael; Anderson, Glenn

1986-01-01

Single-subject research methods are simple, powerful, and very applicable to selected study of deafness. This article considers group versus single-subject designs; an example of withdrawal single-subject design; and an example of the multiple baseline single-subject design. (CB)

BLAS- BASIC LINEAR ALGEBRA SUBPROGRAMS

Science.gov (United States)

Krogh, F. T.

1994-01-01

The Basic Linear Algebra Subprogram (BLAS) library is a collection of FORTRAN callable routines for employing standard techniques in performing the basic operations of numerical linear algebra. The BLAS library was developed to provide a portable and efficient source of basic operations for designers of programs involving linear algebraic computations. The subprograms available in the library cover the operations of dot product, multiplication of a scalar and a vector, vector plus a scalar times a vector, Givens transformation, modified Givens transformation, copy, swap, Euclidean norm, sum of magnitudes, and location of the largest magnitude element. Since these subprograms are to be used in an ANSI FORTRAN context, the cases of single precision, double precision, and complex data are provided for. All of the subprograms have been thoroughly tested and produce consistent results even when transported from machine to machine. BLAS contains Assembler versions and FORTRAN test code for any of the following compilers: Lahey F77L, Microsoft FORTRAN, or IBM Professional FORTRAN. It requires the Microsoft Macro Assembler and a math co-processor. The PC implementation allows individual arrays of over 64K. The BLAS library was developed in 1979. The PC version was made available in 1986 and updated in 1988.

Eye Movement Desensitisation and Reprocessing Therapy for Posttraumatic Stress Disorder in a Child and an Adolescent with Mild to Borderline Intellectual Disability: A Multiple Baseline across Subjects Study

Science.gov (United States)

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…

Multiple linear regressions

Indian Academy of Sciences (India)

Abstract. The predictive analysis based on quantitative structure activity relationships (QSAR) on benzim- ... could lead to treatment of obesity, diabetes and related conditions. ..... After discussing the physical and chemical mean- ing of the ...

Linear time algorithms to construct populations fitting multiple constraint distributions at genomic scales.

Science.gov (United States)

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.

A Type System for the Vectorial Aspect of the Linear-Algebraic Lambda-Calculus

Directory of Open Access Journals (Sweden)

Pablo Arrighi

2012-07-01

Full Text Available We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms resulting from the reduction of programs. This gives rise to an original type theory where types, in the same way as terms, can be superposed into linear combinations. We show that the resulting typed lambda-calculus is strongly normalizing and features a weak subject-reduction.

A Link between Subjective Perceptions of Memory and Physical Function: Implications for Subjective Cognitive Decline.

Science.gov (United States)

Cosentino, Stephanie; Devanand, Davangere; Gurland, Barry

2018-01-01

Subjective impairment in memory is a frequently defining feature of subjective cognitive decline (SCD), a state hypothesized to precede objectively apparent cognitive symptoms of Alzheimer's disease (AD) and to hold promise as a non-invasive, inexpensive, preclinical indicator of AD. However, a full model of the factors that contribute to subjective memory (SM), and therefore to SCD, has yet to be articulated. While SM impairment is widely known to be associated with negative affect, the extent to which SM functioning may also reflect other factors, particularly subjective beliefs or perceptions about one's health, is not known. To examine the extent to which SM is associated with subjective perceptions of health more broadly, the current study investigated the link between SM and subjective physical functioning (independent of depressive affect, and objective cognitive and physical function) in an ethnically diverse sample of 471 older adults enrolled in the population-based Northern Manhattan Aging Project. 199 (42%) participants endorsed no difficulty on a 5-point SM index while 272 (58%) endorsed some degree of difficulty. As hypothesized, SM correlated with both depression and subjective physical function, but not with age, education, global cognition, or objective physical function. When objective and subjective physical function were entered in two separate, adjusted linear regressions predicting SM, only subjective physical function and depressive affect independently predicted SM. Subjective perceptions of memory appear to reflect individuals' broader health perceptions in part. Articulating the various correlates of SM will improve identification of SCD specific to preclinical AD.

On non-linear dynamics of a coupled electro-mechanical system

DEFF Research Database (Denmark)

Darula, Radoslav; Sorokin, Sergey

2012-01-01

Electro-mechanical devices are an example of coupled multi-disciplinary weakly non-linear systems. Dynamics of such systems is described in this paper by means of two mutually coupled differential equations. The first one, describing an electrical system, is of the first order and the second one...... excitation. The results are verified using a numerical model created in MATLAB Simulink environment. Effect of non-linear terms on dynamical response of the coupled system is investigated; the backbone and envelope curves are analyzed. The two phenomena, which exist in the electro-mechanical system: (a......, for mechanical system, is of the second order. The governing equations are coupled via linear and weakly non-linear terms. A classical perturbation method, a method of multiple scales, is used to find a steadystate response of the electro-mechanical system exposed to a harmonic close-resonance mechanical...

