included multiple linear: Topics by Science.gov

Sample records for included multiple linear

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

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

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

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…
Multiple pass laser amplifier system

DOEpatents

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

1977-01-01

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

PubMed

Marill, Keith A

2004-01-01

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

DTIC Science & Technology

2015-09-01

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

PubMed

Marill, Keith A

2004-01-01

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

PubMed

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

1990-05-10

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

PubMed

Eberly, Lynn E

2007-01-01

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

PubMed Central

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

2015-01-01

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

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

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

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

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

NASA Astrophysics Data System (ADS)

Chen, Hao; Gong, Yu; Hong, Xia

2016-07-01

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

DOEpatents

Douglas, David R.

2015-09-01

A separated-orbit bisected energy-recovered linear accelerator apparatus and method. The accelerator includes a first linac, a second linac, and a plurality of arcs of differing path lengths, including a plurality of up arcs, a plurality of downgoing arcs, and a full energy arc providing a path independent of the up arcs and downgoing arcs. The up arcs have a path length that is substantially a multiple of the RF wavelength and the full energy arc includes a path length that is substantially an odd half-integer multiple of the RF wavelength. Operation of the accelerator includes accelerating the beam utilizing the linacs and up arcs until the beam is at full energy, at full energy executing a full recirculation to the second linac using a path length that is substantially an odd half-integer of the RF wavelength, and then decelerating the beam using the linacs and downgoing arcs.
Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

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

2014-11-06

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

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

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

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328
A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

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

1991-03-01

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

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

Hager, Robert, E-mail: rhager@pppl.gov; Yoon, E.S., E-mail: yoone@rpi.edu; Ku, S., E-mail: sku@pppl.gov

2016-06-15

Fusion edge plasmas can be far from thermal equilibrium and require the use of a non-linear collision operator for accurate numerical simulations. In this article, the non-linear single-species Fokker–Planck–Landau collision operator developed by Yoon and Chang (2014) [9] is generalized to include multiple particle species. The finite volume discretization used in this work naturally yields exact conservation of mass, momentum, and energy. The implementation of this new non-linear Fokker–Planck–Landau operator in the gyrokinetic particle-in-cell codes XGC1 and XGCa is described and results of a verification study are discussed. Finally, the numerical techniques that make our non-linear collision operator viable onmore » high-performance computing systems are described, including specialized load balancing algorithms and nested OpenMP parallelization. The collision operator's good weak and strong scaling behavior are shown.« less

A fully non-linear multi-species Fokker–Planck–Landau collision operator for simulation of fusion plasma

DOE PAGES

Hager, Robert; Yoon, E. S.; Ku, S.; ...

2016-04-04

Fusion edge plasmas can be far from thermal equilibrium and require the use of a non-linear collision operator for accurate numerical simulations. The non-linear single-species Fokker–Planck–Landau collision operator developed by Yoon and Chang (2014) [9] is generalized to include multiple particle species. Moreover, the finite volume discretization used in this work naturally yields exact conservation of mass, momentum, and energy. The implementation of this new non-linear Fokker–Planck–Landau operator in the gyrokinetic particle-in-cell codes XGC1 and XGCa is described and results of a verification study are discussed. Finally, the numerical techniques that make our non-linear collision operator viable on high-performance computingmore » systems are described, including specialized load balancing algorithms and nested OpenMP parallelization. As a result, the collision operator's good weak and strong scaling behavior are shown.« less
An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

PubMed

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

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

PubMed Central

Palya, William L; Walter, Donald; Kessel, Robert; Lucke, Robert

2002-01-01

The observed steady-state behavioral dynamics supported by unsignaled periods of reinforcement within repeating 2,000-s trials were modeled with a linear transfer function. These experiments employed improved schedule forms and analytical methods to improve the precision of the measured transfer function, compared to previous work. The refinements include both the use of multiple reinforcement periods that improve spectral coverage and averaging of independently determined transfer functions. A linear analysis was then used to predict behavior observed for three different test schedules. The fidelity of these predictions was determined. PMID:11831782
Multiple corrosion protection systems for reinforced concrete bridge components.

DOT National Transportation Integrated Search

2007-07-01

Eleven systems combining epoxy-coated reinforcement with another corrosion protection system are evaluated using : the rapid macrocell, Southern Exposure, cracked beam, and linear polarization resistance tests. The systems include : bars that are pre...
Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

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

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

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

2014-08-01

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

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Kuo, C. Y.

1979-01-01

The objective of this paper is to define optical physics and/or environmental conditions under which the linear multiple-regression should be applicable. An investigation of the signal-response equations is conducted and the concept is tested by application to actual remote sensing data from a laboratory experiment performed under controlled conditions. Investigation of the signal-response equations shows that the exact solution for a number of optical physics conditions is of the same form as a linearized multiple-regression equation, even if nonlinear contributions from surface reflections, atmospheric constituents, or other water pollutants are included. Limitations on achieving this type of solution are defined.
A parametric LQ approach to multiobjective control system design

NASA Technical Reports Server (NTRS)

Kyr, Douglas E.; Buchner, Marc

1988-01-01

The synthesis of a constant parameter output feedback control law of constrained structure is set in a multiple objective linear quadratic regulator (MOLQR) framework. The use of intuitive objective functions such as model-following ability and closed-loop trajectory sensitivity, allow multiple objective decision making techniques, such as the surrogate worth tradeoff method, to be applied. For the continuous-time deterministic problem with an infinite time horizon, dynamic compensators as well as static output feedback controllers can be synthesized using a descent Anderson-Moore algorithm modified to impose linear equality constraints on the feedback gains by moving in feasible directions. Results of three different examples are presented, including a unique reformulation of the sensitivity reduction problem.
Beam transport results on the multi-beam MABE accelerator

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

Coleman, P.D.; Alexander, J.A.; Hasti, D.E.

1985-10-01

MABE is a multistage, electron beam linear accelerator. The accelerator has been operated in single beam (60 kA, 7 Mev) and multiple beam configurations. This paper deals with the multiple beam configuration in which typically nine approx. = 25 kA injected beams are transported through three accelerating gaps. Experimental results from the machine are discussed, including problems encountered and proposed solutions to those problems.
Spectrum of PORCN mutations in Focal Dermal Hypoplasia

USDA-ARS?s Scientific Manuscript database

Focal Dermal Hypoplasia (FDH), also known as Goltz syndrome (OMIM 305600), is a genetic disorder that affects multiple organ systems early in development. Features of FDH include skin abnormalities, (hypoplasia, atrophy, linear pigmentation, and herniation of fat through dermal defects); papillomas...
Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

ERIC Educational Resources Information Center

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…
On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

NASA Technical Reports Server (NTRS)

Molusis, J. A.; Mookerjee, P.; Bar-Shalom, Y.

1983-01-01

Effect of nonlinearity on convergence of the local linear and global linear adaptive controllers is evaluated. A nonlinear helicopter vibration model is selected for the evaluation which has sufficient nonlinearity, including multiple minimum, to assess the vibration reduction capability of the adaptive controllers. The adaptive control algorithms are based upon a linear transfer matrix assumption and the presence of nonlinearity has a significant effect on algorithm behavior. Simulation results are presented which demonstrate the importance of the caution property in the global linear controller. Caution is represented by a time varying rate weighting term in the local linear controller and this improves the algorithm convergence. Nonlinearity in some cases causes Kalman filter divergence. Two forms of the Kalman filter covariance equation are investigated.
Two-dimensional imaging via a narrowband MIMO radar system with two perpendicular linear arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Su, Yi

2010-05-01

This paper presents a system model and method for the 2-D imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. Furthermore, the imaging formulation for our method is developed through a Fourier integral processing, and the parameters of antenna array including the cross-range resolution, required size, and sampling interval are also examined. Different from the spatial sequential procedure sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging, the proposed method utilizes a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination. Consequently, the complex motion compensation in ISAR imaging can be avoided. Moreover, in our array configuration, multiple narrowband spectrum-shared waveforms coded with orthogonal polyphase sequences are employed. The mainlobes of the compressed echoes from the different filter band could be located in the same range bin, and thus, the range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.
Genetic Programming Transforms in Linear Regression Situations

NASA Astrophysics Data System (ADS)

Castillo, Flor; Kordon, Arthur; Villa, Carlos

The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.
Step-response of a torsional device with multiple discontinuous non-linearities: Formulation of a vibratory experiment

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

ERIC Educational Resources Information Center

Debnath, L.

2013-01-01

This article deals with a short historical introduction to determinants with applications to the theory of equations, geometry, multiple integrals, differential equations and linear algebra. Included are some properties of determinants with proofs, eigenvalues, eigenvectors and characteristic equations with examples of applications to simple…
Importance of Multimodal MRI in Characterizing Brain Tissue and Its Potential Application for Individual Age Prediction.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Peran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2016-09-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. The results of the linear model were used to predict apparent age in different regions of individual brain. This approach pointed to a number of novel applications that could potentially help highlighting areas particularly vulnerable to disease.
MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

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

Ultrasensitive surveillance of sensors and processes

DOEpatents

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

2001-01-01

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

DOEpatents

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

1999-01-01

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

PubMed

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

2016-01-01

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

PubMed

Snyder, Dalton T; Szalwinski, Lucas J; Cooks, R Graham

2017-10-17

Methods of performing precursor ion scans as well as neutral loss scans in a single linear quadrupole ion trap have recently been described. In this paper we report methodology for performing permutations of MS/MS scan modes, that is, ordered combinations of precursor, product, and neutral loss scans following a single ion injection event. Only particular permutations are allowed; the sequences demonstrated here are (1) multiple precursor ion scans, (2) precursor ion scans followed by a single neutral loss scan, (3) precursor ion scans followed by product ion scans, and (4) segmented neutral loss scans. (5) The common product ion scan can be performed earlier in these sequences, under certain conditions. Simultaneous scans can also be performed. These include multiple precursor ion scans, precursor ion scans with an accompanying neutral loss scan, and multiple neutral loss scans. We argue that the new capability to perform complex simultaneous and sequential MS n operations on single ion populations represents a significant step in increasing the selectivity of mass spectrometry.
Complete structural characterization of ceramides as [M – H]− ions by multiple-stage linear ion trap mass spectrometry

PubMed Central

Hsu, Fong-Fu

2016-01-01

Ceramide is a huge lipid family consisting of diversified structures including various modifications in the fatty acyl chain and the long chain base (LCB). In this contribution, negative-ion ESI linear ion-trap multiple-stage mass spectrometric method (LIT MSn) towards complete structural determination of ceramides in ten major families characterized as the [M – H]− ions is described. Multiple sets of fragment ions reflecting the fatty acyl chain and LCB were observed in the CID MS2 spectrum, while the sequential MS3 and MS4 spectra contain structural information for locating the double bond and the functional groups, permitting realization of the fragmentation processes. Thereby, differentiation of ceramide molecules varied by chain length, the LCB (sphingosine, phytosphigosine, 6-hydroxy-sphingosine), and by the modification (α-hydroxy-, β-hydroxy-, ω-hydroxy-FA) can be achieved; and many isomeric structures in the biological specimen can be revealed in detail. PMID:27523779
Multiple eigenmodes of the Rayleigh-Taylor instability observed for a fluid interface with smoothly varying density

NASA Astrophysics Data System (ADS)

Yu, C. X.; Xue, C.; Liu, J.; Hu, X. Y.; Liu, Y. Y.; Ye, W. H.; Wang, L. F.; Wu, J. F.; Fan, Z. F.

2018-01-01

In this article, multiple eigen-systems including linear growth rates and eigen-functions have been discovered for the Rayleigh-Taylor instability (RTI) by numerically solving the Sturm-Liouville eigen-value problem in the case of two-dimensional plane geometry. The system called the first mode has the maximal linear growth rate and is just extensively studied in literature. Higher modes have smaller eigen-values, but possess multi-peak eigen-functions which bring on multiple pairs of vortices in the vorticity field. A general fitting expression for the first four eigen-modes is presented. Direct numerical simulations show that high modes lead to appearances of multi-layered spike-bubble pairs, and lots of secondary spikes and bubbles are also generated due to the interactions between internal spikes and bubbles. The present work has potential applications in many research and engineering areas, e.g., in reducing the RTI growth during capsule implosions in inertial confinement fusion.
Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.
Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.
Buffer$--An Economic Analysis Tool

Treesearch

Gary Bentrup

2007-01-01

Buffer$ is an economic spreadsheet tool for analyzing the cost-benefits of conservation buffers by resource professionals. Conservation buffers are linear strips of vegetation managed for multiple landowner and societal objectives. The Microsoft Excel based spreadsheet can calculate potential income derived from a buffer, including income from cost-share/incentive...
Predicting daily use of urban forest recreation sites

Treesearch

John F. Dwyer

1988-01-01

A multiple linear regression model explains 90% of the variance in daily use of an urban recreation site. Explanatory variables include season, day of the week, and weather. The results offer guides for recreation site planning and management as well as suggestions for improving the model.
The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

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

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

2009-11-15

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

PubMed

Eymann, Alfredo; Busaniche, Julio; Llera, Julián; De Cunto, Carmen; Wahren, Carlos

2009-01-01

To assess psychosocial quality of life in school-age children of divorced parents. A cross-sectional survey was conducted at the pediatric outpatient clinic of a community hospital. Children 5 to 12 years old from married families and divorced families were included. Child quality of life was assessed through maternal reports using a Child Health Questionnaire-Parent Form 50. A multiple linear regression model was constructed including clinically relevant variables significant on univariate analysis (beta coefficient and 95%CI). Three hundred and thirty families were invited to participate and 313 completed the questionnaire. Univariate analysis showed that quality of life was significantly associated with parental separation, child sex, time spent with the father, standard of living, and maternal education. In a multiple linear regression model, quality of life scores decreased in boys -4.5 (-6.8 to -2.3) and increased for time spent with the father 0.09 (0.01 to 0.2). In divorced families, multiple linear regression showed that quality of life scores increased when parents had separated by mutual agreement 6.1 (2.7 to 9.4), when the mother had university level education 5.9 (1.7 to 10.1) and for each year elapsed since separation 0.6 (0.2 to 1.1), whereas scores decreased in boys -5.4 (-9.5 to -1.3) and for each one-year increment of maternal age -0.4 (-0.7 to -0.05). Children's psychosocial quality of life was affected by divorce. The Child Health Questionnaire can be useful to detect a decline in the psychosocial quality of life.
[Non-linear canonical correlation analysis between anthropometric indicators and multiple metabolic abnormalities].

PubMed

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

2013-09-01

To define the general correlation between anthropometric indicators and multiple metabolic abnormalities, and to put forward some particular suggestions for the prevention of multiple metabolic abnormalities. A random cluster sampling was carried out in one county of Henan Province. Questionnaire, physical examination and biochemical tests were admitted to the adult inhabitants. Non-linear canonical correlation analysis (NLCCA) was applied with OVERALS of SPSS 13.0. The coefficients of canonical correlation and multiple correlation were calculated. The plot of centroids labeled by variables showed the correlation among various indicators. In total, 2,914 objects were investigated. It included 1,134 (38.9%) males and 1,780 (61.1%) females (60.0%). The average age was (50.58 +/- 13.70) years old. The fitting result of NLCCA were as follows: the loss of 0.577 accounting for 28.8% of the total variation was relatively small, and indicated that the two sets of variables of this study, namely sets of biochemical indicators (including serum total cholesterol, total triglyceride, high-density lipoprotein cholesterol, low density lipoprotein cholesterol and fasting plasma glucose) and sets of others (including gender, BMI and waist circumference) were closely related and often changed synchronously. Multivariate correlation coefficient showed that internal indicators of the above two sets were closely related respectively and often showed the multiple anomalies of the same set. The diagram of the center of gravity of the association of various indicators showed that the symptoms of metabolic abnormalities increased with age. Women were more liable to have metabolic abnormalities. Overweight and obese people often suffer multiple metabolic disorders. Waist circumference was positively correlated with metabolic abnormalities. (1) Biochemical indicators and anthropometric often change in combination. (2) Much attention should be paid to older people especially middle-aged or older men and older women in primary prevention. (3) Overweight and abdominal obesity can be considered the sensitive predictive indicator of multiple metabolic abnormalities. (4) Nonlinear canonical correlation and center of gravity Figure had the advantage of analyze the correlation between multiple sets of variables.
Multiple collision effects on the antiproton production by high energy proton (100 GeV - 1000 GeV)

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

Takahashi, Hiroshi; Powell, J.

Antiproton production rates which take into account multiple collision are calculated using a simple model. Methods to reduce capture of the produced antiprotons by the target are discussed, including geometry of target and the use of a high intensity laser. Antiproton production increases substantially above 150 GeV proton incident energy. The yield increases almost linearly with incident energy, alleviating space charge problems in the high current accelerator that produces large amounts of antiprotons.
Active Games: An Approach to Teaching Mathematical Skills to the Educable Mentally Retarded

ERIC Educational Resources Information Center

Taylor, George R.; Watkins, Susan T.

1974-01-01

Several games involving both motor behavior and practice with mathematical skills are described. These include adaptations of musical chairs (subtraction), call ball (multiplication), and ring toss (linear measurement); other games are designed to provide practice on identifying numerals, telling time, using money, and naming fractions. (SD)
Probability Theory, Not the Very Guide of Life

ERIC Educational Resources Information Center

Juslin, Peter; Nilsson, Hakan; Winman, Anders

2009-01-01

Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical demonstrations of violations of this norm include the conjunction error and base-rate neglect. Many of these phenomena require multiplicative probability integration, whereas people seem more inclined to linear additive…
Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

PubMed

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

2011-05-11

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

ERIC Educational Resources Information Center

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

2006-01-01

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

NASA Astrophysics Data System (ADS)

Eisenbud, David; Schreyer, Frank-Olaf

2009-07-01

In the remarkable paper Graded Betti numbers of Cohen-Macaulay modules and the multiplicity conjecture, Mats Boij and Jonas Soederberg conjectured that the Betti table of a Cohen-Macaulay module over a polynomial ring is a positive linear combination of Betti tables of modules with pure resolutions. We prove a strengthened form of their conjectures. Applications include a proof of the Multiplicity Conjecture of Huneke and Srinivasan and a proof of the convexity of a fan naturally associated to the Young lattice. With the same tools we show that the cohomology table of any vector bundle on projective space is a positive rational linear combination of the cohomology tables of what we call supernatural vector bundles. Using this result we give new bounds on the slope of a vector bundle in terms of its cohomology.

Structural distinction of diacyl-, alkylacyl, and alk-1-enylacyl glycerophosphocholines as [M - 15]⁻ ions by multiple-stage linear ion-trap mass spectrometry with electrospray ionization.

PubMed

Hsu, Fong-Fu; Lodhi, Irfan J; Turk, John; Semenkovich, Clay F

2014-08-01

We describe a linear ion-trap (LIT) multiple-stage (MS(n)) mass spectrometric approach towards differentiation of alkylacyl, alk-1-enylacyl- and diacyl-glycerophoscholines (PCs) as the [M - 15]⁻ ions desorbed by electrospray ionization (ESI) in the negative-ion mode. The MS⁴ mass spectra of the [M - 15 - R²'CH = CO]⁻ ions originated from the three PC subfamilies are readily distinguishable, resulting in unambiguous distinction of the lipid classes. This method is applied to two alkyl ether rich PC mixtures isolated from murine bone marrow neutrophils and kidney, respectively, to explore its utility in the characterization of complex PC mixture of biological origin, resulting in the realization of the detailed structures of the PC species, including various classes and many minor isobaric isomers.
Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.
Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions

PubMed Central

Tewarie, P.; Bright, M.G.; Hillebrand, A.; Robson, S.E.; Gascoyne, L.E.; Morris, P.G.; Meier, J.; Van Mieghem, P.; Brookes, M.J.

2016-01-01

Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology. PMID:26827811
Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.
Patterns of Library Use by Undergraduate Students in a Chilean University

ERIC Educational Resources Information Center

Jara, Magdalena; Clasing, Paula; Gonzalez, Carlos; Montenegro, Maximiliano; Kelly, Nick; Alarcón, Rosa; Sandoval, Augusto; Saurina, Elvira

2017-01-01

This paper explores the patterns of use of print materials and digital resources in an undergraduate library in a Chilean university, by the students' discipline and year of study. A quantitative analysis was carried out, including descriptive analysis of contingency tables, chi-squared tests, t-tests, and multiple linear regressions. The results…
DSPCP: A Data Scalable Approach for Identifying Relationships in Parallel Coordinates.

PubMed

Nguyen, Hoa; Rosen, Paul

2018-03-01

Parallel coordinates plots (PCPs) are a well-studied technique for exploring multi-attribute datasets. In many situations, users find them a flexible method to analyze and interact with data. Unfortunately, using PCPs becomes challenging as the number of data items grows large or multiple trends within the data mix in the visualization. The resulting overdraw can obscure important features. A number of modifications to PCPs have been proposed, including using color, opacity, smooth curves, frequency, density, and animation to mitigate this problem. However, these modified PCPs tend to have their own limitations in the kinds of relationships they emphasize. We propose a new data scalable design for representing and exploring data relationships in PCPs. The approach exploits the point/line duality property of PCPs and a local linear assumption of data to extract and represent relationship summarizations. This approach simultaneously shows relationships in the data and the consistency of those relationships. Our approach supports various visualization tasks, including mixed linear and nonlinear pattern identification, noise detection, and outlier detection, all in large data. We demonstrate these tasks on multiple synthetic and real-world datasets.
Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

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

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)
The Ability of American Football Helmets to Manage Linear Acceleration With Repeated High-Energy Impacts.

PubMed

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

2016-03-01

Football players can receive up to 1400 head impacts per season, averaging 6.3 impacts per practice and 14.3 impacts per game. A decrease in the capacity of a helmet to manage linear acceleration with multiple impacts could increase the risk of traumatic brain injury. To investigate the ability of football helmets to manage linear acceleration with multiple high-energy impacts. Descriptive laboratory study. Laboratory. We collected linear-acceleration data for 100 impacts at 6 locations on 4 helmets of different models currently used in football. Impacts 11 to 20 were compared with impacts 91 to 100 for each of the 6 locations. Linear acceleration was greater after multiple impacts (91-100) than after the first few impacts (11-20) for the front, front-boss, rear, and top locations. However, these differences are not clinically relevant as they do not affect the risk for head injury. American football helmet performance deteriorated with multiple impacts, but this is unlikely to be a factor in head-injury causation during a game or over a season.
Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

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

2012-01-01

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

NASA Astrophysics Data System (ADS)

Healy, John J.

2018-01-01

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

PubMed

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

2014-01-01

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

PubMed Central

Liu, Xiaolei; Huang, Meng; Fan, Bin; Buckler, Edward S.; Zhang, Zhiwu

2016-01-01

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days. PMID:26828793
Numerical Technology for Large-Scale Computational Electromagnetics

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

Sharpe, R; Champagne, N; White, D

The key bottleneck of implicit computational electromagnetics tools for large complex geometries is the solution of the resulting linear system of equations. The goal of this effort was to research and develop critical numerical technology that alleviates this bottleneck for large-scale computational electromagnetics (CEM). The mathematical operators and numerical formulations used in this arena of CEM yield linear equations that are complex valued, unstructured, and indefinite. Also, simultaneously applying multiple mathematical modeling formulations to different portions of a complex problem (hybrid formulations) results in a mixed structure linear system, further increasing the computational difficulty. Typically, these hybrid linear systems aremore » solved using a direct solution method, which was acceptable for Cray-class machines but does not scale adequately for ASCI-class machines. Additionally, LLNL's previously existing linear solvers were not well suited for the linear systems that are created by hybrid implicit CEM codes. Hence, a new approach was required to make effective use of ASCI-class computing platforms and to enable the next generation design capabilities. Multiple approaches were investigated, including the latest sparse-direct methods developed by our ASCI collaborators. In addition, approaches that combine domain decomposition (or matrix partitioning) with general-purpose iterative methods and special purpose pre-conditioners were investigated. Special-purpose pre-conditioners that take advantage of the structure of the matrix were adapted and developed based on intimate knowledge of the matrix properties. Finally, new operator formulations were developed that radically improve the conditioning of the resulting linear systems thus greatly reducing solution time. The goal was to enable the solution of CEM problems that are 10 to 100 times larger than our previous capability.« less
Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

PubMed

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.
Cooling in the single-photon strong-coupling regime of cavity optomechanics

NASA Astrophysics Data System (ADS)

Nunnenkamp, A.; Børkje, K.; Girvin, S. M.