Testing For The Linearity of Responses To Multiple Anthropogenic Climate Forcings

Science.gov (United States)

Forest, C. E.; Stone, P. H.; Sokolov, A. P.

To test whether climate forcings are additive, we compare climate model simulations in which anthropogenic forcings are applied individually and in combination. Tests are performed with different values for climate system properties (climate sensitivity and rate of heat uptake by the deep ocean) as well as for different strengths of the net aerosol forcing, thereby testing for the dependence of linearity on these properties. The MIT 2D Land-Ocean Climate Model used in this study consists of a zonally aver- aged statistical-dynamical atmospheric model coupled to a mixed-layer Q-flux ocean model, with heat anomalies diffused into the deep ocean. Following our previous stud- ies, the anthropogenic forcings are the changes in concentrations of greenhouse gases (1860-1995), sulfate aerosol (1860-1995), and stratospheric and tropospheric ozone (1979-1995). The sulfate aerosol forcing is applied as a surface albedo change. For an aerosol forcing of -1.0 W/m2 and an effective ocean diffusitivity of 2.5 cm2/s, the nonlinearity of the response of global-mean surface temperatures to the combined forcing shows a strong dependence on climate sensitivity. The fractional change in decadal averages ([(TG + TS + TO) - TGSO]/TGSO) for the 1986-1995 period compared to pre-industrial times are 0.43, 0.90, and 1.08 with climate sensitiv- ities of 3.0, 4.5, and 6.2 C, respectively. The values of TGSO for these three cases o are 0.52, 0.62, and 0.76 C. The dependence of linearity on climate system properties, o the role of climate system feedbacks, and the implications for the detection of climate system's response to individual forcings will be presented. Details of the model and forcings can be found at http://web.mit.edu/globalchange/www/.

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

Science.gov (United States)

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

2015-05-01

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

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

Science.gov (United States)

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…

The possibilities of linearized inversion of internally scattered seismic data

KAUST Repository

Aldawood, Ali

2014-08-05

Least-square migration is an iterative linearized inversion scheme that tends to suppress the migration artifacts and enhance the spatial resolution of the migrated image. However, standard least-square migration, based on imaging single scattering energy, may not be able to enhance events that are mainly illuminated by internal multiples such as vertical and nearly vertical faults. To alleviate this problem, we propose a linearized inversion framework to migrate internally multiply scattered energy. We applied this least-square migration of internal multiples to image a vertical fault. Tests on synthetic data demonstrate the ability of the proposed method to resolve a vertical fault plane that is poorly resolved by least-square imaging using primaries only. We, also, demonstrate the robustness of the proposed scheme in the presence of white Gaussian random observational noise and in the case of imaging the fault plane using inaccurate migration velocities.

The possibilities of linearized inversion of internally scattered seismic data

KAUST Repository

Aldawood, Ali; Alkhalifah, Tariq Ali; Hoteit, Ibrahim; Zuberi, Mohammad; Turkiyyah, George

2014-01-01

Least-square migration is an iterative linearized inversion scheme that tends to suppress the migration artifacts and enhance the spatial resolution of the migrated image. However, standard least-square migration, based on imaging single scattering energy, may not be able to enhance events that are mainly illuminated by internal multiples such as vertical and nearly vertical faults. To alleviate this problem, we propose a linearized inversion framework to migrate internally multiply scattered energy. We applied this least-square migration of internal multiples to image a vertical fault. Tests on synthetic data demonstrate the ability of the proposed method to resolve a vertical fault plane that is poorly resolved by least-square imaging using primaries only. We, also, demonstrate the robustness of the proposed scheme in the presence of white Gaussian random observational noise and in the case of imaging the fault plane using inaccurate migration velocities.

Nonoscillation of half-linear dynamic equations

Czech Academy of Sciences Publication Activity Database

Matucci, S.; Řehák, Pavel

2010-01-01

Roč. 60, č. 5 (2010), s. 1421-1429 ISSN 0898-1221 R&D Projects: GA AV ČR KJB100190701 Grant - others:GA ČR(CZ) GA201/07/0145 Institutional research plan: CEZ:AV0Z10190503 Keywords : half-linear dynamic equation * time scale * (non)oscillation * Riccati technique Subject RIV: BA - General Mathematics Impact factor: 1.472, year: 2010 http://www.sciencedirect.com/science/article/pii/S0898122110004384

Aortic stiffness and hypotension episodes are associated with impaired cognitive function in older subjects with subjective complaints of memory loss.