2012-05-01

In this Rapid Communication we discuss how red-sideband cooling is modified in the single-photon strong-coupling regime of cavity optomechanics where the radiation pressure of a single photon displaces the mechanical oscillator by more than its zero-point uncertainty. Using Fermi's golden rule we calculate the transition rates induced by the optical drive without linearizing the optomechanical interaction. In the resolved-sideband limit we find multiple-phonon cooling resonances for strong single-photon coupling that lead to nonthermal steady states including the possibility of phonon antibunching. Our study generalizes the standard linear cooling theory.
Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.
Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

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

NASA Astrophysics Data System (ADS)

Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

2017-08-01

We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.
Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

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

PubMed Central

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

2016-01-01

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

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...
Optimal space communications techniques. [using digital and phase locked systems for signal processing

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

Digital multiplication of two waveforms using delta modulation (DM) is discussed. It is shown that while conventional multiplication of two N bit words requires N2 complexity, multiplication using DM requires complexity which increases linearly with N. Bounds on the signal-to-quantization noise ratio (SNR) resulting from this multiplication are determined and compared with the SNR obtained using standard multiplication techniques. The phase locked loop (PLL) system, consisting of a phase detector, voltage controlled oscillator, and a linear loop filter, is discussed in terms of its design and system advantages. Areas requiring further research are identified.
Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

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

2005-01-01

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

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

Stiebel-Kalish, Hadas, E-mail: kalishhadas@gmail.com; Sackler School of Medicine, Tel Aviv University, Tel Aviv; Reich, Ehud

Purpose: Meningiomas threatening the anterior visual pathways (AVPs) and not amenable for surgery are currently treated with multisession stereotactic radiotherapy. Stereotactic radiotherapy is available with a number of devices. The most ubiquitous include the gamma knife, CyberKnife, tomotherapy, and isocentric linear accelerator systems. The purpose of our study was to describe a case series of AVP meningiomas treated with linear accelerator fractionated stereotactic radiotherapy (FSRT) using the multiple, noncoplanar, dynamic conformal rotation paradigm and to compare the success and complication rates with those reported for other techniques. Patients and Methods: We included all patients with AVP meningiomas followed up atmore » our neuro-ophthalmology unit for a minimum of 12 months after FSRT. We compared the details of the neuro-ophthalmologic examinations and tumor size before and after FSRT and at the end of follow-up. Results: Of 87 patients with AVP meningiomas, 17 had been referred for FSRT. Of the 17 patients, 16 completed >12 months of follow-up (mean 39). Of the 16 patients, 11 had undergone surgery before FSRT and 5 had undergone FSRT as first-line management. Tumor control was achieved in 14 of the 16 patients, with three meningiomas shrinking in size after RT. Two meningiomas progressed, one in an area that was outside the radiation field. The visual function had improved in 6 or stabilized in 8 of the 16 patients (88%) and worsened in 2 (12%). Conclusions: Linear accelerator fractionated RT using the multiple noncoplanar dynamic rotation conformal paradigm can be offered to patients with meningiomas that threaten the anterior visual pathways as an adjunct to surgery or as first-line treatment, with results comparable to those reported for other stereotactic RT techniques.« less
Estimation of standard liver volume in Chinese adult living donors.

PubMed

Fu-Gui, L; Lu-Nan, Y; Bo, L; Yong, Z; Tian-Fu, W; Ming-Qing, X; Wen-Tao, W; Zhe-Yu, C

2009-12-01

To determine a formula predicting the standard liver volume based on body surface area (BSA) or body weight in Chinese adults. A total of 115 consecutive right-lobe living donors not including the middle hepatic vein underwent right hemi-hepatectomy. No organs were used from prisoners, and no subjects were prisoners. Donor anthropometric data including age, gender, body weight, and body height were recorded prospectively. The weights and volumes of the right lobe liver grafts were measured at the back table. Liver weights and volumes were calculated from the right lobe graft weight and volume obtained at the back table, divided by the proportion of the right lobe on computed tomography. By simple linear regression analysis and stepwise multiple linear regression analysis, we correlated calculated liver volume and body height, body weight, or body surface area. The subjects had a mean age of 35.97 +/- 9.6 years, and a female-to-male ratio of 60:55. The mean volume of the right lobe was 727.47 +/- 136.17 mL, occupying 55.59% +/- 6.70% of the whole liver by computed tomography. The volume of the right lobe was 581.73 +/- 96.137 mL, and the estimated liver volume was 1053.08 +/- 167.56 mL. Females of the same body weight showed a slightly lower liver weight. By simple linear regression analysis and stepwise multiple linear regression analysis, a formula was derived based on body weight. All formulae except the Hong Kong formula overestimated liver volume compared to this formula. The formula of standard liver volume, SLV (mL) = 11.508 x body weight (kg) + 334.024, may be applied to estimate liver volumes in Chinese adults.
Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.
Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389
Natural canopy bridges effectively mitigate tropical forest fragmentation for arboreal mammals.

PubMed

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

2017-06-20

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

NASA Astrophysics Data System (ADS)

Chiang, Chih-Hung; Yu, Chih-Peng; Chen, Yan-Hao; Lai, Jiunnren; Hsu, Keng-Tsang; Cheng, Chia-Chi

2017-04-01

Effects of foundation stiffness on the linear vibrations of wind turbine systems are of concerns for both planning and construction of wind turbine systems. Current study performed numerical modeling for such a problem using linear spectral finite elements. The effects of foundation stiffness were investigated for various combinations of shear wave velocity of soil, size of tower base plate, and pile length. Multiple piles are also included in the models such that the foundation stiffness can be analyzed more realistically. The results indicate that the shear wave velocity of soil and the size of tower base plate have notable effects on the dominant frequency of the turbine-tower system. The larger the lateral dimension, the stiffer the foundation. Large pile cap and multiple spaced piles result in higher stiffness than small pile cap and a mono-pile. The lateral stiffness of a mono-pile mainly depends on the shear wave velocity of soil with the exception for a very short pile that the end constraints may affect the lateral vibration of the superstructure. Effective pile length may be determined by comparing the simulation results of the frictional pile to those of the end-bearing pile.
Multiple regression technique for Pth degree polynominals with and without linear cross products

NASA Technical Reports Server (NTRS)

Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.
Unified quantum no-go theorems and transforming of quantum pure states in a restricted set

NASA Astrophysics Data System (ADS)

Luo, Ming-Xing; Li, Hui-Ran; Lai, Hong; Wang, Xiaojun

2017-12-01

The linear superposition principle in quantum mechanics is essential for several no-go theorems such as the no-cloning theorem, the no-deleting theorem and the no-superposing theorem. In this paper, we investigate general quantum transformations forbidden or permitted by the superposition principle for various goals. First, we prove a no-encoding theorem that forbids linearly superposing of an unknown pure state and a fixed pure state in Hilbert space of a finite dimension. The new theorem is further extended for multiple copies of an unknown state as input states. These generalized results of the no-encoding theorem include the no-cloning theorem, the no-deleting theorem and the no-superposing theorem as special cases. Second, we provide a unified scheme for presenting perfect and imperfect quantum tasks (cloning and deleting) in a one-shot manner. This scheme may lead to fruitful results that are completely characterized with the linear independence of the representative vectors of input pure states. The upper bounds of the efficiency are also proved. Third, we generalize a recent superposing scheme of unknown states with a fixed overlap into new schemes when multiple copies of an unknown state are as input states.
LPmerge: an R package for merging genetic maps by linear programming.

PubMed

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

PubMed

Giulianini, Franco; Eskew, Rhea T

2007-09-01

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

PubMed

Faggion, Clovis M; Wu, Yun-Chun; Tu, Yu-Kang; Wasiak, Jason

2016-06-01

Systematic reviews require comprehensive literature search strategies to avoid publication bias. This study aimed to assess and evaluate the reporting quality of search strategies within systematic reviews published in the field of stereotactic radiosurgery (SRS). Three electronic databases (Ovid MEDLINE(®), Ovid EMBASE(®) and the Cochrane Library) were searched to identify systematic reviews addressing SRS interventions, with the last search performed in October 2014. Manual searches of the reference lists of included systematic reviews were conducted. The search strategies of the included systematic reviews were assessed using a standardized nine-question form based on the Cochrane Collaboration guidelines and Assessment of Multiple Systematic Reviews checklist. Multiple linear regression analyses were performed to identify the important predictors of search quality. A total of 85 systematic reviews were included. The median quality score of search strategies was 2 (interquartile range = 2). Whilst 89% of systematic reviews reported the use of search terms, only 14% of systematic reviews reported searching the grey literature. Multiple linear regression analyses identified publication year (continuous variable), meta-analysis performance and journal impact factor (continuous variable) as predictors of higher mean quality scores. This study identified the urgent need to improve the quality of search strategies within systematic reviews published in the field of SRS. This study is the first to address how authors performed searches to select clinical studies for inclusion in their systematic reviews. Comprehensive and well-implemented search strategies are pivotal to reduce the chance of publication bias and consequently generate more reliable systematic review findings.
General-Purpose Software For Computer Graphics

NASA Technical Reports Server (NTRS)

Rogers, Joseph E.

1992-01-01

NASA Device Independent Graphics Library (NASADIG) is general-purpose computer-graphics package for computer-based engineering and management applications which gives opportunity to translate data into effective graphical displays for presentation. Features include two- and three-dimensional plotting, spline and polynomial interpolation, control of blanking of areas, multiple log and/or linear axes, control of legends and text, control of thicknesses of curves, and multiple text fonts. Included are subroutines for definition of areas and axes of plots; setup and display of text; blanking of areas; setup of style, interpolation, and plotting of lines; control of patterns and of shading of colors; control of legends, blocks of text, and characters; initialization of devices; and setting of mixed alphabets. Written in FORTRAN 77.
Disposable skin staplers for closure of linear gastrointestinal incisions in dogs.

PubMed

Schwartz, Zeev; Coolman, Bradley R

2018-02-01

To report the clinical features and outcomes of linear gastrointestinal incisions closed with skin staples in dogs. Historical cohort study. 333 client-owned dogs. Medical records from 1 private referral hospital were searched for dogs that underwent gastrointestinal surgery between November 1999 and October 2015. Cases were included if skin staplers were used to close linear gastrointestinal incisions. Information regarding preoperative, surgical, and postoperative factors was collected. Complications were diagnosed in 8 of 245 (3.27%) dogs, including 3 of 245 (1.22%) dogs that died or were euthanized, 3 of 245 (1.22%) dogs with incisional dehiscence, and 2 of 245 (0.81%) dogs with attachment of a linear foreign body to the staples at the intestinal lumen. Dehiscence was noted at the enterotomy sites in 3 dogs at a mean time of 44 hours after surgery (SD ± 6.93). Two dogs presented with another linear foreign body that was attached to the staples in the intestinal lumen at postoperative days 24 and 42. The risk factors associated with incisional dehiscence included multiple gastrointestinal incisions performed in 1 surgery (χ 2 , P < .001) and the presence of a linear foreign body (χ 2 , P = .02253). No associations were detected between dogs' age, sex, weight, surgery time, indication for surgical intervention, surgery location in the gastrointestinal tract, or surgeon experience and incisional dehiscence. Skin staplers provide safe and effective closure of gastrotomies, enterotomies, and colonotomies in dogs. This method is reliable, efficient, and affordable in the hands of veterinary surgeons with varying skill levels. © 2017 The American College of Veterinary Surgeons.
INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID.

PubMed

Hammad, Mohanad M; Elshenawy, Ahmed K; El Singaby, M I

2017-01-01

In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment.
Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID

PubMed Central

Elshenawy, Ahmed K.; El Singaby, M.I.

2017-01-01

In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment. PMID:28683071

Ranking Forestry Investments With Parametric Linear Programming

Treesearch

Paul A. Murphy

1976-01-01

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

NASA Astrophysics Data System (ADS)

Kauffmann, K.; Kleiber, R.; Hatzky, R.; Borchardt, M.

2010-11-01

The code EUTERPE uses a Particle-In-Cell (PIC) method to solve the gyrokinetic equation globally (full radius, full flux surface) for three-dimensional equilibria calculated with VMEC. Recently this code has been extended to include multiple kinetic species and electromagnetic effects. Additionally, a pitch-angle scattering operator has been implemented in order to include collisional effects in the simulation of instabilities and to be able to simulate neoclassical transport. As a first application of this extended code we study the effects of collisions on electrostatic ion-temperature-gradient (ITG) instabilities in LHD.
Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

PubMed

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

2017-09-05

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

PubMed

Percy, A; Kinghorn, B P

2005-12-01

We use linear algebra to calculate an index of information content in genotype probabilities which has previously been calculated using trigonometry. The new method can be generalized allowing the index to be calculated for loci with more than two alleles. Applications of this index include its use in genotyping strategies, strategies to manage genetic disorders and in estimation of genotype effects.
Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.
Multiple solution of linear algebraic systems by an iterative method with recomputed preconditioner in the analysis of microstrip structures

NASA Astrophysics Data System (ADS)

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

2016-06-01

A multiple solution of linear algebraic systems with dense matrix by iterative methods is considered. To accelerate the process, the recomputing of the preconditioning matrix is used. A priory condition of the recomputing based on change of the arithmetic mean of the current solution time during the multiple solution is proposed. To confirm the effectiveness of the proposed approach, the numerical experiments using iterative methods BiCGStab and CGS for four different sets of matrices on two examples of microstrip structures are carried out. For solution of 100 linear systems the acceleration up to 1.6 times, compared to the approach without recomputing, is obtained.
Polarization of skylight in the O(2)A band: effects of aerosol properties.

PubMed

Boesche, Eyk; Stammes, Piet; Preusker, Réne; Bennartz, Ralf; Knap, Wouter; Fischer, Juergen

2008-07-01

Motivated by several observations of the degree of linear polarization of skylight in the oxygen A (O(2)A) band that do not yet have a quantitative explanation, we analyze the influence of aerosol altitude, microphysics, and optical thickness on the degree of linear polarization of the zenith skylight in the spectral region of the O(2)A band, between 755 to 775 nm. It is shown that the degree of linear polarization inside the O(2)A band is particularly sensitive to aerosol altitude. The sensitivity is strongest for aerosols within the troposphere and depends also on their microphysical properties and optical thickness. The polarization of the O(2)A band can be larger than the polarization of the continuum, which typically occurs for strongly polarizing aerosols in an elevated layer, or smaller, which typically occurs for depolarizing aerosols or cirrus clouds in an elevated layer. We show that in the case of a single aerosol layer in the atmosphere a determination of the aerosol layer altitude may be obtained. Furthermore, we show limitations of the aerosol layer altitude determination in case of multiple aerosol layers. To perform these simulations we developed a fast method for multiple scattering radiative transfer calculations in gaseous absorption bands including polarization. The method is a combination of doubling-adding and k-binning methods. We present an error estimation of this method by comparing with accurate line-by-line radiative transfer simulations. For the Motivated by several observations of the degree of linear polarization of skylight in the oxygen A (O(2)A) band that do not yet have a quantitative explanation, we analyze the influence of aerosol altitude, microphysics, and optical thickness on the degree of linear polarization of the zenith skylight in the spectral region of the O(2)A band, between 755 to 775 nm. It is shown that the degree of linear polarization inside the O(2)A band is particularly sensitive to aerosol altitude. The sensitivity is strongest for aerosols within the troposphere and depends also on their microphysical properties and optical thickness. The polarization of the O(2)A band can be larger than the polarization of the continuum, which typically occurs for strongly polarizing aerosols in an elevated layer, or smaller, which typically occurs for depolarizing aerosols or cirrus clouds in an elevated layer. We show that in the case of a single aerosol layer in the atmosphere a determination of the aerosol layer altitude may be obtained. Furthermore, we show limitations of the aerosol layer altitude determination in case of multiple aerosol layers. To perform these simulations we developed a fast method for multiple scattering radiative transfer calculations in gaseous absorption bands including polarization. The method is a combination of doubling-adding and k-binning methods. We present an error estimation of this method by comparing with accurate line-by-line radiative transfer simulations. For the O(2)A band, the errors in the degree of linear polarization are less than 0.11% for transmitted light, and less than 0.31% for reflected light. band, the errors in the degree of linear polarization are less than 0.11% for transmitted light, and less than 0.31% for reflected light.
New techniques for the analysis of manual control systems. [mathematical models of human operator behavior

NASA Technical Reports Server (NTRS)

Bekey, G. A.

1971-01-01

Studies are summarized on the application of advanced analytical and computational methods to the development of mathematical models of human controllers in multiaxis manual control systems. Specific accomplishments include the following: (1) The development of analytical and computer methods for the measurement of random parameters in linear models of human operators. (2) Discrete models of human operator behavior in a multiple display situation were developed. (3) Sensitivity techniques were developed which make possible the identification of unknown sampling intervals in linear systems. (4) The adaptive behavior of human operators following particular classes of vehicle failures was studied and a model structure proposed.
Distributed coupling high efficiency linear accelerator

DOEpatents

Tantawi, Sami G.; Neilson, Jeffrey

2016-07-19

A microwave circuit for a linear accelerator includes multiple monolithic metallic cell plates stacked upon each other so that the beam axis passes vertically through a central acceleration cavity of each plate. Each plate has a directional coupler with coupling arms. A first coupling slot couples the directional coupler to an adjacent directional coupler of an adjacent cell plate, and a second coupling slot couples the directional coupler to the central acceleration cavity. Each directional coupler also has an iris protrusion spaced from corners joining the arms, a convex rounded corner at a first corner joining the arms, and a corner protrusion at a second corner joining the arms.
[Combined application of multiple fluorescence in research on the degradation of fluoranthene by potassium ferrate].

PubMed

Li, Si; Yu, Dan-Ni; Ji, Fang-Ying; Zhou, Guang-Ming; He, Qiang

2012-11-01

The degradation of fluoranthene was researched by combined means of multiple fluorescence spectra, including emission, synchronous, excitation emission matrix (EEM), time-scan and photometry. The characteristics of the degradation and fluoranthene molecular changes within the degradation's process were also discussed according to the information about the degradation provided by all of the fluorescence spectra mentioned above. The equations of fluoranthene's degradation by potassium ferrate were obtained on the bases of fitting time-scan fluorescence curves at different time, and the degradation's kinetic was speculated accordingly. From the experimental results, multiple fluorescence data commonly reflected that it had same degradation rate at the same reaction time. t = 10 s, and the degradation rate is -55%, t = 25 s, -81%, t = 40 s, -91%. No new fluorescent characteristic was observed within every degradation' stage. The reaction stage during t < or = 20 s was crucial, in which the degradation process is closest to linear relationship. After this beginning stage, the linear relationship deviated gradually with the development of the degradation process. The degradation of fluoranthene by potassium ferrate was nearly in accord with the order of the first order reaction.
A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…
Sparse matrix multiplications for linear scaling electronic structure calculations in an atom-centered basis set using multiatom blocks.

PubMed

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

2003-04-15

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

PubMed

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

2013-12-01

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

NASA Technical Reports Server (NTRS)

Soulas, George C.

2011-01-01

The equations for rigorously calculating the particle flux and density surrounding a cylindrical aperture in the free molecular flow regime are developed and presented. The fundamental equations for particle flux and density from a reservoir and a diffusely reflecting surface will initially be developed. Assumptions will include a Maxwell-Boltzmann speed distribution, equal particle and wall temperatures, and a linear flux distribution along the cylindrical aperture walls. With this information, the equations for axial flux and density surrounding a cylindrical aperture will be developed. The cylindrical aperture will be divided into multiple volumes and regions to rigorously determine the surrounding axial flux and density, and appropriate limits of integration will be determined. The results of these equations will then be evaluated. The linear wall flux distribution assumption will be assessed. The axial flux and density surrounding a cylindrical aperture with a thickness-to-radius ratio of 1.25 will be presented. Finally, the equations determined in this study will be verified using multiple methods.
Assembling programmable FRET-based photonic networks using designer DNA scaffolds

PubMed Central

Buckhout-White, Susan; Spillmann, Christopher M; Algar, W. Russ; Khachatrian, Ani; Melinger, Joseph S.; Goldman, Ellen R.; Ancona, Mario G.; Medintz, Igor L.

2014-01-01

DNA demonstrates a remarkable capacity for creating designer nanostructures and devices. A growing number of these structures utilize Förster resonance energy transfer (FRET) as part of the device's functionality, readout or characterization, and, as device sophistication increases so do the concomitant FRET requirements. Here we create multi-dye FRET cascades and assess how well DNA can marshal organic dyes into nanoantennae that focus excitonic energy. We evaluate 36 increasingly complex designs including linear, bifurcated, Holliday junction, 8-arm star and dendrimers involving up to five different dyes engaging in four-consecutive FRET steps, while systematically varying fluorophore spacing by Förster distance (R0). Decreasing R0 while augmenting cross-sectional collection area with multiple donors significantly increases terminal exciton delivery efficiency within dendrimers compared with the first linear constructs. Förster modelling confirms that best results are obtained when there are multiple interacting FRET pathways rather than independent channels by which excitons travel from initial donor(s) to final acceptor. PMID:25504073
Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

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.
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

NASA Astrophysics Data System (ADS)

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-Low Satellite-to-Satellite Tracking
Diagnostic Accuracy of Full-Body Linear X-Ray Scanning in Multiple Trauma Patients in Comparison to Computed Tomography.

PubMed

Jöres, A P W; Heverhagen, J T; Bonél, H; Exadaktylos, A; Klink, T

2016-02-01

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. The overall sensitivity of LS for truncal skeleton injuries in multiple-trauma patients was < 50 %. The diagnostic reference standard MSCT is the preferred and reliable imaging modality. LS may be valuable for quick detection of extremity fractures. © Georg Thieme Verlag KG Stuttgart · New York.
Probability theory, not the very guide of life.

PubMed

Juslin, Peter; Nilsson, Håkan; Winman, Anders

2009-10-01

Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical demonstrations of violations of this norm include the conjunction error and base-rate neglect. Many of these phenomena require multiplicative probability integration, whereas people seem more inclined to linear additive integration, in part, at least, because of well-known capacity constraints on controlled thought. In this article, the authors show with computer simulations that when based on approximate knowledge of probabilities, as is routinely the case in natural environments, linear additive integration can yield as accurate estimates, and as good average decision returns, as estimates based on probability theory. It is proposed that in natural environments people have little opportunity or incentive to induce the normative rules of probability theory and, given their cognitive constraints, linear additive integration may often offer superior bounded rationality.

An Index and Test of Linear Moderated Mediation.

PubMed

Hayes, Andrew F

2015-01-01

I describe a test of linear moderated mediation in path analysis based on an interval estimate of the parameter of a function linking the indirect effect to values of a moderator-a parameter that I call the index of moderated mediation. This test can be used for models that integrate moderation and mediation in which the relationship between the indirect effect and the moderator is estimated as linear, including many of the models described by Edwards and Lambert ( 2007 ) and Preacher, Rucker, and Hayes ( 2007 ) as well as extensions of these models to processes involving multiple mediators operating in parallel or in serial. Generalization of the method to latent variable models is straightforward. Three empirical examples describe the computation of the index and the test, and its implementation is illustrated using Mplus and the PROCESS macro for SPSS and SAS.
Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...
Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

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

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.
What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

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

ERIC Educational Resources Information Center

Newman, Isadore; Fraas, John W.

The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…
A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.
Robust stability of linear systems: Some computational considerations

NASA Technical Reports Server (NTRS)

Laub, A. J.

1979-01-01

The cases of both additive and multiplicative perturbations were discussed and a number of relationships between the two cases were given. A number of computational aspects of the theory were also discussed, including a proposed new method for evaluating general transfer or frequency response matrices. The new method is numerically stable and efficient, requiring only operations to update for new values of the frequency parameter.
Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.
Size effects in non-linear heat conduction with flux-limited behaviors

NASA Astrophysics Data System (ADS)

Li, Shu-Nan; Cao, Bing-Yang

2017-11-01

Size effects are discussed for several non-linear heat conduction models with flux-limited behaviors, including the phonon hydrodynamic, Lagrange multiplier, hierarchy moment, nonlinear phonon hydrodynamic, tempered diffusion, thermon gas and generalized nonlinear models. For the phonon hydrodynamic, Lagrange multiplier and tempered diffusion models, heat flux will not exist in problems with sufficiently small scale. The existence of heat flux needs the sizes of heat conduction larger than their corresponding critical sizes, which are determined by the physical properties and boundary temperatures. The critical sizes can be regarded as the theoretical limits of the applicable ranges for these non-linear heat conduction models with flux-limited behaviors. For sufficiently small scale heat conduction, the phonon hydrodynamic and Lagrange multiplier models can also predict the theoretical possibility of violating the second law and multiplicity. Comparisons are also made between these non-Fourier models and non-linear Fourier heat conduction in the type of fast diffusion, which can also predict flux-limited behaviors.
Psychosocial issues on-orbit: results from two space station programs

NASA Astrophysics Data System (ADS)

Kanas, N. A.; Salnitskiy, V. P.; Ritsher, J. B.; Gushin, V. I.; Weiss, D. S.; Saylor, S. A.; Marmar, C. R.

PURPOSE Psychosocial issues affecting people working in isolated and confined environments such as spacecraft can jeopardize mental health and mission safety Our team has completed two large NASA-funded studies involving missions to the Mir and International Space Stations where crewmembers were on-orbit for four to seven months Combining these two datasets allows us to generalize across these two settings and maximize statistical power in testing our hypotheses This paper presents results from three sets of hypotheses concerning possible changes in mood and social climate over time displacement of negative emotions to outside monitoring personnel and the task and support roles of the leader METHODS The combined sample of 216 participants included 13 American astronauts 17 Russian cosmonauts and 150 U S and 36 Russian mission control personnel Subjects completed a weekly questionnaire that included items from the Profile of Mood States the Group Environment Scale and the Work Environment Scale producing 20 subscale scores The analytic strategy included piecewise linear regression and general linear modeling and it accounted for the effects of multiple observations per person and multiple analyses RESULTS There was little evidence to suggest that universal changes in levels of mood and group climate occurred among astronauts and cosmonauts over time Although a few individuals experienced decrements in the second half of the mission the majority did not However there was evidence that subjects displaced negative emotions to outside
Nonlinear flow model of multiple fractured horizontal wells with stimulated reservoir volume including the quadratic gradient term

NASA Astrophysics Data System (ADS)

Ren, Junjie; Guo, Ping

2017-11-01

The real fluid flow in porous media is consistent with the mass conservation which can be described by the nonlinear governing equation including the quadratic gradient term (QGT). However, most of the flow models have been established by ignoring the QGT and little work has been conducted to incorporate the QGT into the flow model of the multiple fractured horizontal (MFH) well with stimulated reservoir volume (SRV). This paper first establishes a semi-analytical model of an MFH well with SRV including the QGT. Introducing the transformed pressure and flow-rate function, the nonlinear model of a point source in a composite system including the QGT is linearized. Then the Laplace transform, principle of superposition, numerical discrete method, Gaussian elimination method and Stehfest numerical inversion are employed to establish and solve the seepage model of the MFH well with SRV. Type curves are plotted and the effects of relevant parameters are analyzed. It is found that the nonlinear effect caused by the QGT can increase the flow capacity of fluid flow and influence the transient pressure positively. The relevant parameters not only have an effect on the type curve but also affect the error in the pressure calculated by the conventional linear model. The proposed model, which is consistent with the mass conservation, reflects the nonlinear process of the real fluid flow, and thus it can be used to obtain more accurate transient pressure of an MFH well with SRV.
Stochastic Swift-Hohenberg Equation with Degenerate Linear Multiplicative Noise

NASA Astrophysics Data System (ADS)

Hernández, Marco; Ong, Kiah Wah

2018-03-01

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

NASA Technical Reports Server (NTRS)

Yan, T. Y.; Yao, K.

1988-01-01

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

USGS Publications Warehouse

Kery, Marc; Hatfield, Jeff S.

2003-01-01

In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.
The 11-year solar cycle in current reanalyses: a (non)linear attribution study of the middle atmosphere

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

PubMed

Madeira, Pedro P; Bessa, Ana; Loureiro, Joana A; Álvares-Ribeiro, Luís; Rodrigues, Alírio E; Zaslavsky, Boris Y

2015-08-21

Partition coefficients of seven low molecular weight compounds were measured in multiple aqueous two-phase systems (ATPSs) formed by pairs of different polymers. The ionic composition of each ATPS was varied to include 0.01M sodium phosphate buffer (NaPB), pH 7.4 and 0.1M Na2SO4, 0.15M NaCl, and 0.15M NaClO4 all in 0.01M NaPB, pH 7.4. The differences between the solvent features of the coexisting phases in all the ATPSs were estimated from partitioning of a homologous series of dinitrophenylated-amino acids and by the solvatochromic method. The solute-specific coefficients for the compounds examined were determined by the multiple linear regression analysis using the modified linear solvation energy relationship equation. It is established that the solute specific coefficients characterizing different types of the solute-water interactions (dipole-dipole, dipole-ion, and H-bonding) for a given solute change in the presence of different salt additives in the solute specific manner. It is also found that these characteristics are linearly interrelated. It is suggested that there is a cooperativity between various types of solute-water interactions governed by the solute structure. Copyright © 2015 Elsevier B.V. All rights reserved.
An approach to the development of numerical algorithms for first order linear hyperbolic systems in multiple space dimensions: The constant coefficient case

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1995-01-01

Two methods for developing high order single step explicit algorithms on symmetric stencils with data on only one time level are presented. Examples are given for the convection and linearized Euler equations with up to the eighth order accuracy in both space and time in one space dimension, and up to the sixth in two space dimensions. The method of characteristics is generalized to nondiagonalizable hyperbolic systems by using exact local polynominal solutions of the system, and the resulting exact propagator methods automatically incorporate the correct multidimensional wave propagation dynamics. Multivariate Taylor or Cauchy-Kowaleskaya expansions are also used to develop algorithms. Both of these methods can be applied to obtain algorithms of arbitrarily high order for hyperbolic systems in multiple space dimensions. Cross derivatives are included in the local approximations used to develop the algorithms in this paper in order to obtain high order accuracy, and improved isotropy and stability. Efficiency in meeting global error bounds is an important criterion for evaluating algorithms, and the higher order algorithms are shown to be up to several orders of magnitude more efficient even though they are more complex. Stable high order boundary conditions for the linearized Euler equations are developed in one space dimension, and demonstrated in two space dimensions.
Nonlinear coherent optical image processing using logarithmic transmittance of bacteriorhodopsin films

NASA Astrophysics Data System (ADS)

Downie, John D.

1995-08-01

The transmission properties of some bacteriorhodopsin-film spatial light modulators are uniquely suited to allow nonlinear optical image-processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude-transmission characteristic of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. I present experimental results demonstrating the principle and the capability for several different image and noise situations, including deterministic noise and speckle. The bacteriorhodopsin film studied here displays the logarithmic transmission response for write intensities spanning a dynamic range greater than 2 orders of magnitude.
Nonlinear Coherent Optical Image Processing Using Logarithmic Transmittance of Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

The transmission properties of some bacteriorhodopsin-film spatial light modulators are uniquely suited to allow nonlinear optical image-processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude-transmission characteristic of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. I present experimental results demonstrating the principle and the capability for several different image and noise situations, including deterministic noise and speckle. The bacteriorhodopsin film studied here displays the logarithmic transmission response for write intensities spanning a dynamic range greater than 2 orders of magnitude.
Hidden Markov models of biological primary sequence information.

PubMed Central

Baldi, P; Chauvin, Y; Hunkapiller, T; McClure, M A

1994-01-01

Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth and convergent algorithm is introduced to iteratively adapt the transition and emission parameters of the models from the examples in a given family. The HMM approach is applied to three protein families: globins, immunoglobulins, and kinases. In all cases, the models derived capture the important statistical characteristics of the family and can be used for a number of tasks, including multiple alignments, motif detection, and classification. For K sequences of average length N, this approach yields an effective multiple-alignment algorithm which requires O(KN2) operations, linear in the number of sequences. PMID:8302831

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

ERIC Educational Resources Information Center

Tillema, Erik; Gatza, Andrew

2016-01-01

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

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

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

NASA Technical Reports Server (NTRS)

Berger, Marsha; Aftosmis, Michael J.

2005-01-01

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

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631
Statistical prediction of space motion sickness

NASA Technical Reports Server (NTRS)

Reschke, Millard F.

1990-01-01

Studies designed to empirically examine the etiology of motion sickness to develop a foundation for enhancing its prediction are discussed. Topics addressed include early attempts to predict space motion sickness, multiple test data base that uses provocative and vestibular function tests, and data base subjects; reliability of provocative tests of motion sickness susceptibility; prediction of space motion sickness using linear discriminate analysis; and prediction of space motion sickness susceptibility using the logistic model.
Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018. The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean differences, simple and multiple linear regression, ANOVA tests, and Chi-Squared distribution.
Testing the dose-response specification in epidemiology: public health and policy consequences for lead.

PubMed

Rothenberg, Stephen J; Rothenberg, Jesse C

2005-09-01

Statistical evaluation of the dose-response function in lead epidemiology is rarely attempted. Economic evaluation of health benefits of lead reduction usually assumes a linear dose-response function, regardless of the outcome measure used. We reanalyzed a previously published study, an international pooled data set combining data from seven prospective lead studies examining contemporaneous blood lead effect on IQ (intelligence quotient) of 7-year-old children (n = 1,333). We constructed alternative linear multiple regression models with linear blood lead terms (linear-linear dose response) and natural-log-transformed blood lead terms (log-linear dose response). We tested the two lead specifications for nonlinearity in the models, compared the two lead specifications for significantly better fit to the data, and examined the effects of possible residual confounding on the functional form of the dose-response relationship. We found that a log-linear lead-IQ relationship was a significantly better fit than was a linear-linear relationship for IQ (p = 0.009), with little evidence of residual confounding of included model variables. We substituted the log-linear lead-IQ effect in a previously published health benefits model and found that the economic savings due to U.S. population lead decrease between 1976 and 1999 (from 17.1 microg/dL to 2.0 microg/dL) was 2.2 times (319 billion dollars) that calculated using a linear-linear dose-response function (149 billion dollars). The Centers for Disease Control and Prevention action limit of 10 microg/dL for children fails to protect against most damage and economic cost attributable to lead exposure.
Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

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

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

2005-12-16

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

NASA Astrophysics Data System (ADS)

Meyer, Sven; Bartelmann, Matthias

2017-11-01

We apply a generic formalism of light propagation to linearly perturbed spherically symmetric dust models including a cosmological constant. For a comoving observer on the central worldline, we derive the equation of geodesic deviation and perform a suitable spherical harmonic decomposition. This allows to map the abstract gauge-invariant perturbation variables to well-known quantities from weak gravitational lensing like convergence or cosmic shear. The resulting set of differential equations can effectively be solved by a Green's function approach leading to line-of-sight integrals sourced by the perturbation variables on the backward lightcone. The resulting spherical harmonic coefficients of the lensing observables are presented and the shear field is decomposed into its E- and B-modes. Results of this work are an essential tool to add information from linear structure formation to the analysis of spherically symmetric dust models with the purpose of testing the Copernican Principle with multiple cosmological probes.
Efficient Third-Order Distributed Feedback Laser with Enhanced Beam Pattern

NASA Technical Reports Server (NTRS)

Hu, Qing (Inventor); Lee, Alan Wei Min (Inventor); Kao, Tsung-Yu (Inventor)

2015-01-01

A third-order distributed feedback laser has an active medium disposed on a substrate as a linear array of segments having a series of periodically spaced interstices therebetween and a first conductive layer disposed on a surface of the active medium on each of the segments and along a strip from each of the segments to a conductive electrical contact pad for application of current along a path including the active medium. Upon application of a current through the active medium, the active medium functions as an optical waveguide, and there is established an alternating electric field, at a THz frequency, both in the active medium and emerging from the interstices. Spacing of adjacent segments is approximately half of a wavelength of the THz frequency in free space or an odd integral multiple thereof, so that the linear array has a coherence length greater than the length of the linear array.
The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.
Role of diversity in ICA and IVA: theory and applications

NASA Astrophysics Data System (ADS)

Adalı, Tülay

2016-05-01

Independent component analysis (ICA) has been the most popular approach for solving the blind source separation problem. Starting from a simple linear mixing model and the assumption of statistical independence, ICA can recover a set of linearly-mixed sources to within a scaling and permutation ambiguity. It has been successfully applied to numerous data analysis problems in areas as diverse as biomedicine, communications, finance, geo- physics, and remote sensing. ICA can be achieved using different types of diversity—statistical property—and, can be posed to simultaneously account for multiple types of diversity such as higher-order-statistics, sample dependence, non-circularity, and nonstationarity. A recent generalization of ICA, independent vector analysis (IVA), generalizes ICA to multiple data sets and adds the use of one more type of diversity, statistical dependence across the data sets, for jointly achieving independent decomposition of multiple data sets. With the addition of each new diversity type, identification of a broader class of signals become possible, and in the case of IVA, this includes sources that are independent and identically distributed Gaussians. We review the fundamentals and properties of ICA and IVA when multiple types of diversity are taken into account, and then ask the question whether diversity plays an important role in practical applications as well. Examples from various domains are presented to demonstrate that in many scenarios it might be worthwhile to jointly account for multiple statistical properties. This paper is submitted in conjunction with the talk delivered for the "Unsupervised Learning and ICA Pioneer Award" at the 2016 SPIE Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications.
On a generalized laminate theory with application to bending, vibration, and delamination buckling in composite laminates

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

Barbero, E.J.

1989-01-01

In this study, a computational model for accurate analysis of composite laminates and laminates with including delaminated interfaces is developed. An accurate prediction of stress distributions, including interlaminar stresses, is obtained by using the Generalized Laminate Plate Theory of Reddy in which layer-wise linear approximation of the displacements through the thickness is used. Analytical as well as finite-element solutions of the theory are developed for bending and vibrations of laminated composite plates for the linear theory. Geometrical nonlinearity, including buckling and postbuckling are included and used to perform stress analysis of laminated plates. A general two dimensional theory of laminatedmore » cylindrical shells is also developed in this study. Geometrical nonlinearity and transverse compressibility are included. Delaminations between layers of composite plates are modelled by jump discontinuity conditions at the interfaces. The theory includes multiple delaminations through the thickness. Geometric nonlinearity is included to capture layer buckling. The strain energy release rate distribution along the boundary of delaminations is computed by a novel algorithm. The computational models presented herein are accurate for global behavior and particularly appropriate for the study of local effects.« less
Intrauterine Linear Echogenicities in the Gravid Uterus: What Radiologists Should Know.

PubMed

Jensen, Kyle K; Oh, Karen Y; Kennedy, Anne M; Sohaey, Roya

2018-01-01

Intrauterine linear echogenicity (ILE) is a common ultrasonographic finding in the gravid uterus and has variable causes and variable maternal and fetal outcomes. Correctly categorizing ILE during pregnancy is crucial for guiding surveillance and advanced imaging strategies. Common causes of ILE include membranes in multiple gestations, uterine synechiae with amniotic sheets, and uterine duplication anomalies. Less common causes include circumvallate placenta, chorioamniotic separation, and hemorrhage between membranes. Amniotic band syndrome is a rare but important diagnosis to consider, as it causes severe fetal defects. Imaging findings enable body stalk anomaly, a lethal defect, to be distinguished from amniotic bands, which although destructive are not necessarily lethal. This review describes the key imaging findings used to differentiate the various types of ILE in pregnancy, thus enabling accurate diagnosis and appropriate patient counseling. Online supplemental material is available for this article. © RSNA, 2018.
Cumulative risk effects for the development of behaviour difficulties in children and adolescents with special educational needs and disabilities.

PubMed

Oldfield, Jeremy; Humphrey, Neil; Hebron, Judith

2015-01-01

Research has identified multiple risk factors for the development of behaviour difficulties. What have been less explored are the cumulative effects of exposure to multiple risks on behavioural outcomes, with no study specifically investigating these effects within a population of young people with special educational needs and disabilities (SEND). Furthermore, it is unclear whether a threshold or linear risk model better fits the data for this population. The sample included 2660 children and 1628 adolescents with SEND. Risk factors associated with increases in behaviour difficulties over an 18-month period were summed to create a cumulative risk score, with this explanatory variable being added into a multi-level model. A quadratic term was then added to test the threshold model. There was evidence of a cumulative risk effect, suggesting that exposure to higher numbers of risk factors, regardless of their exact nature, resulted in increased behaviour difficulties. The relationship between risk and behaviour difficulties was non-linear, with exposure to increasing risk having a disproportionate and detrimental impact on behaviour difficulties in child and adolescent models. Interventions aimed at reducing behaviour difficulties need to consider the impact of multiple risk variables. Tailoring interventions towards those exposed to large numbers of risks would be advantageous. Copyright © 2015 Elsevier Ltd. All rights reserved.
Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

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

2016-01-01

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

PubMed

Brown, Angus M

2006-04-01

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

NASA Astrophysics Data System (ADS)

Rapajic, Predrag B.; Vucetic, Branka S.

1994-05-01

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

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

Mayer, T.; Schroeder, D.

1996-09-01

In this paper the design of a robust control system for a parallel hybrid drivetrain is presented. The drivetrain is based on a continuously variable transmission (CVT) and is therefore a highly nonlinear multiple-input-multiple-output system (MIMO-System). Input-Output-Linearization offers the possibility of linearizing and of decoupling the system. Since for example the vehicle mass varies with the load and the efficiency of the gearbox depends strongly on the actual working point, an exact linearization of the plant will mostly fail. Therefore a robust control algorithm based on sliding mode is used to control the drivetrain.
SU-F-T-475: An Evaluation of the Overlap Between the Acceptance Testing and Commissioning Processes for Conventional Medical Linear Accelerators

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

Morrow, A; Rangaraj, D; Perez-Andujar, A

2016-06-15

Purpose: This work’s objective is to determine the overlap of processes, in terms of sub-processes and time, between acceptance testing and commissioning of a conventional medical linear accelerator and to evaluate the time saved by consolidating the two processes. Method: A process map for acceptance testing for medical linear accelerators was created from vendor documentation (Varian and Elekta). Using AAPM TG-106 and inhouse commissioning procedures, a process map was created for commissioning of said accelerators. The time to complete each sub-process in each process map was evaluated. Redundancies in the processes were found and the time spent on each weremore » calculated. Results: Mechanical testing significantly overlaps between the two processes - redundant work here amounts to 9.5 hours. Many beam non-scanning dosimetry tests overlap resulting in another 6 hours of overlap. Beam scanning overlaps somewhat - acceptance tests include evaluating PDDs and multiple profiles but for only one field size while commissioning beam scanning includes multiple field sizes and depths of profiles. This overlap results in another 6 hours of rework. Absolute dosimetry, field outputs, and end to end tests are not done at all in acceptance testing. Finally, all imaging tests done in acceptance are repeated in commissioning, resulting in about 8 hours of rework. The total time overlap between the two processes is about 30 hours. Conclusion: The process mapping done in this study shows that there are no tests done in acceptance testing that are not also recommended to do for commissioning. This results in about 30 hours of redundant work when preparing a conventional linear accelerator for clinical use. Considering these findings in the context of the 5000 linacs in the United states, consolidating acceptance testing and commissioning would have allowed for the treatment of an additional 25000 patients using no additional resources.« less

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

PubMed Central

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

2014-01-01

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

PubMed Central

Besada-Portas, Eva; Lopez-Orozco, Jose A.; Lanillos, Pablo; de la Cruz, Jesus M.

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost. PMID:22736962
Localization of non-linearly modeled autonomous mobile robots using out-of-sequence measurements.

PubMed

Besada-Portas, Eva; Lopez-Orozco, Jose A; Lanillos, Pablo; de la Cruz, Jesus M

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.
Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector

NASA Technical Reports Server (NTRS)

Huntington, Andrew

2013-01-01

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

NASA Astrophysics Data System (ADS)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.
Multiple Long-Time Solutions for Intermediate Reynolds Number Flow past a Circular Cylinder with a Nonlinear Inertial and Dissipative Attachment

NASA Astrophysics Data System (ADS)

Blanchard, Antoine B. E.; Bergman, Lawrence A.; Vakakis, Alexander F.; Pearlstein, Arne J.

2016-11-01

We consider two-dimensional flow past a linearly-sprung cylinder allowed to undergo rectilinear motion normal to the mean flow, with an attached "nonlinear energy sink" consisting of a mass allowed to rotate about the cylinder axis, and whose rotational motion is linearly damped by a viscous damper. For Re < 50, where the flow is expected to be two-dimensional, we use different inlet transients to identify multiple long-time solutions, and to study how they depend on Re and a dimensionless spring constant. For fixed values of the ratio of cylinder density to fluid density, dimensionless damping coefficient, and ratio of the rotating mass to the total mass, we find that different inlet transients lead to different long-time solutions, including solutions that are steady and symmetric (with a motionless cylinder), time-periodic, quasi-periodic, and chaotic. The results show that over a wide range of the parameters, the steady symmetric motionless-cylinder solution is locally, but not globally, stable. Supported by NSF Grant CMMI-1363231.
Mental ability and psychological work performance in Chinese workers.

PubMed

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

2006-10-01

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

NASA Astrophysics Data System (ADS)

Walker, D. D.; Cello, P. A.; Valocchi, A. J.; Roberts, R. M.; Loftis, B.

2008-12-01

The Generalized Radial Flow approach to hydraulic test interpretation infers the flow dimension to describe the geometry of the flow field during a hydraulic test. Noninteger values of the flow dimension often are inferred for tests in highly heterogeneous aquifers, yet subsequent modeling studies typically ignore the flow dimension. Monte Carlo analyses of detailed numerical models of aquifer tests examine the flow dimension for several stochastic models of heterogeneous transmissivity, T(x). These include multivariate lognormal, fractional Brownian motion, a site percolation network, and discrete linear features with lengths distributed as power-law. The behavior of the simulated flow dimensions are compared to the flow dimensions observed for multiple aquifer tests in a fractured dolomite aquifer in the Great Lakes region of North America. The combination of multiple hydraulic tests, observed fracture patterns, and the Monte Carlo results are used to screen models of heterogeneity and their parameters for subsequent groundwater flow modeling. The comparison shows that discrete linear features with lengths distributed as a power-law appear to be the most consistent with observations of the flow dimension in fractured dolomite aquifers.
Interface Technology for Geometrically Nonlinear Analysis of Multiple Connected Subdomains

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.

1997-01-01

Interface technology for geometrically nonlinear analysis is presented and demonstrated. This technology is based on an interface element which makes use of a hybrid variational formulation to provide for compatibility between independently modeled connected subdomains. The interface element developed herein extends previous work to include geometric nonlinearity and to use standard linear and nonlinear solution procedures. Several benchmark nonlinear applications of the interface technology are presented and aspects of the implementation are discussed.
Minimizing energy dissipation of matrix multiplication kernel on Virtex-II

NASA Astrophysics Data System (ADS)

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

2002-07-01

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

ERIC Educational Resources Information Center

Groves, Kevin S.; Vance, Charles M.

2015-01-01

Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…
Multiple Intelligence Scores of Science Stream Students and Their Relation with Reading Competency in Malaysian University English Test (MUET)

ERIC Educational Resources Information Center

Razak, Norizan Abdul; Zaini, Nuramirah

2014-01-01

Many researches have shown that different approach needed in analysing linear and non-linear reading comprehension texts and different cognitive skills are required. This research attempts to discover the relationship between Science Stream students' reading competency on linear and non-linear texts in Malaysian University English Test (MUET) with…
Comparison of two-concentration with multi-concentration linear regressions: Retrospective data analysis of multiple regulated LC-MS bioanalytical projects.

PubMed

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

2013-09-01

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

PubMed Central

Douglas, Alexander D.; Edwards, Nick J.; Duncan, Christopher J. A.; Thompson, Fiona M.; Sheehy, Susanne H.; O'Hara, Geraldine A.; Anagnostou, Nicholas; Walther, Michael; Webster, Daniel P.; Dunachie, Susanna J.; Porter, David W.; Andrews, Laura; Gilbert, Sarah C.; Draper, Simon J.; Hill, Adrian V. S.; Bejon, Philip

2013-01-01

Controlled human malaria infection is used to measure efficacy of candidate malaria vaccines before field studies are undertaken. Mathematical modeling using data from quantitative polymerase chain reaction (qPCR) parasitemia monitoring can discriminate between vaccine effects on the parasite's liver and blood stages. Uncertainty regarding the most appropriate modeling method hinders interpretation of such trials. We used qPCR data from 267 Plasmodium falciparum infections to compare linear, sine-wave, and normal-cumulative-density-function models. We find that the parameters estimated by these models are closely correlated, and their predictive accuracy for omitted data points was similar. We propose that future studies include the linear model. PMID:23570846
Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach

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

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr; Piunovskiy, A. B., E-mail: piunov@liv.ac.uk

2016-08-15

In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures ofmore » the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.« less
Linear stability analysis of scramjet unstart

NASA Astrophysics Data System (ADS)

Jang, Ik; Nichols, Joseph; Moin, Parviz

2015-11-01

We investigate the bifurcation structure of unstart and restart events in a dual-mode scramjet using the Reynolds-averaged Navier-Stokes equations. The scramjet of interest (HyShot II, Laurence et al., AIAA2011-2310) operates at a free-stream Mach number of approximately 8, and the length of the combustor chamber is 300mm. A heat-release model is applied to mimic the combustion process. Pseudo-arclength continuation with Newton-Raphson iteration is used to calculate multiple solution branches. Stability analysis based on linearized dynamics about the solution curves reveals a metric that optimally forewarns unstart. By combining direct and adjoint eigenmodes, structural sensitivity analysis suggests strategies for unstart mitigation, including changing the isolator length. This work is supported by DOE/NNSA and AFOSR.
DYGABCD: A program for calculating linear A, B, C, and D matrices from a nonlinear dynamic engine simulation

NASA Technical Reports Server (NTRS)

Geyser, L. C.

1978-01-01

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

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

2014-05-21

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

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2002-01-01

An infrared imager, such as a spectrometer, includes multiple infrared photodetectors and readout circuits for reading out signals from the photodetectors. Each readout circuit includes a buffered direct injection input circuit including a differential amplifier with active feedback provided through an injection transistor. The differential amplifier includes a pair of input transistors, a pair of cascode transistors and a current mirror load. Photocurrent from a photodetector can be injected onto an integration capacitor in the readout circuit with high injection efficiency at high speed. A high speed, low noise, wide dynamic range linear infrared multiplexer array for reading out infrared detectors with large capacitances can be achieved even when short exposure times are used. The effect of image lag can be reduced.