Science.gov (United States)

Scuteri, Angelo; Tesauro, Manfredi; Guglini, Letizia; Lauro, Davide; Fini, Massimo; Di Daniele, Nicola

2013-11-20

Though CV risk factors and markers of arterial aging are recognized risky for cognition, no study has simultaneously investigated the impact of multiple cardiac, arterial (large and small vessels), and hemodynamic parameters on cognitive function in older subjects. Two hundred eighty older subjects with subjective complaints of memory loss and no previous stroke (mean age 78.3 ± 6.3 years) were studied. Global cognitive function was evaluated with the Mini-Mental State Examination (MMSE). Cognitive impairment was defined as a MMSE cognitive function-controlling for age, sex, education, depression, traditional CV risk factors, and medications. LV mass was no longer associated with cognition in multiple regression. Older subjects with stiffer arteries or episodes of hypotension presented a 4-fold and an 11-fold, respectively, greater odds for progression from normal cognitive function to cognitive impairment. A synergistic effect between PWV, WML, and hypotension was observed: the occurrence of any two of PWV, WML, or hypotension was accompanied by lower MMSE; in the presence of all three factors, a further significant decline in cognitive function was observed. Systemic hemodynamic parameters (higher PWV and hypotension) together with cerebral microvascular damage (WML) are significantly associated with poorer cognitive function and may identify older subjects with subjective complaints of memory loss at higher risk of cognitive decline. © 2013.

Increased prolactin levels are associated with impaired processing speed in subjects with early psychosis.

Directory of Open Access Journals (Sweden)

Itziar Montalvo

Full Text Available Hyperprolactinaemia, a common side effect of some antipsychotic drugs, is also present in drug-naïve psychotic patients and subjects at risk for psychosis. Recent studies in non-psychiatric populations suggest that increased prolactin may have negative effects on cognition. The aim of our study was to explore whether high plasma prolactin levels are associated with poorer cognitive functioning in subjects with early psychoses. We studied 107 participants: 29 healthy subjects and 78 subjects with an early psychosis (55 psychotic disorders with <3 years of illness, 23 high-risk subjects. Cognitive assessment was performed with the MATRICS Cognitive Consensus Cognitive Battery, and prolactin levels were determined as well as total cortisol levels in plasma. Psychopathological status was assessed and the use of psychopharmacological treatments (antipsychotics, antidepressants, benzodiazepines recorded. Prolactin levels were negatively associated with cognitive performance in processing speed, in patients with a psychotic disorder and high-risk subjects. In the latter group, increased prolactin levels were also associated with impaired reasoning and problem solving and poorer general cognition. In a multiple linear regression analysis conducted in both high-risk and psychotic patients, controlling for potential confounders, prolactin and benzodiazepines were independently related to poorer cognitive performance in the speed of processing domain. A mediation analysis showed that both prolactin and benzodiazepine treatment act as mediators of the relationship between risperidone/paliperidone treatment and speed of processing. These results suggest that increased prolactin levels are associated with impaired processing speed in early psychosis. If these results are confirmed in future studies, strategies targeting reduction of prolactin levels may improve cognition in this population.

The essential multiobjectivity of linear programming | Stewart | ORiON

African Journals Online (AJOL)

It is argued that any non-trivial real world problems involve multiple objectives. The simplistic approach of combining objectives in linear form can generate highly misleading and biased results, and is poor operational research practice. Such biases are illustrated by means of a simple example, and it is demonstrated that ...

Linearized least-square imaging of internally scattered data

KAUST Repository

Aldawood, Ali; Hoteit, Ibrahim; Turkiyyah, George M.; Zuberi, M. A H; Alkhalifah, Tariq Ali

2014-01-01

Internal multiples deteriorate the quality of the migrated image obtained conventionally by imaging single scattering energy. However, imaging internal multiples properly has the potential to enhance the migrated image because they illuminate zones in the subsurface that are poorly illuminated by single-scattering energy such as nearly vertical faults. Standard migration of these multiples provide subsurface reflectivity distributions with low spatial resolution and migration artifacts due to the limited recording aperture, coarse sources and receivers sampling, and the band-limited nature of the source wavelet. Hence, we apply a linearized least-square inversion scheme to mitigate the effect of the migration artifacts, enhance the spatial resolution, and provide more accurate amplitude information when imaging internal multiples. Application to synthetic data demonstrated the effectiveness of the proposed inversion in imaging a reflector that is poorly illuminated by single-scattering energy. The least-square inversion of doublescattered data helped delineate that reflector with minimal acquisition fingerprint.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

Science.gov (United States)

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852