Mixed H∞ and passive control for linear switched systems via hybrid control approach

NASA Astrophysics Data System (ADS)

Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

2018-03-01

This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.
Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.
Structural Equation Modeling: A Framework for Ocular and Other Medical Sciences Research

PubMed Central

Christ, Sharon L.; Lee, David J.; Lam, Byron L.; Diane, Zheng D.

2017-01-01

Structural equation modeling (SEM) is a modeling framework that encompasses many types of statistical models and can accommodate a variety of estimation and testing methods. SEM has been used primarily in social sciences but is increasingly used in epidemiology, public health, and the medical sciences. SEM provides many advantages for the analysis of survey and clinical data, including the ability to model latent constructs that may not be directly observable. Another major feature is simultaneous estimation of parameters in systems of equations that may include mediated relationships, correlated dependent variables, and in some instances feedback relationships. SEM allows for the specification of theoretically holistic models because multiple and varied relationships may be estimated together in the same model. SEM has recently expanded by adding generalized linear modeling capabilities that include the simultaneous estimation of parameters of different functional form for outcomes with different distributions in the same model. Therefore, mortality modeling and other relevant health outcomes may be evaluated. Random effects estimation using latent variables has been advanced in the SEM literature and software. In addition, SEM software has increased estimation options. Therefore, modern SEM is quite general and includes model types frequently used by health researchers, including generalized linear modeling, mixed effects linear modeling, and population average modeling. This article does not present any new information. It is meant as an introduction to SEM and its uses in ocular and other health research. PMID:24467557
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

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 computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.
Pre-natal exposures to cocaine and alcohol and physical growth patterns to age 8 years

PubMed Central

Lumeng, Julie C.; Cabral, Howard J.; Gannon, Katherine; Heeren, Timothy; Frank, Deborah A.

2007-01-01

Two hundred and two primarily African American/Caribbean children (classified by maternal report and infant meconium as 38 heavier, 74 lighter and 89 not cocaine-exposed) were measured repeatedly from birth to age 8 years to assess whether there is an independent effect of prenatal cocaine exposure on physical growth patterns. Children with fetal alcohol syndrome identifiable at birth were excluded. At birth, cocaine and alcohol exposures were significantly and independently associated with lower weight, length and head circumference in cross-sectional multiple regression analyses. The relationship over time of pre-natal exposures to weight, height, and head circumference was then examined by multiple linear regression using mixed linear models including covariates: child’s gestational age, gender, ethnicity, age at assessment, current caregiver, birth mother’s use of alcohol, marijuana and tobacco during the pregnancy and pre-pregnancy weight (for child’s weight) and height (for child’s height and head circumference). The cocaine effects did not persist beyond infancy in piecewise linear mixed models, but a significant and independent negative effect of pre-natal alcohol exposure persisted for weight, height, and head circumference. Catch-up growth in cocaine-exposed infants occurred primarily by 6 months of age for all growth parameters, with some small fluctuations in growth rates in the preschool age range but no detectable differences between heavier versus unexposed nor lighter versus unexposed thereafter. PMID:17412558
Substituting values for censored data from Texas, USA, reservoirs inflated and obscured trends in analyses commonly used for water quality target development.

PubMed

Grantz, Erin; Haggard, Brian; Scott, J Thad

2018-06-12

We calculated four median datasets (chlorophyll a, Chl a; total phosphorus, TP; and transparency) using multiple approaches to handling censored observations, including substituting fractions of the quantification limit (QL; dataset 1 = 1QL, dataset 2 = 0.5QL) and statistical methods for censored datasets (datasets 3-4) for approximately 100 Texas, USA reservoirs. Trend analyses of differences between dataset 1 and 3 medians indicated percent difference increased linearly above thresholds in percent censored data (%Cen). This relationship was extrapolated to estimate medians for site-parameter combinations with %Cen > 80%, which were combined with dataset 3 as dataset 4. Changepoint analysis of Chl a- and transparency-TP relationships indicated threshold differences up to 50% between datasets. Recursive analysis identified secondary thresholds in dataset 4. Threshold differences show that information introduced via substitution or missing due to limitations of statistical methods biased values, underestimated error, and inflated the strength of TP thresholds identified in datasets 1-3. Analysis of covariance identified differences in linear regression models relating transparency-TP between datasets 1, 2, and the more statistically robust datasets 3-4. Study findings identify high-risk scenarios for biased analytical outcomes when using substitution. These include high probability of median overestimation when %Cen > 50-60% for a single QL, or when %Cen is as low 16% for multiple QL's. Changepoint analysis was uniquely vulnerable to substitution effects when using medians from sites with %Cen > 50%. Linear regression analysis was less sensitive to substitution and missing data effects, but differences in model parameters for transparency cannot be discounted and could be magnified by log-transformation of the variables.
A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

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

2010-01-01

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

DTIC Science & Technology

2013-01-01

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

PubMed Central

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

2015-01-01

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

PubMed

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

2015-05-01

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

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.
Children's environmental chemical exposures in the USA, NHANES 2003-2012.

PubMed

Hendryx, Michael; Luo, Juhua

2018-02-01

Children are vulnerable to environmental chemical exposures, but little is known about the extent of multiple chemical exposures among children. We analyzed biomonitoring data from five cycles (2003-2012) of the National Health and Nutrition Examination Survey (NHANES) to describe multiple chemical exposures in US children, examine levels of chemical concentrations present over time, and examine differences in chemical exposures by selected demographic groups. We analyzed data for 36 chemical analytes across five chemical classes in a sample of 4299 children aged 6-18. Classes included metals, pesticides, phthalates, phenols, and polycyclic aromatic hydrocarbons. We calculated the number and percent of chemicals detected and tested for secular trends over time in chemical concentrations. We compared log concentrations among groups defined by age, sex, race/ethnicity, and poverty using multiple linear regression models and report adjusted geometric means. Among a smaller subgroup of 733 children with data across chemical classes, we calculated the linear correlations within and between classes and conducted a principal component analysis. The percentage of children with detectable concentrations of an individual chemical ranged from 26 to 100%; the average was 93%, and 29 of 36 were detected in more than 90% of children. Concentrations of most tested chemicals were either unchanged or declined from earlier to more recent years. Many differences in concentrations were present by age, sex, poverty, and race/ethnicity categories. Within and between class correlations were all significant and positive, and the principal component analysis suggested a one factor solution, indicating that children exposed to higher levels of one chemical were exposed to higher levels of other chemicals. In conclusion, children in the USA are exposed to multiple simultaneous chemicals at uneven risk across socioeconomic and demographic groups. Further efforts to understand the effects of multiple exposures on child health and development are warranted.
Impacts of education level and employment status on health-related quality of life in multiple sclerosis patients.

PubMed

Šabanagić-Hajrić, Selma; Alajbegović, Azra

2015-02-01

To evaluate the impacts of education level and employment status on health-related quality of life (HRQoL) in multiple sclerosis patients. This study included 100 multiple sclerosis patients treated at the Department of Neurology, Clinical Center of the University of Sarajevo. Inclusion criteria were the Expanded Disability Status Scale (EDSS) score between 1.0 and 6.5, age between 18 and 65 years, stable disease on enrollment. Quality of life (QoL) was evaluated by the Multiple Sclerosis Quality of Life-54 questionnaire (MSQoL-54). Mann-Whitney and Kruskal-Wallis test were used for comparisons. Linear regression analyses were performed to evaluate prediction value of educational level and employment status in predicting MSQOL-54 physical and mental composite scores. Full employment status had positive impact on physical health (54.85 vs. 37.90; p les than 0.001) and mental health (59.55 vs. 45.90; p les than 0.001) composite scores. Employment status retained its independent predictability for both physical (r(2)=0.105) and mental (r(2)=0.076) composite scores in linear regression analysis. Patients with college degree had slightly higher median value of physical (49.36 vs. 45.30) and mental health composite score (66.74 vs. 55.62) comparing to others, without statistically significant difference. Employment proved to be an important factor in predicting quality of life in multiple sclerosis patients. Higher education level may determine better QOL but without significant predictive value. Sustained employment and development of vocational rehabilitation programs for MS patients living in the country with high unemployment level is an important factor in improving both physical and mental health outcomes in MS patients.
Self-interaction of NPM1 modulates multiple mechanisms of liquid-liquid phase separation.

PubMed

Mitrea, Diana M; Cika, Jaclyn A; Stanley, Christopher B; Nourse, Amanda; Onuchic, Paulo L; Banerjee, Priya R; Phillips, Aaron H; Park, Cheon-Gil; Deniz, Ashok A; Kriwacki, Richard W

2018-02-26

Nucleophosmin (NPM1) is an abundant, oligomeric protein in the granular component of the nucleolus with roles in ribosome biogenesis. Pentameric NPM1 undergoes liquid-liquid phase separation (LLPS) via heterotypic interactions with nucleolar components, including ribosomal RNA (rRNA) and proteins which display multivalent arginine-rich linear motifs (R-motifs), and is integral to the liquid-like nucleolar matrix. Here we show that NPM1 can also undergo LLPS via homotypic interactions between its polyampholytic intrinsically disordered regions, a mechanism that opposes LLPS via heterotypic interactions. Using a combination of biophysical techniques, including confocal microscopy, SAXS, analytical ultracentrifugation, and single-molecule fluorescence, we describe how conformational changes within NPM1 control valency and switching between the different LLPS mechanisms. We propose that this newly discovered interplay between multiple LLPS mechanisms may influence the direction of vectorial pre-ribosomal particle assembly within, and exit from the nucleolus as part of the ribosome biogenesis process.
A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester

2010-01-01

A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.
Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1985-01-01

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.
Wing Shaping and Gust Load Controls of Flexible Aircraft: An LPV Approach

NASA Technical Reports Server (NTRS)

Hammerton, Jared R.; Su, Weihua; Zhu, Guoming; Swei, Sean Shan-Min

2018-01-01

In the proposed paper, the optimum wing shape of a highly flexible aircraft under varying flight conditions will be controlled by a linear parameter-varying approach. The optimum shape determined under multiple objectives, including flight performance, ride quality, and control effort, will be determined as well. This work is an extension of work done previously by the authors, and updates the existing optimization and utilizes the results to generate a robust flight controller.
Working memory span in mild cognitive impairment. Influence of processing speed and cognitive reserve.

PubMed

Facal, David; Juncos-Rabadán, Onésimo; Pereiro, Arturo X; Lojo-Seoane, Cristina

2014-04-01

Mild cognitive impairment (MCI) often includes episodic memory impairment, but can also involve other types of cognitive decline. Although previous studies have shown poorer performance of MCI patients in working memory (WM) span tasks, different MCI subgroups were not studied. In the present exploratory study, 145 participants underwent extensive cognitive evaluation, which included three different WM span tasks, and were classified into the following groups: multiple-domain amnestic MCI (mda-MCI), single-domain amnestic MCI (sda-MCI), and controls. General linear model was conducted by considering the WM span tasks as the within-subject factor; the group (mda-MCI, sda-MCI, and controls) as the inter-subject factor; and processing speed, vocabulary and age as covariates. Multiple linear regression models were also used to test the influence of processing speed, vocabulary, and other cognitive reserve (CR) proxies. Results indicate different levels of impairment of WM, with more severe impairment in mda-MCI patients. The differences were still present when processing resources and CR were controlled. Between-group differences can be understood as a manifestation of the greater severity and widespread memory impairment in mda-MCI patients and may contribute to a better understanding of continuum from normal controls to mda-MCI patients. Processing speed and CR have a limited influence on WM scores, reducing but not removing differences between groups.
A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem

NASA Technical Reports Server (NTRS)

Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad

2010-01-01

Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.

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

PubMed

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

2015-01-01

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

PubMed

Coon, K A; Goldberg, J; Rogers, B L; Tucker, K L

2001-01-01

We examined relationships between the presence of television during meals and children's food consumption patterns to test whether children's overall food consumption patterns, including foods not normally advertised, vary systematically with the extent to which television is part of normal mealtime routines. Ninety-one parent-child pairs from suburbs adjacent to Washington, DC, recruited via advertisements and word of mouth, participated. Children were in the fourth, fifth, or sixth grades. Socioeconomic data and information on television use were collected during survey interviews. Three nonconsecutive 24-hour dietary recalls, conducted with each child, were used to construct nutrient and food intake outcome variables. Independent sample t tests were used to compare mean food and nutrient intakes of children from families in which the television was usually on during 2 or more meals (n = 41) to those of children from families in which the television was either never on or only on during one meal (n = 50). Multiple linear regression models, controlling for socioeconomic factors and other covariates, were used to test strength of associations between television and children's consumption of food groups and nutrients. Children from families with high television use derived, on average, 6% more of their total daily energy intake from meats; 5% more from pizza, salty snacks, and soda; and nearly 5% less of their energy intake from fruits, vegetables, and juices than did children from families with low television use. Associations between television and children's consumption of food groups remained statistically significant in multiple linear regression models that controlled for socioeconomic factors and other covariates. Children from high television families derived less of their total energy from carbohydrate and consumed twice as much caffeine as children from low television families. There continued to be a significant association between television and children's consumption of caffeine when these relationships were tested in multiple linear regression models. The dietary patterns of children from families in which television viewing is a normal part of meal routines may include fewer fruits and vegetables and more pizzas, snack foods, and sodas than the dietary patterns of children from families in which television viewing and eating are separate activities.
Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad

2014-05-01

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

NASA Technical Reports Server (NTRS)

Sheen, Jyh-Jong; Bishop, Robert H.

1992-01-01

The feedback linearization technique is applied to the problem of spacecraft attitude control and momentum management with control moment gyros (CMGs). The feedback linearization consists of a coordinate transformation, which transforms the system to a companion form, and a nonlinear feedback control law to cancel the nonlinear dynamics resulting in a linear equivalent model. Pole placement techniques are then used to place the closed-loop poles. The coordinate transformation proposed here evolves from three output functions of relative degree four, three, and two, respectively. The nonlinear feedback control law is presented. Stability in a neighborhood of a controllable torque equilibrium attitude (TEA) is guaranteed and this fact is demonstrated by the simulation results. An investigation of the nonlinear control law shows that singularities exist in the state space outside the neighborhood of the controllable TEA. The nonlinear control law is simplified by a standard linearization technique and it is shown that the linearized nonlinear controller provides a natural way to select control gains for the multiple-input, multiple-output system. Simulation results using the linearized nonlinear controller show good performance relative to the nonlinear controller in the neighborhood of the TEA.
A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Li, Jun

2002-09-01

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

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam; DiMaggio, John A

2012-12-01

Stature estimation is considered as one of the basic parameters of the investigation process in unknown and commingled human remains in medico-legal case work. Race, age and sex are the other parameters which help in this process. Stature estimation is of the utmost importance as it completes the biological profile of a person along with the other three parameters of identification. The present research is intended to formulate standards for stature estimation from foot dimensions in adolescent males from North India and study the pattern of foot growth during the growing years. 154 male adolescents from the Northern part of India were included in the study. Besides stature, five anthropometric measurements that included the length of the foot from each toe (T1, T2, T3, T4, and T5 respectively) to pternion were measured on each foot. The data was analyzed statistically using Student's t-test, Pearson's correlation, linear and multiple regression analysis for estimation of stature and growth of foot during ages 13-18 years. Correlation coefficients between stature and all the foot measurements were found to be highly significant and positively correlated. Linear regression models and multiple regression models (with age as a co-variable) were derived for estimation of stature from the different measurements of the foot. Multiple regression models (with age as a co-variable) estimate stature with greater accuracy than the regression models for 13-18 years age group. The study shows the growth pattern of feet in North Indian adolescents and indicates that anthropometric measurements of the foot and its segments are valuable in estimation of stature in growing individuals of that population. Copyright © 2012 Elsevier Ltd. All rights reserved.
[Stature estimation for Sichuan Han nationality female based on X-ray technology with measurement of lumbar vertebrae].

PubMed

Qing, Si-han; Chang, Yun-feng; Dong, Xiao-ai; Li, Yuan; Chen, Xiao-gang; Shu, Yong-kang; Deng, Zhen-hua

2013-10-01

To establish the mathematical models of stature estimation for Sichuan Han female with measurement of lumbar vertebrae by X-ray to provide essential data for forensic anthropology research. The samples, 206 Sichuan Han females, were divided into three groups including group A, B and C according to the ages. Group A (206 samples) consisted of all ages, group B (116 samples) were 20-45 years old and 90 samples over 45 years old were group C. All the samples were examined lumbar vertebrae through CR technology, including the parameters of five centrums (L1-L5) as anterior border, posterior border and central heights (x1-x15), total central height of lumbar spine (x16), and the real height of every sample. The linear regression analysis was produced using the parameters to establish the mathematical models of stature estimation. Sixty-two trained subjects were tested to verify the accuracy of the mathematical models. The established mathematical models by hypothesis test of linear regression equation model were statistically significant (P<0.05). The standard errors of the equation were 2.982-5.004 cm, while correlation coefficients were 0.370-0.779 and multiple correlation coefficients were 0.533-0.834. The return tests of the highest correlation coefficient and multiple correlation coefficient of each group showed that the highest accuracy of the multiple regression equation, y = 100.33 + 1.489 x3 - 0.548 x6 + 0.772 x9 + 0.058 x12 + 0.645 x15, in group A were 80.6% (+/- lSE) and 100% (+/- 2SE). The established mathematical models in this study could be applied for the stature estimation for Sichuan Han females.
Learning in the Machine: Random Backpropagation and the Deep Learning Channel.

PubMed

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2018-07-01

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and learning channels. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.
Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

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

NASA Astrophysics Data System (ADS)

Huang, Rui; Hu, Haiyan; Zhao, Yonghui

2013-10-01

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

PubMed

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

2015-05-01

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

PubMed

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

2016-12-01

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

NASA Technical Reports Server (NTRS)

Huba, J. D.; Chen, J.; Anderson, R. R.

1992-01-01

Attention is given to a mechanism to generate a broad spectrum of electrostatic turbulence in the quiet time central plasma sheet (CPS) plasma. It is shown theoretically that multiple-ring ion distributions can generate short-wavelength (less than about 1), electrostatic turbulence with frequencies less than about kVj, where Vj is the velocity of the jth ring. On the basis of a set of parameters from measurements made in the CPS, it is found that electrostatic turbulence can be generated with wavenumbers in the range of 0.02 and 1.0, with real frequencies in the range of 0 and 10, and with linear growth rates greater than 0.01 over a broad range of angles relative to the magnetic field (5-90 deg). These theoretical results are compared with wave data from ISEE 1 using an ion distribution function exhibiting multiple-ring structures observed at the same time. The theoretical results in the linear regime are found to be consistent with the wave data.
Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

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

PubMed Central

Maity, Arnab; Williams, Paige; Ryan, Louise; Missmer, Stacey; Coull, Brent; Hauser, Russ

2014-01-01

In vitro fertilization (IVF) is an increasingly common method of assisted reproductive technology. Because of the careful observation and followup required as part of the procedure, IVF studies provide an ideal opportunity to identify and assess clinical and demographic factors along with environmental exposures that may impact successful reproduction. A major challenge in analyzing data from IVF studies is handling the complexity and multiplicity of outcome, resulting from both multiple opportunities for pregnancy loss within a single IVF cycle in addition to multiple IVF cycles. To date, most evaluations of IVF studies do not make use of full data due to its complex structure. In this paper, we develop statistical methodology for analysis of IVF data with multiple cycles and possibly multiple failure types observed for each individual. We develop a general analysis framework based on a generalized linear modeling formulation that allows implementation of various types of models including shared frailty models, failure specific frailty models, and transitional models, using standard software. We apply our methodology to data from an IVF study conducted at the Brigham and Women’s Hospital, Massachusetts. We also summarize the performance of our proposed methods based on a simulation study. PMID:24317880
The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.
An Efficient Spectral Method for Ordinary Differential Equations with Rational Function Coefficients

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

EPA Science Inventory

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

ERIC Educational Resources Information Center

Schnittjer, Carl J.

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

Nonlinear Optical Image Processing with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.; Deiss, Ron (Technical Monitor)

1994-01-01

The transmission properties of some bacteriorhodopsin film spatial light modulators are uniquely suited to allow nonlinear optical image processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude transmission feature of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. The bacteriorhodopsin film displays the logarithmic amplitude response for write beam intensities spanning a dynamic range greater than 2.0 orders of magnitude. We present experimental results demonstrating the principle and capability for several different image and noise situations, including deterministic noise and speckle. Using the bacteriorhodopsin film, we successfully filter out image noise from the transformed image that cannot be removed from the original image.
Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.
Elegant anti-disturbance control for discrete-time stochastic systems with nonlinearity and multiple disturbances

NASA Astrophysics Data System (ADS)

Wei, Xinjiang; Sun, Shixiang

2018-03-01

An elegant anti-disturbance control (EADC) strategy for a class of discrete-time stochastic systems with both nonlinearity and multiple disturbances, which include the disturbance with partially known information and a sequence of random vectors, is proposed in this paper. A stochastic disturbance observer is constructed to estimate the disturbance with partially known information, based on which, an EADC scheme is proposed by combining pole placement and linear matrix inequality methods. It is proved that the two different disturbances can be rejected and attenuated, and the corresponding desired performances can be guaranteed for discrete-time stochastic systems with known and unknown nonlinear dynamics, respectively. Simulation examples are given to demonstrate the effectiveness of the proposed schemes compared with some existing results.
A density functional theory for colloids with two multiple bonding associating sites.

PubMed

Haghmoradi, Amin; Wang, Le; Chapman, Walter G

2016-06-22

Wertheim's multi-density formalism is extended for patchy colloidal fluids with two multiple bonding patches. The theory is developed as a density functional theory to predict the properties of an associating inhomogeneous fluid. The equation of state developed for this fluid depends on the size of the patch, and includes formation of cyclic, branched and linear clusters of associated species. The theory predicts the density profile and the fractions of colloids in different bonding states versus the distance from one wall as a function of bulk density and temperature. The predictions from our theory are compared with previous results for a confined fluid with four single bonding association sites. Also, comparison between the present theory and Monte Carlo simulation indicates a good agreement.
High resolution, multiple-energy linear sweep detector for x-ray imaging

DOEpatents

Perez-Mendez, Victor; Goodman, Claude A.

1996-01-01

Apparatus for generating plural electrical signals in a single scan in response to incident X-rays received from an object. Each electrical signal represents an image of the object at a different range of energies of the incident X-rays. The apparatus comprises a first X-ray detector, a second X-ray detector stacked upstream of the first X-ray detector, and an X-ray absorber stacked upstream of the first X-ray detector. The X-ray absorber provides an energy-dependent absorption of the incident X-rays before they are incident at the first X-ray detector, but provides no absorption of the incident X-rays before they are incident at the second X-ray detector. The first X-ray detector includes a linear array of first pixels, each of which produces an electrical output in response to the incident X-rays in a first range of energies. The first X-ray detector also includes a circuit that generates a first electrical signal in response to the electrical output of each of the first pixels. The second X-ray detector includes a linear array of second pixels, each of which produces an electrical output in response to the incident X-rays in a second range of energies, broader than the first range of energies. The second X-ray detector also includes a circuit that generates a second electrical signal in response to the electrical output of each of the second pixels.
High resolution, multiple-energy linear sweep detector for x-ray imaging

DOEpatents

Perez-Mendez, V.; Goodman, C.A.

1996-08-20

Apparatus is disclosed for generating plural electrical signals in a single scan in response to incident X-rays received from an object. Each electrical signal represents an image of the object at a different range of energies of the incident X-rays. The apparatus comprises a first X-ray detector, a second X-ray detector stacked upstream of the first X-ray detector, and an X-ray absorber stacked upstream of the first X-ray detector. The X-ray absorber provides an energy-dependent absorption of the incident X-rays before they are incident at the first X-ray detector, but provides no absorption of the incident X-rays before they are incident at the second X-ray detector. The first X-ray detector includes a linear array of first pixels, each of which produces an electrical output in response to the incident X-rays in a first range of energies. The first X-ray detector also includes a circuit that generates a first electrical signal in response to the electrical output of each of the first pixels. The second X-ray detector includes a linear array of second pixels, each of which produces an electrical output in response to the incident X-rays in a second range of energies, broader than the first range of energies. The second X-ray detector also includes a circuit that generates a second electrical signal in response to the electrical output of each of the second pixels. 12 figs.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less
Mode trap for absorbing transverse modes of an accelerated electron beam

DOEpatents

Chojnacki, Eric P.

1994-01-01

A mode trap to trap and absorb transverse modes formed by a beam in a linear accelerator includes a waveguide having a multiplicity of electrically conductive (preferably copper) irises and rings, each iris and ring including an aperture, and the irises and rings being stacked in a side-by-side, alternating fashion such that the apertures of the irises and rings are concentrically aligned. An absorbing material layer such as a dielectric is embedded in each iris and ring, and this absorbing material layer encircles, but is circumferentially spaced from its respective aperture. Each iris and ring includes a plurality of circumferentially spaced slots around its aperture and extending radially out toward its absorbing material layer.
Repeatability of road pavement condition assessment based on three-dimensional analysis of linear accelerations of vehicles

NASA Astrophysics Data System (ADS)

Staniek, Marcin

2018-05-01

The article provides a discussion concerning a tool used for road pavement condition assessment based on signals of linear accelerations recorded with high sampling frequency for typical vehicles traversing the road network under real-life road traffic conditions. Specific relationships have been established for the sake of road pavement condition assessment, including identification of road sections of poor technical condition. The data thus acquired have been verified with regard to repeatability of estimated road pavement assessment indices. The data make it possible to describe the road network status against an area in which users of the system being developed move. What proves to be crucial in the assessment process is the scope of the data set based on multiple transfers within the road network.
Finite-element time-domain algorithms for modeling linear Debye and Lorentz dielectric dispersions at low frequencies.

PubMed

Stoykov, Nikolay S; Kuiken, Todd A; Lowery, Madeleine M; Taflove, Allen

2003-09-01

We present what we believe to be the first algorithms that use a simple scalar-potential formulation to model linear Debye and Lorentz dielectric dispersions at low frequencies in the context of finite-element time-domain (FETD) numerical solutions of electric potential. The new algorithms, which permit treatment of multiple-pole dielectric relaxations, are based on the auxiliary differential equation method and are unconditionally stable. We validate the algorithms by comparison with the results of a previously reported method based on the Fourier transform. The new algorithms should be useful in calculating the transient response of biological materials subject to impulsive excitation. Potential applications include FETD modeling of electromyography, functional electrical stimulation, defibrillation, and effects of lightning and impulsive electric shock.
The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

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

2018-05-18

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

PubMed Central

Caccese, V.; Ferguson, J.; Lloyd, J.; Edgecomb, M.; Seidi, M.; Hajiaghamemar, M.

2017-01-01

A test method based upon a Hybrid-III head and neck assembly that includes measurement of both linear and angular acceleration is investigated for potential use in impact testing of protective headgear. The test apparatus is based upon a twin wire drop test system modified with the head/neck assembly and associated flyarm components. This study represents a preliminary assessment of the test apparatus for use in the development of protective headgear designed to prevent injury due to falls. By including angular acceleration in the test protocol it becomes possible to assess and intentionally reduce this component of acceleration. Comparisons of standard and reduced durometer necks, various anvils, front, rear, and side drop orientations, and response data on performance of the apparatus are provided. Injury measures summarized for an unprotected drop include maximum linear and angular acceleration, head injury criteria (HIC), rotational injury criteria (RIC), and power rotational head injury criteria (PRHIC). Coefficient of variation for multiple drops ranged from 0.4 to 6.7% for linear acceleration. Angular acceleration recorded in a side drop orientation resulted in highest coefficient of variation of 16.3%. The drop test apparatus results in a reasonably repeatable test method that has potential to be used in studies of headgear designed to reduce head impact injury. PMID:28216804
Probabilistic lifetime strength of aerospace materials via computational simulation

NASA Technical Reports Server (NTRS)

Boyce, Lola; Keating, Jerome P.; Lovelace, Thomas B.; Bast, Callie C.

1991-01-01

The results of a second year effort of a research program are presented. The research included development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic phenomenological constitutive relationship, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects of primitive variables. These primitive variables often originate in the environment and may include stress from loading, temperature, chemical, or radiation attack. This multifactor interaction constitutive equation is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the constitutive equation using actual experimental materials data together with the multiple linear regression of that data.
The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

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

2017-01-01

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

DTIC Science & Technology

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

ERIC Educational Resources Information Center

Ausburn, Floyd B.

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

PubMed

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

2006-08-01

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

NASA Technical Reports Server (NTRS)

Martin, J. A.

1974-01-01

A general analytical treatment is presented of a single-stage vehicle with multiple propulsion phases. A closed-form solution for the cost and for the performance and a derivation of the optimal phasing of the propulsion are included. Linearized variations in the inert weight elements are included, and the function to be minimized can be selected. The derivation of optimal phasing results in a set of nonlinear algebraic equations for optimal fuel volumes, for which a solution method is outlined. Three specific example cases are analyzed: minimum gross lift-off weight, minimum inert weight, and a minimized general function for a two-phase vehicle. The results for the two-phase vehicle are applied to the dual-fuel rocket. Comparisons with single-fuel vehicles indicate that dual-fuel vehicles can have lower inert weight either by development of a dual-fuel engine or by parallel burning of separate engines from lift-off.
Step responses of a torsional system with multiple clearances: Study of vibro-impact phenomenon using experimental and computational methods

NASA Astrophysics Data System (ADS)

Oruganti, Pradeep Sharma; Krak, Michael D.; Singh, Rajendra

2018-01-01

Recently Krak and Singh (2017) proposed a scientific experiment that examined vibro-impacts in a torsional system under a step down excitation and provided preliminary measurements and limited non-linear model studies. A major goal of this article is to extend the prior work with a focus on the examination of vibro-impact phenomena observed under step responses in a torsional system with one, two or three controlled clearances. First, new measurements are made at several locations with a higher sampling frequency. Measured angular accelerations are examined in both time and time-frequency domains. Minimal order non-linear models of the experiment are successfully constructed, using piecewise linear stiffness and Coulomb friction elements; eight cases of the generic system are examined though only three are experimentally studied. Measured and predicted responses for single and dual clearance configurations exhibit double sided impacts and time varying periods suggest softening trends under the step down torque. Non-linear models are experimentally validated by comparing results with new measurements and with those previously reported. Several metrics are utilized to quantify and compare the measured and predicted responses (including peak to peak accelerations). Eigensolutions and step responses of the corresponding linearized models are utilized to better understand the nature of the non-linear dynamic system. Finally, the effect of step amplitude on the non-linear responses is examined for several configurations, and hardening trends are observed in the torsional system with three clearances.
An improved null model for assessing the net effects of multiple stressors on communities.

PubMed

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

2018-01-01

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

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

PubMed

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

2007-10-01

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

NASA Technical Reports Server (NTRS)

Richard, H. L.; Barnes, W. L.

1985-01-01

Several techniques that can be used in an earth-imaging system to separate the linear image formed after the collecting optics into the desired spectral band are examined. The advantages and disadvantages of the Multispectral Linear Array (MLA) multiple optics, the MLA adjacent arrays, the imaging spectrometer, and the MLA beam splitter are discussed. The beam-splitter design approach utilizes, in addition to relatively broad spectral region separation, a movable Multiband Selection Device (MSD), placed between the exit ports of the beam splitter and a linear array detector, permitting many bands to be selected. The successful development and test of the MSD is described. The device demonstrated the capacity to provide a wide field of view, visible-to-near IR/short-wave IR and thermal IR capability, and a multiplicity of spectral bands and polarization measuring means, as well as a reasonable size and weight at minimal cost and risk compared to a spectrometer design approach.
Passenger comfort during terminal-area flight maneuvers. M.S. Thesis.

NASA Technical Reports Server (NTRS)

Schoonover, W. E., Jr.

1976-01-01

A series of flight experiments was conducted to obtain passenger subjective responses to closely controlled and repeatable flight maneuvers. In 8 test flights, reactions were obtained from 30 passenger subjects to a wide range of terminal-area maneuvers, including descents, turns, decelerations, and combinations thereof. Analysis of the passenger rating variance indicated that the objective of a repeatable flight passenger environment was achieved. Multiple linear regression models developed from the test data were used to define maneuver motion boundaries for specified degrees of passenger acceptance.
Random harmonic analysis program, L221 (TEV156). Volume 1: Engineering and usage

NASA Technical Reports Server (NTRS)

Miller, R. D.; Graham, M. L.

1979-01-01

A digital computer program capable of calculating steady state solutions for linear second order differential equations due to sinusoidal forcing functions is described. The field of application of the program, the analysis of airplane response and loads due to continuous random air turbulence, is discussed. Optional capabilities including frequency dependent input matrices, feedback damping, gradual gust penetration, multiple excitation forcing functions, and a static elastic solution are described. Program usage and a description of the analysis used are presented.
MRM assay for quantitation of complement components in human blood plasma - a feasibility study on multiple sclerosis.

PubMed

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

2011-12-10

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

PubMed

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

2003-01-01

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

NASA Astrophysics Data System (ADS)

Imamura, Seigo; Ono, Kenji; Yokokawa, Mitsuo

2016-07-01

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

NASA Astrophysics Data System (ADS)

Kuester, Matthew

2017-11-01

Multiple experiments have shown that surface roughness can enhance the growth of Tollmien-Schlichting (T-S) waves in a laminar boundary layer. One of the common observations from these studies is a ``wall displacement'' effect, where the boundary layer profile shape remains relatively unchanged, but the origin of the profile pushes away from the wall. The objective of this work is to calculate the steady velocity field (including this wall displacement) of a laminar boundary layer over a surface with small, 2D surface ripples. The velocity field is a combination of a Blasius boundary layer and multiple disturbance modes, calculated using the linearized Navier-Stokes equations. The method of multiple scales is used to include non-parallel boundary layer effects of O (Rδ- 1) ; the non-parallel terms are necessary, because a wall displacement is mathematically inconsistent with a parallel boundary layer assumption. This technique is used to calculate the steady velocity field over ripples of varying height and wavelength, including cases where a separation bubble forms on the leeward side of the ripple. In future work, the steady velocity field will be the input for stability calculations, which will quantify the growth of T-S waves over rough surfaces. The author would like to acknowledge the support of the Kevin T. Crofton Aerospace & Ocean Engineering Department at Virginia Tech.
Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

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

2018-04-16

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

PubMed

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.
Geological Mapping of the Ac-H-9 Occator Quadrangle of Ceres from NASA Dawn Mission

NASA Astrophysics Data System (ADS)

Buczkowski, Debra; Williams, David; Scully, Jennifer; Mest, Scott; Crown, David; Aileen Yingst, R.; Schenk, Paul; Jaumann, Ralf; Roatsch, Thomas; Preusker, Frank; Platz, Thomas; Nathues, Andreas; Hoffmann, Martin; Schaefer, Michael; Marchi, Simone; De Sanctis, M. Cristina; Raymond, Carol; Russell, Chris

2016-04-01

As was done at Vesta [1], the Dawn Science Team is conducting a geological mapping cam-paign at Ceres during the nominal mission, including iterative mapping using data obtained dur-ing each orbital phase. We are using geological mapping as a method to identify the geologic processes that have modified the surface of dwarf planet Ceres. We here present the geology of the Ac-H-9 Occator quadrangle, located between 22°S-22°N and 216-288°E. The Ac-H-9 map area is completely within the topographically high region on Ceres named Erntedank Planum. It is one of two longitudinally distinct regions where ESA Herschel space telescope data suggested a release of water vapor [2]. The quadrangle includes several other notable features, including those discussed below. Occator is the 92 km diameter crater that hosts the "Bright Spot 5" that was identified in Hubble Space Telescope data [3], which is actually comprised of multiple bright spots on the crater floor. The floor of Occator is cut by linear fractures, while circumferential fractures are found in the ejecta and on the crater walls. The bright spots are noticeably associated with the floor fractures, although the brightest spot is associated with a central pit [4]. Multiple lobate flows are observed on the crater floor; these appear to be sourced from the center of the crater. The crater has a scalloped rim that is cut by regional linear structures, displaying a cross-section of one structure in the crater wall. Color data show that the Occator ejecta have multiple colors, generally related to changes in morphology. Azacca is a 50 km diameter crater that has a central peak and bright spots on its floor and within its ejecta. Like Occator, Azacca has both floor fractures and circumferential fractures in its ejecta and crater walls. Also like Occator, the Azacca ejecta is multi-colored with variable morphology. Linear structures - including grooves, pit crater chains, fractures and troughs - cross much of the eastern hemisphere of Ceres. Some of these structures appear to be radial to the large basins Urvara and Yalode, and most likely formed due to impact processes. However, a set of regional linear structures (RLS) do not have any obvious relationship to impact craters and may represent internally driven tectonics [5]. In the Ac-H-9 map area, many of the longer RLS are comprised of smaller structures that have linked together, suggestive of en echelon fracturing. Also, many of the RLS are crosscut by the linear features radial to Urvara and Yalode, indicating they are not fractures formed due to stresses released during those impact events. Kirnis is a 115 km diameter crater with a degraded rim deformed by one of RLS pit crater chains. A dome-like feature on the floor of Kirnis might represent uplifting of the Ceres surface. References: [1] Yingst et al. (2014) PSS, 103, 2-23. [2] Küppers, M., et al. (2014) Nature, 505, 525-527. [3] Li J.Y. et al. (2006) Icarus, 182, 143-160. [4]Schenk, P. et al. (2015) EPSC2015-527. [5] Buczkowski D.L. et al. (2015) GSA, abstract #261709.
Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design.

PubMed

Agha, Salah R; Alnahhal, Mohammed J

2012-11-01

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.
A survey of the state of the art and focused research in range systems, task 2

NASA Technical Reports Server (NTRS)

Yao, K.

1986-01-01

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

PubMed

Geukes, Marije; van Aalst, Mariëlle P; Nauta, Mary C E; Oosterhof, Henk

2012-03-01

Menopause is an important life event that may have a negative influence on quality of life. Work ability, a concept widely used in occupational health, can predict both future impairment and duration of sickness absence. The aim of this study was to examine the impact of menopausal symptoms on work ability. This was a cross-sectional study that used a sample of healthy working Dutch women aged 44 to 60 years. Work ability was measured using the Work Ability Index, and menopausal symptoms were measured using the Greene Climacteric Scale. Stepwise multiple linear regression models were used to examine the relationship between menopausal symptoms and work ability. A total of 208 women were included in this study. There was a significant negative correlation between total Greene Climacteric Scale score and Work Ability Index score. Total Greene Climacteric Scale score predicted 33.8% of the total variance in the Work Ability Index score. Only the psychological and somatic subscales of the Greene Climacteric Scale were significant predictors in multiple linear regression analysis. Together, they accounted for 36.5% of total variance in Work Ability Index score. Menopausal symptoms are negatively associated with work ability and may increase the risk of sickness absence.
Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

NASA Technical Reports Server (NTRS)

Kapasouris, Petros

1988-01-01

A systematic control design methodology is introduced for multi-input/multi-output systems with multiple saturations. The methodology can be applied to stable and unstable open loop plants with magnitude and/or rate control saturations and to systems in which state limitations are desired. This new methodology is a substantial improvement over previous heuristic single-input/single-output approaches. The idea is to introduce a supervisor loop so that when the references and/or disturbances are sufficiently small, the control system operates linearly as designed. For signals large enough to cause saturations, the control law is modified in such a way to ensure stability and to preserve, to the extent possible, the behavior of the linear control design. Key benefits of this methodology are: the modified compensator never produces saturating control signals, integrators and/or slow dynamics in the compensator never windup, the directional properties of the controls are maintained, and the closed loop system has certain guaranteed stability properties. The advantages of the new design methodology are illustrated by numerous simulations, including the multivariable longitudinal control of modified models of the F-8 (stable) and F-16 (unstable) aircraft.
Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593
Predicting Reactive Intermediate Quantum Yields from Dissolved Organic Matter Photolysis Using Optical Properties and Antioxidant Capacity.

PubMed

Mckay, Garrett; Huang, Wenxi; Romera-Castillo, Cristina; Crouch, Jenna E; Rosario-Ortiz, Fernando L; Jaffé, Rudolf

2017-05-16

The antioxidant capacity and formation of photochemically produced reactive intermediates (RI) was studied for water samples collected from the Florida Everglades with different spatial (marsh versus estuarine) and temporal (wet versus dry season) characteristics. Measured RI included triplet excited states of dissolved organic matter ( 3 DOM*), singlet oxygen ( 1 O 2 ), and the hydroxyl radical ( • OH). Single and multiple linear regression modeling were performed using a broad range of extrinsic (to predict RI formation rates, R RI ) and intrinsic (to predict RI quantum yields, Φ RI ) parameters. Multiple linear regression models consistently led to better predictions of R RI and Φ RI for our data set but poor prediction of Φ RI for a previously published data set,1 probably because the predictors are intercorrelated (Pearson's r > 0.5). Single linear regression models were built with data compiled from previously published studies (n ≈ 120) in which E2:E3, S, and Φ RI values were measured, which revealed a high degree of similarity between RI-optical property relationships across DOM samples of diverse sources. This study reveals that • OH formation is, in general, decoupled from 3 DOM* and 1 O 2 formation, providing supporting evidence that 3 DOM* is not a • OH precursor. Finally, Φ RI for 1 O 2 and 3 DOM* correlated negatively with antioxidant activity (a surrogate for electron donating capacity) for the collected samples, which is consistent with intramolecular oxidation of DOM moieties by 3 DOM*.
Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

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

2015-08-01

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

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

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

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

PubMed Central

Rothenberg, Stephen J.; Rothenberg, Jesse C.

2005-01-01

Statistical evaluation of the dose–response function in lead epidemiology is rarely attempted. Economic evaluation of health benefits of lead reduction usually assumes a linear dose–response function, regardless of the outcome measure used. We reanalyzed a previously published study, an international pooled data set combining data from seven prospective lead studies examining contemporaneous blood lead effect on IQ (intelligence quotient) of 7-year-old children (n = 1,333). We constructed alternative linear multiple regression models with linear blood lead terms (linear–linear dose response) and natural-log–transformed blood lead terms (log-linear dose response). We tested the two lead specifications for nonlinearity in the models, compared the two lead specifications for significantly better fit to the data, and examined the effects of possible residual confounding on the functional form of the dose–response relationship. We found that a log-linear lead–IQ relationship was a significantly better fit than was a linear–linear relationship for IQ (p = 0.009), with little evidence of residual confounding of included model variables. We substituted the log-linear lead–IQ effect in a previously published health benefits model and found that the economic savings due to U.S. population lead decrease between 1976 and 1999 (from 17.1 μg/dL to 2.0 μg/dL) was 2.2 times ($319 billion) that calculated using a linear–linear dose–response function ($149 billion). The Centers for Disease Control and Prevention action limit of 10 μg/dL for children fails to protect against most damage and economic cost attributable to lead exposure. PMID:16140626
A linear complementarity method for the solution of vertical vehicle-track interaction

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gao, Qiang; Wu, Feng; Zhong, Wan-Xie

2018-02-01

A new method is proposed for the solution of the vertical vehicle-track interaction including a separation between wheel and rail. The vehicle is modelled as a multi-body system using rigid bodies, and the track is treated as a three-layer beam model in which the rail is considered as an Euler-Bernoulli beam and both the sleepers and the ballast are represented by lumped masses. A linear complementarity formulation is directly established using a combination of the wheel-rail normal contact condition and the generalised-α method. This linear complementarity problem is solved using the Lemke algorithm, and the wheel-rail contact force can be obtained. Then the dynamic responses of the vehicle and the track are solved without iteration based on the generalised-α method. The same equations of motion for the vehicle and track are adopted at the different wheel-rail contact situations. This method can remove some restrictions, that is, time-dependent mass, damping and stiffness matrices of the coupled system, multiple equations of motion for the different contact situations and the effect of the contact stiffness. Numerical results demonstrate that the proposed method is effective for simulating the vehicle-track interaction including a separation between wheel and rail.
The challenges of transitioning from linear to high-order overlay control in advanced lithography

NASA Astrophysics Data System (ADS)

Adel, M.; Izikson, P.; Tien, D.; Huang, C. K.; Robinson, J. C.; Eichelberger, B.

2008-03-01

In the lithography section of the ITRS 2006 update, at the top of the list of difficult challenges appears the text "overlay of multiple exposures including mask image placement". This is a reflection of the fact that today overlay is becoming a major yield risk factor in semiconductor manufacturing. Historically, lithographers have achieved sufficient alignment accuracy and hence layer to layer overlay control by relying on models which define overlay as a linear function of the field and wafer coordinates. These linear terms were easily translated to correctibles in the available exposure tool degrees of freedom on the wafer and reticle stages. However, as the 45 nm half pitch node reaches production, exposure tool vendors have begun to make available, and lithographers have begun to utilize so called high order wafer and field control, in which either look up table or high order polynomial models are modified on a product by product basis. In this paper, the major challenges of this transition will be described. It will include characterization of the sources of variation which need to be controlled by these new models and the overlay and alignment sampling optimization problem which needs to be addressed, while maintaining the ever tightening demands on productivity and cost of ownership.
On the linear programming bound for linear Lee codes.

PubMed

Astola, Helena; Tabus, Ioan

2016-01-01

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

PubMed

Ouyang, Z; Gao, L; Fico, M; Chappell, W J; Noll, R J; Cooks, R G

2007-01-01

Quadrupole ion traps are reviewed, emphasizing recent developments, especially the investigation of new geometries, guided by multiple particle simulations such as the ITSIM program. These geometries include linear ion traps (LITs) and the simplified rectilinear ion trap (RIT). Various methods of fabrication are described, including the use of rapid prototyping apparatus (RPA), in which 3D objects are generated through point-by-point laser polymerization. Fabrication in silicon using multilayer semi-conductor fabrication techniques has been used to construct arrays of micro-traps. The performance of instruments containing individual traps as well as arrays of traps of various sizes and geometries is reviewed. Two types of array are differentiated. In the first type, trap arrays constitute fully multiplexed mass spectrometers in which multiple samples are examined using multiple sources, analyzers and detectors, to achieve high throughput analysis. In the second, an array of individual traps acts collectively as a composite trap to increase trapping capacity and performance for a single sample. Much progress has been made in building miniaturized mass spectrometers; a specific example is a 10 kg hand-held tandem mass spectrometer based on the RIT mass analyzer. The performance of this instrument in air and water analysis, using membrane sampling, is described.
SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

PubMed

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models.
The parenting attitudes and the stress of mothers predict the asthmatic severity of their children: a prospective study.

PubMed

Nagano, Jun; Kakuta, Chikage; Motomura, Chikako; Odajima, Hiroshi; Sudo, Nobuyuki; Nishima, Sankei; Kubo, Chiharu

2010-10-07

To examine relationships between a mother's stress-related conditions and parenting attitudes and their children's asthmatic status. 274 mothers of an asthmatic child 2 to 12 years old completed a questionnaire including questions about their chronic stress/coping behaviors (the "Stress Inventory"), parenting attitudes (the "Ta-ken Diagnostic Test for Parent-Child Relationship, Parent Form"), and their children's disease status. One year later, a follow-up questionnaire was mailed to the mothers that included questions on the child's disease status. 223 mothers (81%) responded to the follow-up survey. After controlling for non-psychosocial factors including disease severity at baseline, multiple linear regression analysis followed by multiple logistic regression analysis found chronic irritation/anger and emotional suppression to be aggravating factors for children aged < 7 years; for children aged 7 and over, the mothers' egocentric behavior was a mitigating factor while interference was an aggravating factor. Different types of parental stress/coping behaviors and parenting styles may differently predict their children's asthmatic status, and such associations may change as children grow.
Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

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

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…
Correlations of neutron multiplicity and γ -ray multiplicity with fragment mass and total kinetic energy in spontaneous fission of Cf 252

DOE PAGES

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

2016-01-08

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

PubMed

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

2013-01-01

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

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.
Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885
Particle Beam Radiography

NASA Astrophysics Data System (ADS)

Peach, Ken; Ekdahl, Carl

2014-02-01

Particle beam radiography, which uses a variety of particle probes (neutrons, protons, electrons, gammas and potentially other particles) to study the structure of materials and objects noninvasively, is reviewed, largely from an accelerator perspective, although the use of cosmic rays (mainly muons but potentially also high-energy neutrinos) is briefly reviewed. Tomography is a form of radiography which uses multiple views to reconstruct a three-dimensional density map of an object. There is a very wide range of applications of radiography and tomography, from medicine to engineering and security, and advances in instrumentation, specifically the development of electronic detectors, allow rapid analysis of the resultant radiographs. Flash radiography is a diagnostic technique for large high-explosive-driven hydrodynamic experiments that is used at many laboratories. The bremsstrahlung radiation pulse from an intense relativistic electron beam incident onto a high-Z target is the source of these radiographs. The challenge is to provide radiation sources intense enough to penetrate hundreds of g/cm2 of material, in pulses short enough to stop the motion of high-speed hydrodynamic shocks, and with source spots small enough to resolve fine details. The challenge has been met with a wide variety of accelerator technologies, including pulsed-power-driven diodes, air-core pulsed betatrons and high-current linear induction accelerators. Accelerator technology has also evolved to accommodate the experimenters' continuing quest for multiple images in time and space. Linear induction accelerators have had a major role in these advances, especially in providing multiple-time radiographs of the largest hydrodynamic experiments.
Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.
Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

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

2017-03-01

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

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.
Fiber Bragg grating sensor interrogators on chip: challenges and opportunities

NASA Astrophysics Data System (ADS)

Marin, Yisbel; Nannipieri, Tiziano; Oton, Claudio J.; Di Pasquale, Fabrizio

2017-04-01

In this paper we present an overview of the current efforts towards integration of Fiber Bragg Grating (FBG) sensor interrogators. Different photonic integration platforms will be discussed, including monolithic planar lightwave circuit technology, silicon on insulator (SOI), indium phosphide (InP) and gallium arsenide (GaAs) material platforms. Also various possible techniques for wavelength metering and methods for FBG multiplexing will be discussed and compared in terms of resolution, dynamic performance, multiplexing capabilities and reliability. The use of linear filters, array waveguide gratings (AWG) as multiple linear filters and AWG based centroid signal processing techniques will be addressed as well as interrogation techniques based on tunable micro-ring resonators and Mach-Zehnder interferometers (MZI) for phase sensitive detection. The paper will also discuss the challenges and perspectives of photonic integration to address the increasing requirements of several industrial applications.
Fetal growth in different racial groups.

PubMed Central

Alvear, J; Brooke, O G

1978-01-01

Three racial groups of mothers and their newborn babies-- North European 75, Negro 75, and "Indian" Asian 37--were matched for parity, gestational age, sex, maternal age, maternal smoking habits, and social class. Multiple anthropometric measurements, including skinfold thickness, limb circumferences, and various linear measurements were made on the mothers and their infants to determine the effects of race and smoking on fetal size. Indian-Asian mothers, though shorter and lighter than Europeans and Negroes, had similar skinfold thickness and weight: height2 ratios and gained as much weight during pregnancy. Their infants, however, were lighter than the others, and had smaller head and limb circumferences, although their linear measurements were the same. Negro and European infants were almost identical in size. We found no effect on any of the fetal measurements which could be attributed to smoking. PMID:626515
Unambiguous discrimination between linearly dependent equidistant states with multiple copies

NASA Astrophysics Data System (ADS)

Zhang, Wen-Hai; Ren, Gang

2018-07-01

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

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

PubMed

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

2009-06-01

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

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

Smallwood, David O.

2007-01-01

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

NASA Technical Reports Server (NTRS)

Trumper, David L.; Queen, Michael A.

1992-01-01

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

DOEpatents

Chojnacki, E.P.

1994-05-31

A mode trap to trap and absorb transverse modes formed by a beam in a linear accelerator includes a waveguide having a multiplicity of electrically conductive (preferably copper) irises and rings, each iris and ring including an aperture, and the irises and rings being stacked in a side-by-side, alternating fashion such that the apertures of the irises and rings are concentrically aligned. An absorbing material layer such as a dielectric is embedded in each iris and ring, and this absorbing material layer encircles, but is circumferentially spaced from its respective aperture. Each iris and ring includes a plurality of circumferentially spaced slots around its aperture and extending radially out toward its absorbing material layer. 9 figs.
Dilations and the Equation of a Line

ERIC Educational Resources Information Center

Yopp, David A.

2016-01-01

Students engage in proportional reasoning when they use covariance and multiple comparisons. Without rich connections to proportional reasoning, students may develop inadequate understandings of linear relationships and the equations that model them. Teachers can improve students' understanding of linear relationships by focusing on realistic…
Self-interaction of NPM1 modulates multiple mechanisms of liquid–liquid phase separation

DOE PAGES

Mitrea, Diana M.; Cika, Jaclyn A.; Stanley, Christopher B.; ...

2018-02-26

Nucleophosmin (NPM1) is an abundant, oligomeric protein in the granular component of the nucleolus with roles in ribosome biogenesis. Pentameric NPM1 undergoes liquid–liquid phase separation (LLPS) via heterotypic interactions with nucleolar components, including ribosomal RNA (rRNA) and proteins which display multivalent arginine-rich linear motifs (R-motifs), and is integral to the liquid-like nucleolar matrix. Here we show that NPM1 can also undergo LLPS via homotypic interactions between its polyampholytic intrinsically disordered regions, a mechanism that opposes LLPS via heterotypic interactions. Using a combination of biophysical techniques, including confocal microscopy, SAXS, analytical ultracentrifugation, and single-molecule fluorescence, we describe how conformational changes withinmore » NPM1 control valency and switching between the different LLPS mechanisms. We propose that this newly discovered interplay between multiple LLPS mechanisms may influence the direction of vectorial pre-ribosomal particle assembly within, and exit from the nucleolus as part of the ribosome biogenesis process.« less
Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Péran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2015-01-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.
Adaptive management for soil ecosystem services

USGS Publications Warehouse

Birge, Hannah E.; Bevans, Rebecca A.; Allen, Craig R.; Angeler, David G.; Baer, Sara G.; Wall, Diana H.

2016-01-01

Ecosystem services provided by soil include regulation of the atmosphere and climate, primary (including agricultural) production, waste processing, decomposition, nutrient conservation, water purification, erosion control, medical resources, pest control, and disease mitigation. The simultaneous production of these multiple services arises from complex interactions among diverse aboveground and belowground communities across multiple scales. When a system is mismanaged, non-linear and persistent losses in ecosystem services can arise. Adaptive management is an approach to management designed to reduce uncertainty as management proceeds. By developing alternative hypotheses, testing these hypotheses and adjusting management in response to outcomes, managers can probe dynamic mechanistic relationships among aboveground and belowground soil system components. In doing so, soil ecosystem services can be preserved and critical ecological thresholds avoided. Here, we present an adaptive management framework designed to reduce uncertainty surrounding the soil system, even when soil ecosystem services production is not the explicit management objective, so that managers can reach their management goals without undermining soil multifunctionality or contributing to an irreversible loss of soil ecosystem services.
Self-interaction of NPM1 modulates multiple mechanisms of liquid–liquid phase separation

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

Mitrea, Diana M.; Cika, Jaclyn A.; Stanley, Christopher B.

Nucleophosmin (NPM1) is an abundant, oligomeric protein in the granular component of the nucleolus with roles in ribosome biogenesis. Pentameric NPM1 undergoes liquid–liquid phase separation (LLPS) via heterotypic interactions with nucleolar components, including ribosomal RNA (rRNA) and proteins which display multivalent arginine-rich linear motifs (R-motifs), and is integral to the liquid-like nucleolar matrix. Here we show that NPM1 can also undergo LLPS via homotypic interactions between its polyampholytic intrinsically disordered regions, a mechanism that opposes LLPS via heterotypic interactions. Using a combination of biophysical techniques, including confocal microscopy, SAXS, analytical ultracentrifugation, and single-molecule fluorescence, we describe how conformational changes withinmore » NPM1 control valency and switching between the different LLPS mechanisms. We propose that this newly discovered interplay between multiple LLPS mechanisms may influence the direction of vectorial pre-ribosomal particle assembly within, and exit from the nucleolus as part of the ribosome biogenesis process.« less
Refill Adherence in Relation to Substitution and the Use of Multiple Medications: A Nationwide Population Based Study on New ACE-Inhibitor Users

PubMed Central

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

2016-01-01

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

PubMed

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

2008-05-15

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

PubMed Central

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

2013-01-01

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 for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. PMID:23376789
Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

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

PubMed

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 for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. Published by Elsevier Inc.
Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.
Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

PubMed

Ding, Chuan; Chen, Peng; Jiao, Junfeng

2018-03-01

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

DOEpatents

Rosenberg, Louis B.

2001-01-01

A method and apparatus for providing high bandwidth and low noise mechanical input and output for computer systems. A gimbal mechanism provides two revolute degrees of freedom to an object about two axes of rotation. A linear axis member is coupled to the gimbal mechanism at the intersection of the two axes of rotation. The linear axis member is capable of being translated along a third axis to provide a third degree of freedom. The user object is coupled to the linear axis member and is thus translatable along the third axis so that the object can be moved along all three degrees of freedom. Transducers associated with the provided degrees of freedom include sensors and actuators and provide an electromechanical interface between the object and a digital processing system. Capstan drive mechanisms transmit forces between the transducers and the object. The linear axis member can also be rotated about its lengthwise axis to provide a fourth degree of freedom, and, optionally, a floating gimbal mechanism is coupled to the linear axis member to provide fifth and sixth degrees of freedom to an object. Transducer sensors are associated with the fourth, fifth, and sixth degrees of freedom. The interface is well suited for simulations of medical procedures and simulations in which an object such as a stylus or a joystick is moved and manipulated by the user.
Characteristics of compound multiplicity in 84Kr36 with various light and heavy targets at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

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

2013-12-01

Interactions of 84Kr36 having kinetic energy around 1 GeV per nucleon with NIKFI BR-2 nuclear emulsion detector's target reveal some of the important features of compound multiplicity. Present article shows that width of compound multiplicity distributions and value of mean compound multiplicity have linear relationship with mass number of the projectile colliding system.
The optimal hormonal replacement modality selection for multiple organ procurement from brain-dead organ donors

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-04-24

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

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

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

PubMed Central

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

2011-01-01

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

ERIC Educational Resources Information Center

Larson, Christine

2010-01-01

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

PubMed

Zhu, Xiaoyan; Yao, Qingzhu

2011-12-01

It is technologically possible for a biorefinery to use a variety of biomass as feedstock including native perennial grasses (e.g., switchgrass) and agricultural residues (e.g., corn stalk and wheat straw). Incorporating the distinct characteristics of various types of biomass feedstocks and taking into account their interaction in supplying the bioenergy production, this paper proposed a multi-commodity network flow model to design the logistics system for a multiple-feedstock biomass-to-bioenergy industry. The model was formulated as a mixed integer linear programming, determining the locations of warehouses, the size of harvesting team, the types and amounts of biomass harvested/purchased, stored, and processed in each month, the transportation of biomass in the system, and so on. This paper demonstrated the advantages of using multiple types of biomass feedstocks by comparing with the case of using a single feedstock (switchgrass) and analyzed the relationship of the supply capacity of biomass feedstocks to the output and cost of biofuel. Copyright © 2011 Elsevier Ltd. All rights reserved.
Stochastic nature of Landsat MSS data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.

1987-01-01

A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.
Miniaturized Planar Room Temperature Ionic Liquid Electrochemical Gas Sensor for Rapid Multiple Gas Pollutants Monitoring.

PubMed

Wan, Hao; Yin, Heyu; Lin, Lu; Zeng, Xiangqun; Mason, Andrew J

2018-02-01

The growing impact of airborne pollutants and explosive gases on human health and occupational safety has escalated the demand of sensors to monitor hazardous gases. This paper presents a new miniaturized planar electrochemical gas sensor for rapid measurement of multiple gaseous hazards. The gas sensor features a porous polytetrafluoroethylene substrate that enables fast gas diffusion and room temperature ionic liquid as the electrolyte. Metal sputtering was utilized for platinum electrodes fabrication to enhance adhesion between the electrodes and the substrate. Together with carefully selected electrochemical methods, the miniaturized gas sensor is capable of measuring multiple gases including oxygen, methane, ozone and sulfur dioxide that are important to human health and safety. Compared to its manually-assembled Clark-cell predecessor, this sensor provides better sensitivity, linearity and repeatability, as validated for oxygen monitoring. With solid performance, fast response and miniaturized size, this sensor is promising for deployment in wearable devices for real-time point-of-exposure gas pollutant monitoring.
The enigmatic nature of the circumstellar envelope and bow shock surrounding Betelgeuse as revealed by Herschel. I. Evidence of clumps, multiple arcs, and a linear bar-like structure

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

PubMed

Chen, Chen; Xie, Yuanchang

2016-06-01

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

PubMed

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Development of multiple source data processing for structural analysis at a regional scale. [digital remote sensing in geology

NASA Technical Reports Server (NTRS)

Carrere, Veronique

1990-01-01

Various image processing techniques developed for enhancement and extraction of linear features, of interest to the structural geologist, from digital remote sensing, geologic, and gravity data, are presented. These techniques include: (1) automatic detection of linear features and construction of rose diagrams from Landsat MSS data; (2) enhancement of principal structural directions using selective filters on Landsat MSS, Spacelab panchromatic, and HCMM NIR data; (3) directional filtering of Spacelab panchromatic data using Fast Fourier Transform; (4) detection of linear/elongated zones of high thermal gradient from thermal infrared data; and (5) extraction of strong gravimetric gradients from digitized Bouguer anomaly maps. Processing results can be compared to each other through the use of a geocoded database to evaluate the structural importance of each lineament according to its depth: superficial structures in the sedimentary cover, or deeper ones affecting the basement. These image processing techniques were successfully applied to achieve a better understanding of the transition between Provence and the Pyrenees structural blocks, in southeastern France, for an improved structural interpretation of the Mediterranean region.
SLiMSearch 2.0: biological context for short linear motifs in proteins

PubMed Central

Davey, Norman E.; Haslam, Niall J.; Shields, Denis C.

2011-01-01

Short, linear motifs (SLiMs) play a critical role in many biological processes. The SLiMSearch 2.0 (Short, Linear Motif Search) web server allows researchers to identify occurrences of a user-defined SLiM in a proteome, using conservation and protein disorder context statistics to rank occurrences. User-friendly output and visualizations of motif context allow the user to quickly gain insight into the validity of a putatively functional motif occurrence. For each motif occurrence, overlapping UniProt features and annotated SLiMs are displayed. Visualization also includes annotated multiple sequence alignments surrounding each occurrence, showing conservation and protein disorder statistics in addition to known and predicted SLiMs, protein domains and known post-translational modifications. In addition, enrichment of Gene Ontology terms and protein interaction partners are provided as indicators of possible motif function. All web server results are available for download. Users can search motifs against the human proteome or a subset thereof defined by Uniprot accession numbers or GO term. The SLiMSearch server is available at: http://bioware.ucd.ie/slimsearch2.html. PMID:21622654
An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

ERIC Educational Resources Information Center

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

2011-01-01

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

NASA Astrophysics Data System (ADS)

Seagraves, P. H.; Elmore, David F.

1994-09-01

Systems using optical elements such as linear polarizers, retarders, and mirrors can be represented by Mueller matrices. Some polarimeters include elements with time-varying polarization properties, multiple light beams, light detectors, and signal processing equipment. Standard Mueller matrix forms describing time-varying retarders, and beam splitters are presented, as well as non-Mueller matrices which describe detection and signal processing. These matrices provide a compact and intuitive mathematical description of polarimeter response which can aid in the refining of instrument designs.
Frequency division multiplex technique

NASA Technical Reports Server (NTRS)

Brey, H. (Inventor)

1973-01-01

A system for monitoring a plurality of condition responsive devices is described. It consists of a master control station and a remote station. The master control station is capable of transmitting command signals which includes a parity signal to a remote station which transmits the signals back to the command station so that such can be compared with the original signals in order to determine if there are any transmission errors. The system utilizes frequency sources which are 1.21 multiples of each other so that no linear combination of any harmonics will interfere with another frequency.
[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.
Stroop Color-Word Interference Test: Normative data for Spanish-speaking pediatric population.

PubMed

Rivera, D; Morlett-Paredes, A; Peñalver Guia, A I; Irías Escher, M J; Soto-Añari, M; Aguayo Arelis, A; Rute-Pérez, S; Rodríguez-Lorenzana, A; Rodríguez-Agudelo, Y; Albaladejo-Blázquez, N; García de la Cadena, C; Ibáñez-Alfonso, J A; Rodriguez-Irizarry, W; García-Guerrero, C E; Delgado-Mejía, I D; Padilla-López, A; Vergara-Moragues, E; Barrios Nevado, M D; Saracostti Schwartzman, M; Arango-Lasprilla, J C

2017-01-01

To generate normative data for the Stroop Word-Color Interference test in Spanish-speaking pediatric populations. The sample consisted of 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Each participant was administered the Stroop Word-Color Interference test as part of a larger neuropsychological battery. The Stroop Word, Stroop Color, Stroop Word-Color, and Stroop Interference scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the analyses. The final multiple linear regression models showed main effects for age on all scores, except on Stroop Interference for Guatemala, such that scores increased linearly as a function of age. Age2 affected Stroop Word scores for all countries, Stroop Color scores for Ecuador, Mexico, Peru, and Spain; Stroop Word-Color scores for Ecuador, Mexico, and Paraguay; and Stroop Interference scores for Cuba, Guatemala, and Spain. MLPE affected Stroop Word scores for Chile, Mexico, and Puerto Rico; Stroop Color scores for Mexico, Puerto Rico, and Spain; Stroop Word-Color scores for Ecuador, Guatemala, Mexico, Puerto Rico and Spain; and Stroop-Interference scores for Ecuador, Mexico, and Spain. Sex affected Stroop Word scores for Spain, Stroop Color scores for Mexico, and Stroop Interference for Honduras. This is the largest Spanish-speaking pediatric normative study in the world, and it will allow neuropsychologists from these countries to have a more accurate approach to interpret the Stroop Word-Color Interference test in pediatric populations.
Adaptive multiregression in reproducing kernel Hilbert spaces: the multiaccess MIMO channel case.

PubMed

Slavakis, Konstantinos; Bouboulis, Pantelis; Theodoridis, Sergios

2012-02-01

This paper introduces a wide framework for online, i.e., time-adaptive, supervised multiregression tasks. The problem is formulated in a general infinite-dimensional reproducing kernel Hilbert space (RKHS). In this context, a fairly large number of nonlinear multiregression models fall as special cases, including the linear case. Any convex, continuous, and not necessarily differentiable function can be used as a loss function in order to quantify the disagreement between the output of the system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. To this end, we demonstrate a way to calculate the subgradients of robust loss functions, suitable for the multiregression task. As it is by now well documented, when dealing with online schemes in RKHS, the memory keeps increasing with each iteration step. To attack this problem, a simple sparsification strategy is utilized, which leads to an algorithmic scheme of linear complexity with respect to the number of unknown parameters. A convergence analysis of the technique, based on arguments of convex analysis, is also provided. To demonstrate the capacity of the proposed method, the multiregressor is applied to the multiaccess multiple-input multiple-output channel equalization task for a setting with poor resources and nonavailable channel information. Numerical results verify the potential of the method, when its performance is compared with those of the state-of-the-art linear techniques, which, in contrast, use space-time coding, more antenna elements, as well as full channel information.
Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.
FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

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

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

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

NASA Astrophysics Data System (ADS)

Watkins, Edward Francis

1995-01-01

A novel approach to the search for optimal designs of source-driven nuclear systems is investigated. Such systems include radiation shields, fusion reactor blankets and various neutron spectrum-shaping assemblies. The novel approach involves the replacement of the steepest-descents optimization algorithm incorporated in the code SWAN by a significantly more general and efficient sequential quadratic programming optimization algorithm provided by the code NPSOL. The resulting SWAN/NPSOL code system can be applied to more general, multi-variable, multi-constraint shield optimization problems. The constraints it accounts for may include simple bounds on variables, linear constraints, and smooth nonlinear constraints. It may also be applied to unconstrained, bound-constrained and linearly constrained optimization. The shield optimization capabilities of the SWAN/NPSOL code system is tested and verified in a variety of optimization problems: dose minimization at constant cost, cost minimization at constant dose, and multiple-nonlinear constraint optimization. The replacement of the optimization part of SWAN with NPSOL is found feasible and leads to a very substantial improvement in the complexity of optimization problems which can be efficiently handled.
MABE multibeam accelerator

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

Hasti, D.E.; Ramirez, J.J.; Coleman, P.D.

1985-01-01

The Megamp Accelerator and Beam Experiment (MABE) was the technology development testbed for the multiple beam, linear induction accelerator approach for Hermes III, a new 20 MeV, 0.8 MA, 40 ns accelerator being developed at Sandia for gamma-ray simulation. Experimental studies of a high-current, single-beam accelerator (8 MeV, 80 kA), and a nine-beam injector (1.4 MeV, 25 kA/beam) have been completed, and experiments on a nine-beam linear induction accelerator are in progress. A two-beam linear induction accelerator is designed and will be built as a gamma-ray simulator to be used in parallel with Hermes III. The MABE pulsed power systemmore » and accelerator for the multiple beam experiments is described. Results from these experiments and the two-beam design are discussed. 11 refs., 6 figs.« less
A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.
[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

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

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

NASA Astrophysics Data System (ADS)

Lovejoy, McKenna R.; Wickert, Mark A.

2017-05-01

A known problem with infrared imaging devices is their non-uniformity. This non-uniformity is the result of dark current, amplifier mismatch as well as the individual photo response of the detectors. To improve performance, non-uniformity correction (NUC) techniques are applied. Standard calibration techniques use linear, or piecewise linear models to approximate the non-uniform gain and off set characteristics as well as the nonlinear response. Piecewise linear models perform better than the one and two-point models, but in many cases require storing an unmanageable number of correction coefficients. Most nonlinear NUC algorithms use a second order polynomial to improve performance and allow for a minimal number of stored coefficients. However, advances in technology now make higher order polynomial NUC algorithms feasible. This study comprehensively tests higher order polynomial NUC algorithms targeted at short wave infrared (SWIR) imagers. Using data collected from actual SWIR cameras, the nonlinear techniques and corresponding performance metrics are compared with current linear methods including the standard one and two-point algorithms. Machine learning, including principal component analysis, is explored for identifying and replacing bad pixels. The data sets are analyzed and the impact of hardware implementation is discussed. Average floating point results show 30% less non-uniformity, in post-corrected data, when using a third order polynomial correction algorithm rather than a second order algorithm. To maximize overall performance, a trade off analysis on polynomial order and coefficient precision is performed. Comprehensive testing, across multiple data sets, provides next generation model validation and performance benchmarks for higher order polynomial NUC methods.
Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

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

2018-01-01

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

PubMed

Wong, Liang Jie; Hong, Kyung-Han; Carbajo, Sergio; Fallahi, Arya; Piot, Philippe; Soljačić, Marin; Joannopoulos, John D; Kärtner, Franz X; Kaminer, Ido

2017-09-11

Linear-field particle acceleration in free space (which is distinct from geometries like the linac that requires components in the vicinity of the particle) has been studied for over 20 years, and its ability to eventually produce high-quality, high energy multi-particle bunches has remained a subject of great interest. Arguments can certainly be made that linear-field particle acceleration in free space is very doubtful given that first-order electron-photon interactions are forbidden in free space. Nevertheless, we chose to develop an accurate and truly predictive theoretical formalism to explore this remote possibility when intense, few-cycle electromagnetic pulses are used in a computational experiment. The formalism includes exact treatment of Maxwell's equations and exact treatment of the interaction among the multiple individual particles at near and far field. Several surprising results emerge. We find that electrons interacting with intense laser pulses in free space are capable of gaining substantial amounts of energy that scale linearly with the field amplitude. For example, 30 keV electrons (2.5% energy spread) are accelerated to 61 MeV (0.5% spread) and to 205 MeV (0.25% spread) using 250 mJ and 2.5 J lasers respectively. These findings carry important implications for our understanding of ultrafast electron-photon interactions in strong fields.
Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.
Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models

USGS Publications Warehouse

Linard, Joshua I.

2013-01-01

Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.
Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).
Effect of processor temperature on film dosimetry

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

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

2012-07-01

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

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

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

NASA Astrophysics Data System (ADS)

Laborda, Francisco; Medrano, Jesús; Castillo, Juan R.

2004-06-01

The quality of the quantitative results obtained from transient signals in high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS) and flow injection-inductively coupled plasma mass spectrometry (FI-ICPMS) was investigated under multielement conditions. Quantification methods were based on multiple-point calibration by simple and weighted linear regression, and double-point calibration (measurement of the baseline and one standard). An uncertainty model, which includes the main sources of uncertainty from FI-ICPMS and HPLC-ICPMS (signal measurement, sample flow rate and injection volume), was developed to estimate peak area uncertainties and statistical weights used in weighted linear regression. The behaviour of the ICPMS instrument was characterized in order to be considered in the model, concluding that the instrument works as a concentration detector when it is used to monitorize transient signals from flow injection or chromatographic separations. Proper quantification by the three calibration methods was achieved when compared to reference materials, although the double-point calibration allowed to obtain results of the same quality as the multiple-point calibration, shortening the calibration time. Relative expanded uncertainties ranged from 10-20% for concentrations around the LOQ to 5% for concentrations higher than 100 times the LOQ.
Predicting the photoinduced electron transfer thermodynamics in polyfluorinated 1,3,5-triarylpyrazolines based on multiple linear free energy relationships†

PubMed Central

Verma, Manjusha; Chaudhry, Aneese F.; Fahrni, Christoph J.

2010-01-01

The photophysical properties of 1,3,5-triarylpyrazolines are strongly influenced by the nature and position of substituents attached to the aryl-rings, rendering this fluorophore platform well suited for the design of fluorescent probes utilizing a photoinduced electron transfer (PET) switching mechanism. To explore the tunability of two key parameters that govern the PET thermodynamics, the excited state energy ΔE00 and acceptor potential E(A/A−), a library of polyfluoro-substituted 1,3-diaryl-5-phenyl-pyrazolines was synthesized and characterized. The observed trends for the PET parameters were effectively captured through multiple Hammett linear free energy relationships (LFER) using a set of independent substituent constants for each of the two aryl rings. Given the lack of experimental Hammett constants for polyfluoro substituted aromatics, theoretically derived constants based on the electrostatic potential at the nucleus (EPN) of carbon atoms were employed as quantum chemical descriptors. The performance of the LFER was evaluated with a set of compounds that were not included in the training set, yielding a mean unsigned error of 0.05 eV for the prediction of the combined PET parameters. The outlined LFER approach should be well suited to design and optimize the performance of cation-responsive 1,3,5-triarylpyrazolines. PMID:19343239
Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

PubMed Central

Liu, Yufeng; Wu, Yichao

2011-01-01

Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842
Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…
MAGDM linear-programming models with distinct uncertain preference structures.

PubMed

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.

Communication: modeling charge-sign asymmetric solvation free energies with nonlinear boundary conditions.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G

2014-10-07

We show that charge-sign-dependent asymmetric hydration can be modeled accurately using linear Poisson theory after replacing the standard electric-displacement boundary condition with a simple nonlinear boundary condition. Using a single multiplicative scaling factor to determine atomic radii from molecular dynamics Lennard-Jones parameters, the new model accurately reproduces MD free-energy calculations of hydration asymmetries for: (i) monatomic ions, (ii) titratable amino acids in both their protonated and unprotonated states, and (iii) the Mobley "bracelet" and "rod" test problems [D. L. Mobley, A. E. Barber II, C. J. Fennell, and K. A. Dill, "Charge asymmetries in hydration of polar solutes," J. Phys. Chem. B 112, 2405-2414 (2008)]. Remarkably, the model also justifies the use of linear response expressions for charging free energies. Our boundary-element method implementation demonstrates the ease with which other continuum-electrostatic solvers can be extended to include asymmetry.
Incremental harmonic balance method for predicting amplitudes of a multi-d.o.f. non-linear wheel shimmy system with combined Coulomb and quadratic damping

NASA Astrophysics Data System (ADS)

Zhou, J. X.; Zhang, L.

2005-01-01

Incremental harmonic balance (IHB) formulations are derived for general multiple degrees of freedom (d.o.f.) non-linear autonomous systems. These formulations are developed for a concerned four-d.o.f. aircraft wheel shimmy system with combined Coulomb and velocity-squared damping. A multi-harmonic analysis is performed and amplitudes of limit cycles are predicted. Within a large range of parametric variations with respect to aircraft taxi velocity, the IHB method can, at a much cheaper cost, give results with high accuracy as compared with numerical results given by a parametric continuation method. In particular, the IHB method avoids the stiff problems emanating from numerical treatment of aircraft wheel shimmy system equations. The development is applicable to other vibration control systems that include commonly used dry friction devices or velocity-squared hydraulic dampers.
A newly recognized syndrome of severe growth deficiency, microcephaly, intellectual disability, and characteristic facial features.

PubMed

Vinkler, Chana; Leshinsky-Silver, Esther; Michelson, Marina; Haas, Dorothea; Lerman-Sagie, Tally; Lev, Dorit

2014-01-01

Genetic syndromes with proportionate severe short stature are rare. We describe two sisters born to nonconsanguineous parents with severe linear growth retardation, poor weight gain, microcephaly, characteristic facial features, cutaneous syndactyly of the toes, high myopia, and severe intellectual disability. During infancy and early childhood, the girls had transient hepatosplenomegaly and low blood cholesterol levels that normalized later. A thorough evaluation including metabolic studies, radiological, and genetic investigations were all normal. Cholesterol metabolism and transport were studied and no definitive abnormality was found. No clinical deterioration was observed and no metabolic crises were reported. After due consideration of other known hereditary causes of post-natal severe linear growth retardation, microcephaly, and intellectual disability, we propose that this condition represents a newly recognized autosomal recessive multiple congenital anomaly-intellectual disability syndrome. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Programmable multimode quantum networks

PubMed Central

Armstrong, Seiji; Morizur, Jean-François; Janousek, Jiri; Hage, Boris; Treps, Nicolas; Lam, Ping Koy; Bachor, Hans-A.

2012-01-01

Entanglement between large numbers of quantum modes is the quintessential resource for future technologies such as the quantum internet. Conventionally, the generation of multimode entanglement in optics requires complex layouts of beamsplitters and phase shifters in order to transform the input modes into entangled modes. Here we report the highly versatile and efficient generation of various multimode entangled states with the ability to switch between different linear optics networks in real time. By defining our modes to be combinations of different spatial regions of one beam, we may use just one pair of multi-pixel detectors in order to measure multiple entangled modes. We programme virtual networks that are fully equivalent to the physical linear optics networks they are emulating. We present results for N=2 up to N=8 entangled modes here, including N=2, 3, 4 cluster states. Our approach introduces the highly sought after attributes of flexibility and scalability to multimode entanglement. PMID:22929783
Communication: Modeling charge-sign asymmetric solvation free energies with nonlinear boundary conditions

PubMed Central

Bardhan, Jaydeep P.; Knepley, Matthew G.

2014-01-01

We show that charge-sign-dependent asymmetric hydration can be modeled accurately using linear Poisson theory after replacing the standard electric-displacement boundary condition with a simple nonlinear boundary condition. Using a single multiplicative scaling factor to determine atomic radii from molecular dynamics Lennard-Jones parameters, the new model accurately reproduces MD free-energy calculations of hydration asymmetries for: (i) monatomic ions, (ii) titratable amino acids in both their protonated and unprotonated states, and (iii) the Mobley “bracelet” and “rod” test problems [D. L. Mobley, A. E. Barber II, C. J. Fennell, and K. A. Dill, “Charge asymmetries in hydration of polar solutes,” J. Phys. Chem. B 112, 2405–2414 (2008)]. Remarkably, the model also justifies the use of linear response expressions for charging free energies. Our boundary-element method implementation demonstrates the ease with which other continuum-electrostatic solvers can be extended to include asymmetry. PMID:25296776
Parallel Implicit Runge-Kutta Methods Applied to Coupled Orbit/Attitude Propagation

NASA Astrophysics Data System (ADS)

Hatten, Noble; Russell, Ryan P.

2017-12-01

A variable-step Gauss-Legendre implicit Runge-Kutta (GLIRK) propagator is applied to coupled orbit/attitude propagation. Concepts previously shown to improve efficiency in 3DOF propagation are modified and extended to the 6DOF problem, including the use of variable-fidelity dynamics models. The impact of computing the stage dynamics of a single step in parallel is examined using up to 23 threads and 22 associated GLIRK stages; one thread is reserved for an extra dynamics function evaluation used in the estimation of the local truncation error. Efficiency is found to peak for typical examples when using approximately 8 to 12 stages for both serial and parallel implementations. Accuracy and efficiency compare favorably to explicit Runge-Kutta and linear-multistep solvers for representative scenarios. However, linear-multistep methods are found to be more efficient for some applications, particularly in a serial computing environment, or when parallelism can be applied across multiple trajectories.
Parallel and Preemptable Dynamically Dimensioned Search Algorithms for Single and Multi-objective Optimization in Water Resources

NASA Astrophysics Data System (ADS)

Tolson, B.; Matott, L. S.; Gaffoor, T. A.; Asadzadeh, M.; Shafii, M.; Pomorski, P.; Xu, X.; Jahanpour, M.; Razavi, S.; Haghnegahdar, A.; Craig, J. R.

2015-12-01

We introduce asynchronous parallel implementations of the Dynamically Dimensioned Search (DDS) family of algorithms including DDS, discrete DDS, PA-DDS and DDS-AU. These parallel algorithms are unique from most existing parallel optimization algorithms in the water resources field in that parallel DDS is asynchronous and does not require an entire population (set of candidate solutions) to be evaluated before generating and then sending a new candidate solution for evaluation. One key advance in this study is developing the first parallel PA-DDS multi-objective optimization algorithm. The other key advance is enhancing the computational efficiency of solving optimization problems (such as model calibration) by combining a parallel optimization algorithm with the deterministic model pre-emption concept. These two efficiency techniques can only be combined because of the asynchronous nature of parallel DDS. Model pre-emption functions to terminate simulation model runs early, prior to completely simulating the model calibration period for example, when intermediate results indicate the candidate solution is so poor that it will definitely have no influence on the generation of further candidate solutions. The computational savings of deterministic model preemption available in serial implementations of population-based algorithms (e.g., PSO) disappear in synchronous parallel implementations as these algorithms. In addition to the key advances above, we implement the algorithms across a range of computation platforms (Windows and Unix-based operating systems from multi-core desktops to a supercomputer system) and package these for future modellers within a model-independent calibration software package called Ostrich as well as MATLAB versions. Results across multiple platforms and multiple case studies (from 4 to 64 processors) demonstrate the vast improvement over serial DDS-based algorithms and highlight the important role model pre-emption plays in the performance of parallel, pre-emptable DDS algorithms. Case studies include single- and multiple-objective optimization problems in water resources model calibration and in many cases linear or near linear speedups are observed.
On Performance of Linear Multiuser Detectors for Wireless Multimedia Applications

NASA Astrophysics Data System (ADS)

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

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

DTIC Science & Technology

2007-03-01

mathematical frame- 1-6 work of linear algebra and functional analysis [122, 33], while Kalman-Bucy filtering [96, 32] is an especially important...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, March 2002. 85. Hoffman, Kenneth and Ray Kunze. Linear Algebra (Second Edition...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, December 1989. 189. Strang, Gilbert. Linear Algebra and Its Applications
Robust set-point regulation for ecological models with multiple management goals.

PubMed

Guiver, Chris; Mueller, Markus; Hodgson, Dave; Townley, Stuart

2016-05-01

Population managers will often have to deal with problems of meeting multiple goals, for example, keeping at specific levels both the total population and population abundances in given stage-classes of a stratified population. In control engineering, such set-point regulation problems are commonly tackled using multi-input, multi-output proportional and integral (PI) feedback controllers. Building on our recent results for population management with single goals, we develop a PI control approach in a context of multi-objective population management. We show that robust set-point regulation is achieved by using a modified PI controller with saturation and anti-windup elements, both described in the paper, and illustrate the theory with examples. Our results apply more generally to linear control systems with positive state variables, including a class of infinite-dimensional systems, and thus have broader appeal.
Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.
Analysis of the Multiple-Solution Response of a Flexible Rotor Supported on Non-Linear Squeeze Film Dampers

NASA Astrophysics Data System (ADS)

ZHU, C. S.; ROBB, D. A.; EWINS, D. J.

2002-05-01

The multiple-solution response of rotors supported on squeeze film dampers is a typical non-linear phenomenon. The behaviour of the multiple-solution response in a flexible rotor supported on two identical squeeze film dampers with centralizing springs is studied by three methods: synchronous circular centred-orbit motion solution, numerical integration method and slow acceleration method using the assumption of a short bearing and cavitated oil film; the differences of computational results obtained by the three different methods are compared in this paper. It is shown that there are three basic forms for the multiple-solution response in the flexible rotor system supported on the squeeze film dampers, which are the resonant, isolated bifurcation and swallowtail bifurcation multiple solutions. In the multiple-solution speed regions, the rotor motion may be subsynchronous, super-subsynchronous, almost-periodic and even chaotic, besides synchronous circular centred, even if the gravity effect is not considered. The assumption of synchronous circular centred-orbit motion for the journal and rotor around the static deflection line can be used only in some special cases; the steady state numerical integration method is very useful, but time consuming. Using the slow acceleration method, not only can the multiple-solution speed regions be detected, but also the non-synchronous response regions.
A quantitative model of application slow-down in multi-resource shared systems

DOE PAGES

Lim, Seung-Hwan; Kim, Youngjae

2016-12-26

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
A quantitative model of application slow-down in multi-resource shared systems

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

Lim, Seung-Hwan; Kim, Youngjae

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.
Spatial summation revealed in the earliest visual evoked component C1 and the effect of attention on its linearity.

PubMed

Chen, Juan; Yu, Qing; Zhu, Ziyun; Peng, Yujia; Fang, Fang

2016-01-01

In natural scenes, multiple objects are usually presented simultaneously. How do specific areas of the brain respond to multiple objects based on their responses to each individual object? Previous functional magnetic resonance imaging (fMRI) studies have shown that the activity induced by a multiobject stimulus in the primary visual cortex (V1) can be predicted by the linear or nonlinear sum of the activities induced by its component objects. However, there has been little evidence from electroencephelogram (EEG) studies so far. Here we explored how V1 responded to multiple objects by comparing the EEG signals evoked by a three-grating stimulus with those evoked by its two components (the central grating and 2 flanking gratings). We focused on the earliest visual component C1 (onset latency of ∼50 ms) because it has been shown to reflect the feedforward responses of neurons in V1. We found that when the stimulus was unattended, the amplitude of the C1 evoked by the three-grating stimulus roughly equaled the sum of the amplitudes of the C1s evoked by its two components, regardless of the distances between these gratings. When the stimulus was attended, this linear spatial summation existed only when the three gratings were far apart from each other. When the three gratings were close to each other, the spatial summation became compressed. These results suggest that the earliest visual responses in V1 follow a linear summation rule when attention is not involved and that attention can affect the earliest interactions between multiple objects. Copyright © 2016 the American Physiological Society.
MAPPING THE SHORES OF THE BROWN DWARF DESERT. II. MULTIPLE STAR FORMATION IN TAURUS-AURIGA

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

Kraus, Adam L.; Ireland, Michael J.; Martinache, Frantz

2011-04-10

We have conducted a high-resolution imaging study of the Taurus-Auriga star-forming region in order to characterize the primordial outcome of multiple star formation and the extent of the brown dwarf desert. Our survey identified 16 new binary companions to primary stars with masses of 0.25-2.5 M{sub sun}, raising the total number of binary pairs (including components of high-order multiples) with separations of 3-5000 AU to 90. We find that {approx}2/3-3/4 of all Taurus members are multiple systems of two or more stars, while the other {approx}1/4-1/3 appear to have formed as single stars; the distribution of high-order multiplicity suggests thatmore » fragmentation into a wide binary has no impact on the subsequent probability that either component will fragment again. The separation distribution for solar-type stars (0.7-2.5 M{sub sun}) is nearly log-flat over separations of 3-5000 AU, but lower-mass stars (0.25-0.7 M{sub sun}) show a paucity of binary companions with separations of {approx}>200 AU. Across this full mass range, companion masses are well described with a linear-flat function; all system mass ratios (q = M{sub B} /M{sub A} ) are equally probable, apparently including substellar companions. Our results are broadly consistent with the two expected modes of binary formation (free-fall fragmentation on large scales and disk fragmentation on small scales), but the distributions provide some clues as to the epochs at which the companions are likely to form.« less
SU-E-T-197: Helical Cranial-Spinal Treatments with a Linear Accelerator

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

Anderson, J; Bernard, D; Liao, Y

2014-06-01

Purpose: Craniospinal irradiation (CSI) of systemic disease requires a high level of beam intensity modulation to reduce dose to bone marrow and other critical structures. Current helical delivery machines can take 30 minutes or more of beam-on time to complete these treatments. This pilot study aims to test the feasibility of performing helical treatments with a conventional linear accelerator using longitudinal couch travel during multiple gantry revolutions. Methods: The VMAT optimization package of the Eclipse 10.0 treatment planning system was used to optimize pseudo-helical CSI plans of 5 clinical patient scans. Each gantry revolution was divided into three 120° arcsmore » with each isocenter shifted longitudinally. Treatments requiring more than the maximum 10 arcs used multiple plans with each plan after the first being optimized including the dose of the others (Figure 1). The beam pitch was varied between 0.2 and 0.9 (couch speed 5- 20cm/revolution and field width of 22cm) and dose-volume histograms of critical organs were compared to tomotherapy plans. Results: Viable pseudo-helical plans were achieved using Eclipse. Decreasing the pitch from 0.9 to 0.2 lowered the maximum lens dose by 40%, the mean bone marrow dose by 2.1% and the maximum esophagus dose by 17.5%. (Figure 2). Linac-based helical plans showed dose results comparable to tomotherapy delivery for both target coverage and critical organ sparing, with the D50 of bone marrow and esophagus respectively 12% and 31% lower in the helical linear accelerator plan (Figure 3). Total mean beam-on time for the linear accelerator plan was 8.3 minutes, 54% faster than the tomotherapy average for the same plans. Conclusions: This pilot study has demonstrated the feasibility of planning pseudo-helical treatments for CSI targets using a conventional linac and dynamic couch movement, and supports the ongoing development of true helical optimization and delivery.« less
Accelerometer output and its association with energy expenditure during manual wheelchair propulsion.

PubMed

Learmonth, Y C; Kinnett-Hopkins, D; Rice, I M; Dysterheft, J L; Motl, R W

2016-02-01

This is an experimental design. This study examined the association between rates of energy expenditure (that is, oxygen consumption (VO2)) and accelerometer counts (that is, vector magnitude (VM)) across a range of speeds during manual wheelchair propulsion on a motor-driven treadmill. Such an association allows for the generation of cutoff points for quantifying the time spent in moderate-to-vigorous physical activity (MVPA) during manual wheelchair propulsion. The study was conducted in the University Laboratory. Twenty-four manual wheelchair users completed a 6-min period of seated rest and three 6-min periods of manual wheelchair propulsion on a motor-driven wheelchair treadmill. The 6-min periods of wheelchair propulsion corresponded with three treadmill speeds (1.5, 3.0 and 4.5 mph) that elicited a range of physical activity intensities. Participants wore a portable metabolic unit and accelerometers on both wrists. Primary outcome measures included steady-state VO2 and VM, and the strength of association between VO2 and VM was based on the multiple correlation and squared multiple correlation coefficients from linear regression analyses. Strong linear associations were established between VO2 and VM for the left (R=0.93±0.44; R2=0.87±0.19), right (R=0.95±0.37; R2=0.90±0.14) and combined (R=0.94±0.38; R2=0.88±0.15) accelerometers. The linear relationship between VO2 and VM for the left, right and combined wrists yielded cutoff points for MVPA of 3659 ±1302, 3630±1403 and 3644±1339 counts min(-1), respectively. We provide cutoff points based on the linear association between energy expenditure and accelerometer counts for estimating time spent in MVPA during manual wheelchair propulsion using wrist-worn accelerometry. The similarity across wrist location permits flexibility in selecting a location for wrist accelerometry placement.
A Generic Multiple Reaction Monitoring Based Approach for Plant Flavonoids Profiling Using a Triple Quadrupole Linear Ion Trap Mass Spectrometry

NASA Astrophysics Data System (ADS)

Yan, Zhixiang; Lin, Ge; Ye, Yang; Wang, Yitao; Yan, Ru

2014-06-01

Flavonoids are one of the largest classes of plant secondary metabolites serving a variety of functions in plants and associating with a number of health benefits for humans. Typically, they are co-identified with many other secondary metabolites using untargeted metabolomics. The limited data quality of untargeted workflow calls for a shift from the breadth-first to the depth-first screening strategy when a specific biosynthetic pathway is focused on. Here we introduce a generic multiple reaction monitoring (MRM)-based approach for flavonoids profiling in plants using a hybrid triple quadrupole linear ion trap (QTrap) mass spectrometer. The approach includes four steps: (1) preliminary profiling of major aglycones by multiple ion monitoring triggered enhanced product ion scan (MIM-EPI); (2) glycones profiling by precursor ion triggered EPI scan (PI-EPI) of major aglycones; (3) comprehensive aglycones profiling by combining MIM-EPI and neutral loss triggered EPI scan (NL-EPI) of major glycone; (4) in-depth flavonoids profiling by MRM-EPI with elaborated MRM transitions. Particularly, incorporation of the NH3 loss and sugar elimination proved to be very informative and confirmative for flavonoids screening. This approach was applied for profiling flavonoids in Astragali radix ( Huangqi), a famous herb widely used for medicinal and nutritional purposes in China. In total, 421 flavonoids were tentatively characterized, among which less than 40 have been previously reported in this medicinal plant. This MRM-based approach provides versatility and sensitivity that required for flavonoids profiling in plants and serves as a useful tool for plant metabolomics.

An analytical approach to reduce between-plate variation in multiplex assays that measure antibodies to Plasmodium falciparum antigens.

PubMed

Fang, Rui; Wey, Andrew; Bobbili, Naveen K; Leke, Rose F G; Taylor, Diane Wallace; Chen, John J

2017-07-17

Antibodies play an important role in immunity to malaria. Recent studies show that antibodies to multiple antigens, as well as, the overall breadth of the response are associated with protection from malaria. Yet, the variability and reliability of antibody measurements against a combination of malarial antigens using multiplex assays have not been well characterized. A normalization procedure for reducing between-plate variation using replicates of pooled positive and negative controls was investigated. Sixty test samples (30 from malaria-positive and 30 malaria-negative individuals), together with five pooled positive-controls and two pooled negative-controls, were screened for antibody levels to 9 malarial antigens, including merozoite antigens (AMA1, EBA175, MSP1, MSP2, MSP3, MSP11, Pf41), sporozoite CSP, and pregnancy-associated VAR2CSA. The antibody levels were measured in triplicate on each of 3 plates, and the experiments were replicated on two different days by the same technician. The performance of the proposed normalization procedure was evaluated with the pooled controls for the test samples on both the linear and natural-log scales. Compared with data on the linear scale, the natural-log transformed data were less skewed and reduced the mean-variance relationship. The proposed normalization procedure using pooled controls on the natural-log scale significantly reduced between-plate variation. For malaria-related research that measure antibodies to multiple antigens with multiplex assays, the natural-log transformation is recommended for data analysis and use of the normalization procedure with multiple pooled controls can improve the precision of antibody measurements.
Multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid with high-performance liquid chromatography for the determination of steroid sex hormones in water and urine.

PubMed

Liao, Keren; Mei, Meng; Li, Haonan; Huang, Xiaojia; Wu, Cuiqin

2016-02-01

The development of a simple and sensitive analytical approach that combines multiple monolithic fiber solid-phase microextraction with liquid desorption followed by high-performance liquid chromatography with diode array detection is proposed for the determination of trace levels of seven steroid sex hormones (estriol, 17β-estradiol, testosterone, ethinylestradiol, estrone, progesterone and mestranol) in water and urine matrices. To extract the target analytes effectively, multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid was used to concentrate hormones. Several key extraction parameters including desorption solvent, extraction and desorption time, pH value and ionic strength in sample matrix were investigated in detail. Under the optimal experimental conditions, the limits of detection were found to be in the range of 0.027-0.12 μg/L. The linear range was 0.10-200 μg/L for 17β-estradiol, 0.25-200 μg/L estriol, ethinylestradiol and estrone, and 0.50-200 μg/L for the other hormones. Satisfactory linearities were achieved for analytes with the correlation coefficients above 0.99. Acceptable method reproducibility was achieved by evaluating the repeatability and intermediate precision with relative standard deviations of both less than 8%. The enrichment factors ranged from 54- to 74-fold. Finally, the proposed method was successfully applied to the analysis of steroid sex hormones in environmental water samples and human urines with spiking recoveries ranged from 75.6 to 116%. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulating the effects of climatic variation on stem carbon accumulation of a ponderosa pine stand: comparison with annual growth increment data.

PubMed

Hunt, E R; Martin, F C; Running, S W

1991-01-01

Simulation models of ecosystem processes may be necessary to separate the long-term effects of climate change on forest productivity from the effects of year-to-year variations in climate. The objective of this study was to compare simulated annual stem growth with measured annual stem growth from 1930 to 1982 for a uniform stand of ponderosa pine (Pinus ponderosa Dougl.) in Montana, USA. The model, FOREST-BGC, was used to simulate growth assuming leaf area index (LAI) was either constant or increasing. The measured stem annual growth increased exponentially over time; the differences between the simulated and measured stem carbon accumulations were not large. Growth trends were removed from both the measured and simulated annual increments of stem carbon to enhance the year-to-year variations in growth resulting from climate. The detrended increments from the increasing LAI simulation fit the detrended increments of the stand data over time with an R(2) of 0.47; the R(2) increased to 0.65 when the previous year's simulated detrended increment was included with the current year's simulated increment to account for autocorrelation. Stepwise multiple linear regression of the detrended increments of the stand data versus monthly meteorological variables had an R(2) of 0.37, and the R(2) increased to 0.47 when the previous year's meteorological data were included to account for autocorrelation. Thus, FOREST-BGC was more sensitive to the effects of year-to-year climate variation on annual stem growth than were multiple linear regression models.
Exploring the association between parental rearing styles and medical students' critical thinking disposition in China.

PubMed

Huang, Lei; Wang, Zhaoxin; Yao, Yuhong; Shan, Chang; Wang, Haojie; Zhu, Mengyi; Lu, Yuan; Sun, Pengfei; Zhao, Xudong

2015-05-14

Critical thinking is an essential ability for medical students. However, the relationship between parental rearing styles and medical students' critical thinking disposition has rarely been considered. The aim of this study was to investigate whether parental rearing styles were significant predictors of critical thinking disposition among Chinese medical students. 1,075 medical students from the first year to the fifth year attending one of three medical schools in China were recruited via multistage stratified cluster sampling. The Chinese Critical Thinking Disposition Inventory(CTDI-CV) and The Egna Minnen av Barndoms Uppfostran (EMBU) questionnaire were applied to collect data and to conduct descriptive analysis. Stepwise multiple linear regression was used to analyze the data. The critical thinking disposition average mean score was 287.44 with 632 participants (58.79%) demonstrating positive critical thinking disposition. Stepwise multiple linear regression analysis revealed that the rearing styles of fathers, including "overprotection", "emotional warmth and understanding", "rejection" and "over-interference" were significant predictors of medical students' critical thinking disposition that explained 79.0% of the variance in critical thinking ability. Rearing styles of mothers including "emotional warmth and understanding", "punishing" and "rejection" were also found to be significant predictors, and explained 77.0% of the variance. Meaningful association has been evidenced between parental rearing styles and Chinese medical students' critical thinking disposition. Parental rearing styles should be considered as one of the many potential determinant factors that contribute to the cultivation of medical students' critical thinking capability. Positive parental rearing styles should be encouraged in the cultivation of children's critical thinking skills.
Prevalence of Pterygia in Hawaii: Examining Cumulative Surfing Hours as a Risk Factor.

PubMed

Lin, Alexander D; Miles, Ku'ulei; Brinks, Mitchel V

2016-08-01

To examine the association between surfing and pterygium prevalence in Hawaii. A convenience sampling was performed at four beaches on the island of Oahu, Hawaii. A total of 169 individuals were interviewed and underwent penlight examination to assess grade and extent of pterygium. Of 169 participants aged 18-80 years, 88 non-surfers, 41 occasional surfers, 15 recreational surfers and 25 surfing enthusiasts were identified based on their lifetime surfing hours. Overall, 19 participants were found to have pterygia (28 pterygia total) including two non-surfers (2.3%), five occasional surfers (12.2%), three recreational surfers (20.0%), and nine enthusiast surfers (36.0%). Variables associated with pterygium prevalence were lifetime surfing hours (p < 0.0001), outdoor occupation (p = 0.04), Hawaiian residence (p = 0.009), and Hawaiian/Pacific Islander ethnicity (p = 0.002). Multiple logistic regression with the outcome of pterygium was performed, along with multiple linear regression for the continuous outcomes of corneal extent, chord length, and apex-visual axis gap, with lifetime surfing hours as the primary explanatory variable. After adjustment for confounders, a significant linear relationship was observed between chord length and lifetime surfing hours (p = 0.01). Surfing was associated with an increased pterygium prevalence and trend towards an association with increased pterygium severity. Increased risk of exposure to wind, particle irritation, and ultraviolet (UV) radiation while surfing may contribute to pterygium development. Implications for public health include promoting UV protective eyewear during surfing, in addition to raising awareness about the association of pterygia and the sport of surfing.
Precise Sequential DNA Ligation on A Solid Substrate: Solid-Based Rapid Sequential Ligation of Multiple DNA Molecules

PubMed Central

Takita, Eiji; Kohda, Katsunori; Tomatsu, Hajime; Hanano, Shigeru; Moriya, Kanami; Hosouchi, Tsutomu; Sakurai, Nozomu; Suzuki, Hideyuki; Shinmyo, Atsuhiko; Shibata, Daisuke

2013-01-01

Ligation, the joining of DNA fragments, is a fundamental procedure in molecular cloning and is indispensable to the production of genetically modified organisms that can be used for basic research, the applied biosciences, or both. Given that many genes cooperate in various pathways, incorporating multiple gene cassettes in tandem in a transgenic DNA construct for the purpose of genetic modification is often necessary when generating organisms that produce multiple foreign gene products. Here, we describe a novel method, designated PRESSO (precise sequential DNA ligation on a solid substrate), for the tandem ligation of multiple DNA fragments. We amplified donor DNA fragments with non-palindromic ends, and ligated the fragment to acceptor DNA fragments on solid beads. After the final donor DNA fragments, which included vector sequences, were joined to the construct that contained the array of fragments, the ligation product (the construct) was thereby released from the beads via digestion with a rare-cut meganuclease; the freed linear construct was circularized via an intra-molecular ligation. PRESSO allowed us to rapidly and efficiently join multiple genes in an optimized order and orientation. This method can overcome many technical challenges in functional genomics during the post-sequencing generation. PMID:23897972
A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

PubMed Central

Nam, Haewon

2017-01-01

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects. PMID:28604794
White matter tract abnormalities are associated with cognitive dysfunction in secondary progressive multiple sclerosis.

PubMed

Meijer, Kim A; Muhlert, Nils; Cercignani, Mara; Sethi, Varun; Ron, Maria A; Thompson, Alan J; Miller, David H; Chard, Declan; Geurts, Jeroen Jg; Ciccarelli, Olga

2016-10-01

While our knowledge of white matter (WM) pathology underlying cognitive impairment in relapsing remitting multiple sclerosis (MS) is increasing, equivalent understanding in those with secondary progressive (SP) MS lags behind. The aim of this study is to examine whether the extent and severity of WM tract damage differ between cognitively impaired (CI) and cognitively preserved (CP) secondary progressive multiple sclerosis (SPMS) patients. Conventional magnetic resonance imaging (MRI) and diffusion MRI were acquired from 30 SPMS patients and 32 healthy controls (HC). Cognitive domains commonly affected in MS patients were assessed. Linear regression was used to predict cognition. Diffusion measures were compared between groups using tract-based spatial statistics (TBSS). A total of 12 patients were classified as CI, and processing speed was the most commonly affected domain. The final regression model including demographic variables and radial diffusivity explained the greatest variance of cognitive performance (R 2 = 0.48, p = 0.002). SPMS patients showed widespread loss of WM integrity throughout the WM skeleton when compared with HC. When compared with CP patients, CI patients showed more extensive and severe damage of several WM tracts, including the fornix, superior longitudinal fasciculus and forceps major. Loss of WM integrity assessed using TBSS helps to explain cognitive decline in SPMS patients. © The Author(s), 2016.
Multiple degree of freedom object recognition using optical relational graph decision nets

NASA Technical Reports Server (NTRS)

Casasent, David P.; Lee, Andrew J.

1988-01-01

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.
A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Multiple imputation for cure rate quantile regression with censored data.

PubMed

Wu, Yuanshan; Yin, Guosheng

2017-03-01

The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject. By utilizing this estimated probability and Bernoulli sample imputation, we can classify each subject as cured or uncured, and then employ the locally weighted method to estimate the quantile regression coefficients with only the uncured subjects. Repeating the imputation procedure multiple times and taking an average over the resultant estimators, we obtain consistent estimators for the quantile regression coefficients. Our approach relaxes the usual global linearity assumption, so that we can apply quantile regression to any particular quantile of interest. We establish asymptotic properties for the proposed estimators, including both consistency and asymptotic normality. We conduct simulation studies to assess the finite-sample performance of the proposed multiple imputation method and apply it to a lung cancer study as an illustration. © 2016, The International Biometric Society.
Factors affecting costs in Medicaid populations with behavioral health disorders.

PubMed

Freeman, Elsie; McGuire, Catherine A; Thomas, John W; Thayer, Deborah A

2014-03-01

Persons with behavioral disorders incur higher healthcare costs. Although they utilize behavioral health (BH) services others do not, they also have higher utilization of medical services : To determine the degree to which higher costs for persons with BH disorders are attributable to utilization of BH services, multiple chronic medical conditions (CMCs) or other issues specific to populations with BH disorders. Data base consisted of claims for 63,141 Medicaid beneficiaries, 49% of whom had one of 5 categories of BH disorder. Generalized linear models were used to identify relative impact of demographics, BH status, multiple CMCs and primary care access on total, behavioral, nonbehavioral, and medical/surgical costs. Number of CMCs was associated with significant increases in all cost categories, including behavioral costs. Presence of any BH disorder significantly influenced these same costs, including those not associated with BH care. Effect size in each cost category varied by BH group. BH status has a large impact on all healthcare costs, including costs of medical and other non-BH services. The number of CMCs affects BH costs independent of BH disorder. Results suggest that costs might be reduced through better integration of behavioral and medical health services.
Computational Modeling of Micro-Crack Induced Attenuation in CFRP Composites

NASA Technical Reports Server (NTRS)

Roberts, R. A.; Leckey, C. A. C.

2012-01-01

A computational study is performed to determine the contribution to ultrasound attenuation in carbon fiber reinforced polymer composite laminates of linear elastic scattering by matrix micro-cracking. Multiple scattering approximations are benchmarked against exact computational approaches. Results support linear scattering as the source of observed increased attenuation in the presence of micro-cracking.
Avoiding Communication in Dense Linear Algebra

DTIC Science & Technology

2013-08-16

Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.1 Asymptotic Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . 6...and parallelizing Strassen’s matrix multiplication algorithm (Chapter 11). 6 Chapter 2 Preliminaries 2.1 Notation and Definitions In this section we...between computations and algo- rithms). The following definition is based on [56]: Definition 2.1. A classical algorithm in linear algebra is one that
Re-Mediating Classroom Activity with a Non-Linear, Multi-Display Presentation Tool

ERIC Educational Resources Information Center

Bligh, Brett; Coyle, Do

2013-01-01

This paper uses an Activity Theory framework to evaluate the use of a novel, multi-screen, non-linear presentation tool. The Thunder tool allows presenters to manipulate and annotate multiple digital slides and to concurrently display a selection of juxtaposed resources across a wall-sized projection area. Conventional, single screen presentation…
Secret Message Decryption: Group Consulting Projects Using Matrices and Linear Programming

ERIC Educational Resources Information Center

Gurski, Katharine F.

2009-01-01

We describe two short group projects for finite mathematics students that incorporate matrices and linear programming into fictional consulting requests presented as a letter to the students. The students are required to use mathematics to decrypt secret messages in one project involving matrix multiplication and inversion. The second project…
Timber management planning with timber ram and goal programming

Treesearch

Richard C. Field

1978-01-01

By using goal programming to enhance the linear programming of Timber RAM, multiple decision criteria were incorporated in the timber management planning of a National Forest in the southeastern United States. Combining linear and goal programming capitalizes on the advantages of the two techniques and produces operationally feasible solutions. This enhancement may...
An Introduction to Multilinear Formula Score Theory. Measurement Series 84-4.

ERIC Educational Resources Information Center

Levine, Michael V.

Formula score theory (FST) associates each multiple choice test with a linear operator and expresses all of the real functions of item response theory as linear combinations of the operator's eigenfunctions. Hard measurement problems can then often be reformulated as easier, standard mathematical problems. For example, the problem of estimating…
Possible limits of plasma linear colliders

NASA Astrophysics Data System (ADS)

Zimmermann, F.

2017-07-01

Plasma linear colliders have been proposed as next or next-next generation energy-frontier machines for high-energy physics. I investigate possible fundamental limits on energy and luminosity of such type of colliders, considering acceleration, multiple scattering off plasma ions, intrabeam scattering, bremsstrahlung, and betatron radiation. The question of energy efficiency is also addressed.
Renormalizability of the gradient flow in the 2D O(N) non-linear sigma model

NASA Astrophysics Data System (ADS)

Makino, Hiroki; Suzuki, Hiroshi

2015-03-01

It is known that the gauge field and its composite operators evolved by the Yang-Mills gradient flow are ultraviolet (UV) finite without any multiplicative wave function renormalization. In this paper, we prove that the gradient flow in the 2D O(N) non-linear sigma model possesses a similar property: The flowed N-vector field and its composite operators are UV finite without multiplicative wave function renormalization. Our proof in all orders of perturbation theory uses a (2+1)-dimensional field theoretical representation of the gradient flow, which possesses local gauge invariance without gauge field. As an application of the UV finiteness of the gradient flow, we construct the energy-momentum tensor in the lattice formulation of the O(N) non-linear sigma model that automatically restores the correct normalization and the conservation law in the continuum limit.

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.
Focal points and principal solutions of linear Hamiltonian systems revisited

NASA Astrophysics Data System (ADS)

Šepitka, Peter; Šimon Hilscher, Roman

2018-05-01

In this paper we present a novel view on the principal (and antiprincipal) solutions of linear Hamiltonian systems, as well as on the focal points of their conjoined bases. We present a new and unified theory of principal (and antiprincipal) solutions at a finite point and at infinity, and apply it to obtain new representation of the multiplicities of right and left proper focal points of conjoined bases. We show that these multiplicities can be characterized by the abnormality of the system in a neighborhood of the given point and by the rank of the associated T-matrix from the theory of principal (and antiprincipal) solutions. We also derive some additional important results concerning the representation of T-matrices and associated normalized conjoined bases. The results in this paper are new even for completely controllable linear Hamiltonian systems. We also discuss other potential applications of our main results, in particular in the singular Sturmian theory.
On optimal control of linear systems in the presence of multiplicative noise

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1976-01-01

This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programming. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an 'enforced separation' solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.
Fault detection for singular switched linear systems with multiple time-varying delay in finite frequency domain

NASA Astrophysics Data System (ADS)

Zhai, Ding; Lu, Anyang; Li, Jinghao; Zhang, Qingling

2016-10-01

This paper deals with the problem of the fault detection (FD) for continuous-time singular switched linear systems with multiple time-varying delay. In this paper, the actuator fault is considered. Besides, the systems faults and unknown disturbances are assumed in known frequency domains. Some finite frequency performance indices are initially introduced to design the switched FD filters which ensure that the filtering augmented systems under switching signal with average dwell time are exponentially admissible and guarantee the fault input sensitivity and disturbance robustness. By developing generalised Kalman-Yakubovic-Popov lemma and using Parseval's theorem and Fourier transform, finite frequency delay-dependent sufficient conditions for the existence of such a filter which can guarantee the finite-frequency H- and H∞ performance are derived and formulated in terms of linear matrix inequalities. Four examples are provided to illustrate the effectiveness of the proposed finite frequency method.
Multiple time scale analysis of pressure oscillations in solid rocket motors

NASA Astrophysics Data System (ADS)

Ahmed, Waqas; Maqsood, Adnan; Riaz, Rizwan

2018-03-01

In this study, acoustic pressure oscillations for single and coupled longitudinal acoustic modes in Solid Rocket Motor (SRM) are investigated using Multiple Time Scales (MTS) method. Two independent time scales are introduced. The oscillations occur on fast time scale whereas the amplitude and phase changes on slow time scale. Hopf bifurcation is employed to investigate the properties of the solution. The supercritical bifurcation phenomenon is observed for linearly unstable system. The amplitude of the oscillations result from equal energy gain and loss rates of longitudinal acoustic modes. The effect of linear instability and frequency of longitudinal modes on amplitude and phase of oscillations are determined for both single and coupled modes. For both cases, the maximum amplitude of oscillations decreases with the frequency of acoustic mode and linear instability of SRM. The comparison of analytical MTS results and numerical simulations demonstrate an excellent agreement.
Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.
Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…
Efficient parallel simulation of CO2 geologic sequestration insaline aquifers

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

Zhang, Keni; Doughty, Christine; Wu, Yu-Shu

2007-01-01

An efficient parallel simulator for large-scale, long-termCO2 geologic sequestration in saline aquifers has been developed. Theparallel simulator is a three-dimensional, fully implicit model thatsolves large, sparse linear systems arising from discretization of thepartial differential equations for mass and energy balance in porous andfractured media. The simulator is based on the ECO2N module of the TOUGH2code and inherits all the process capabilities of the single-CPU TOUGH2code, including a comprehensive description of the thermodynamics andthermophysical properties of H2O-NaCl- CO2 mixtures, modeling singleand/or two-phase isothermal or non-isothermal flow processes, two-phasemixtures, fluid phases appearing or disappearing, as well as saltprecipitation or dissolution. The newmore » parallel simulator uses MPI forparallel implementation, the METIS software package for simulation domainpartitioning, and the iterative parallel linear solver package Aztec forsolving linear equations by multiple processors. In addition, theparallel simulator has been implemented with an efficient communicationscheme. Test examples show that a linear or super-linear speedup can beobtained on Linux clusters as well as on supercomputers. Because of thesignificant improvement in both simulation time and memory requirement,the new simulator provides a powerful tool for tackling larger scale andmore complex problems than can be solved by single-CPU codes. Ahigh-resolution simulation example is presented that models buoyantconvection, induced by a small increase in brine density caused bydissolution of CO2.« less
Landsat D Thematic Mapper image dimensionality reduction and geometric correction accuracy

NASA Technical Reports Server (NTRS)

Ford, G. E.

1986-01-01

To characterize and quantify the performance of the Landsat thematic mapper (TM), techniques for dimensionality reduction by linear transformation have been studied and evaluated and the accuracy of the correction of geometric errors in TM images analyzed. Theoretical evaluations and comparisons for existing methods for the design of linear transformation for dimensionality reduction are presented. These methods include the discrete Karhunen Loeve (KL) expansion, Multiple Discriminant Analysis (MDA), Thematic Mapper (TM)-Tasseled Cap Linear Transformation and Singular Value Decomposition (SVD). A unified approach to these design problems is presented in which each method involves optimizing an objective function with respect to the linear transformation matrix. From these studies, four modified methods are proposed. They are referred to as the Space Variant Linear Transformation, the KL Transform-MDA hybrid method, and the First and Second Version of the Weighted MDA method. The modifications involve the assignment of weights to classes to achieve improvements in the class conditional probability of error for classes with high weights. Experimental evaluations of the existing and proposed methods have been performed using the six reflective bands of the TM data. It is shown that in terms of probability of classification error and the percentage of the cumulative eigenvalues, the six reflective bands of the TM data require only a three dimensional feature space. It is shown experimentally as well that for the proposed methods, the classes with high weights have improvements in class conditional probability of error estimates as expected.
Determination and importance of temperature dependence of retention coefficient (RPHPLC) in QSAR model of nitrazepams' partition coefficient in bile acid micelles.

PubMed

Posa, Mihalj; Pilipović, Ana; Lalić, Mladena; Popović, Jovan

2011-02-15

Linear dependence between temperature (t) and retention coefficient (k, reversed phase HPLC) of bile acids is obtained. Parameters (a, intercept and b, slope) of the linear function k=f(t) highly correlate with bile acids' structures. Investigated bile acids form linear congeneric groups on a principal component (calculated from k=f(t)) score plot that are in accordance with conformations of the hydroxyl and oxo groups in a bile acid steroid skeleton. Partition coefficient (K(p)) of nitrazepam in bile acids' micelles is investigated. Nitrazepam molecules incorporated in micelles show modified bioavailability (depo effect, higher permeability, etc.). Using multiple linear regression method QSAR models of nitrazepams' partition coefficient, K(p) are derived on the temperatures of 25°C and 37°C. For deriving linear regression models on both temperatures experimentally obtained lipophilicity parameters are included (PC1 from data k=f(t)) and in silico descriptors of the shape of a molecule while on the higher temperature molecular polarisation is introduced. This indicates the fact that the incorporation mechanism of nitrazepam in BA micelles changes on the higher temperatures. QSAR models are derived using partial least squares method as well. Experimental parameters k=f(t) are shown to be significant predictive variables. Both QSAR models are validated using cross validation and internal validation method. PLS models have slightly higher predictive capability than MLR models. Copyright © 2010 Elsevier B.V. All rights reserved.
Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.
Evolutionary tree design: An exploratory study of the influence of linear versus branching format on visitors' interpretation and understanding across age groups

NASA Astrophysics Data System (ADS)

MacDonald, Teresa Elise

This exploratory study sought to investigate the influence of tree graphic design---specifically linear versus branching depictions of taxa---on visitors in three different age groups (aged 11-13, 14-18, adults) interpretation and understanding using a multiple-case study strategy. The findings from this research indicate that linear and branched depictions elicit qualitatively different narratives and explanations about the relationships between the taxa in all age groups. Branched tree graphics support scientifically appropriate explanations of evolutionary relationships, i.e. that taxa are related via shared or common ancestry; while linear representations reinforce intuitive interpretations of ancestor-descendant or anagenic relationships. Furthermore, differences in the language used for linear and branched trees suggests that there is a spectrum within an analogy of developmental change that is thought to serve as a transitional concept between intuitive and scientific understanding--with 'evolved from' for branched depictions of taxa representing a shift towards an interpretation of shared ancestry rather than an individual transformation from one thing into another. In addition, branched graphics appear to support the correct reading and interpretation of shared or common ancestry in tree diagrams. Mixed reasoning was common and overall reasoning patterns were broadly similar among participants in all age groups, however, older youth (aged 14 to 18) and adults often provided more detail in their explanations and sometimes included references to evolutionary ideas such as variation, inheritance and selection.
Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.
Inference regarding multiple structural changes in linear models with endogenous regressors☆

PubMed Central

Hall, Alastair R.; Han, Sanggohn; Boldea, Otilia

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares (2SLS) criterion yields consistent estimators of these parameters. We develop a methodology for estimation and inference of the parameters of the model based on 2SLS. The analysis covers the cases where the reduced form is either stable or unstable. The methodology is illustrated via an application to the New Keynesian Phillips Curve for the US. PMID:23805021
Linearity-Preserving Limiters on Irregular Grids

NASA Technical Reports Server (NTRS)

Berger, Marsha; Aftosmis, Michael; Murman, Scott

2004-01-01

This paper examines the behavior of flux and slope limiters on non-uniform grids in multiple dimensions. We note that on non-uniform grids the scalar formulation in standard use today sacrifices k-exactness, even for linear solutions, impacting both accuracy and convergence. We rewrite some well-known limiters in a n way to highlight their underlying symmetry, and use this to examine both traditional and novel limiter formulations. A consistent method of handling stretched meshes is developed, as is a new directional formulation in multiple dimensions for irregular grids. Results are presented demonstrating improved accuracy and convergence using a combination of model problems and complex three-dimensional examples.
Estimating the intensity of a cyclic Poisson process in the presence of additive and multiplicative linear trend

NASA Astrophysics Data System (ADS)

Wayan Mangku, I.

2017-10-01

In this paper we survey some results on estimation of the intensity function of a cyclic Poisson process in the presence of additive and multiplicative linear trend. We do not assume any parametric form for the cyclic component of the intensity function, except that it is periodic. Moreover, we consider the case when there is only a single realization of the Poisson process is observed in a bounded interval. The considered estimators are weakly and strongly consistent when the size of the observation interval indefinitely expands. Asymptotic approximations to the bias and variance of those estimators are presented.
Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.
Detecting multiple outliers in linear functional relationship model for circular variables using clustering technique

NASA Astrophysics Data System (ADS)

Mokhtar, Nurkhairany Amyra; Zubairi, Yong Zulina; Hussin, Abdul Ghapor

2017-05-01

Outlier detection has been used extensively in data analysis to detect anomalous observation in data and has important application in fraud detection and robust analysis. In this paper, we propose a method in detecting multiple outliers for circular variables in linear functional relationship model. Using the residual values of the Caires and Wyatt model, we applied the hierarchical clustering procedure. With the use of tree diagram, we illustrate the graphical approach of the detection of outlier. A simulation study is done to verify the accuracy of the proposed method. Also, an illustration to a real data set is given to show its practical applicability.
Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.
Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

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

2008-01-01

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

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

PubMed Central

Williams, D. Keith; Muddiman, David C.

2008-01-01

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

NASA Astrophysics Data System (ADS)

Clausel, M.; Grégoire, G.

2014-12-01

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

PubMed Central

Røislien, Jo; Lossius, Hans Morten; Kristiansen, Thomas

2015-01-01

Background Trauma is a leading global cause of death. Trauma mortality rates are higher in rural areas, constituting a challenge for quality and equality in trauma care. The aim of the study was to explore population density and transport time to hospital care as possible predictors of geographical differences in mortality rates, and to what extent choice of statistical method might affect the analytical results and accompanying clinical conclusions. Methods Using data from the Norwegian Cause of Death registry, deaths from external causes 1998–2007 were analysed. Norway consists of 434 municipalities, and municipality population density and travel time to hospital care were entered as predictors of municipality mortality rates in univariate and multiple regression models of increasing model complexity. We fitted linear regression models with continuous and categorised predictors, as well as piecewise linear and generalised additive models (GAMs). Models were compared using Akaike's information criterion (AIC). Results Population density was an independent predictor of trauma mortality rates, while the contribution of transport time to hospital care was highly dependent on choice of statistical model. A multiple GAM or piecewise linear model was superior, and similar, in terms of AIC. However, while transport time was statistically significant in multiple models with piecewise linear or categorised predictors, it was not in GAM or standard linear regression. Conclusions Population density is an independent predictor of trauma mortality rates. The added explanatory value of transport time to hospital care is marginal and model-dependent, highlighting the importance of exploring several statistical models when studying complex associations in observational data. PMID:25972600
Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

USGS Publications Warehouse

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.

2009-01-01

In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.
Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

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

2000-01-01

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

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.
Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...
Experiment in multiple-criteria energy policy analysis

NASA Astrophysics Data System (ADS)

Ho, J. K.

1980-07-01

An international panel of energy analysts participated in an experiment to use HOPE (holistic preference evaluation): an interactive parametric linear programming method for multiple criteria optimization. The criteria of cost, environmental effect, crude oil, and nuclear fuel were considered, according to BESOM: an energy model for the US in the year 2000.
Development of a technique for estimating noise covariances using multiple observers

NASA Technical Reports Server (NTRS)

Bundick, W. Thomas

1988-01-01

Friedland's technique for estimating the unknown noise variances of a linear system using multiple observers has been extended by developing a general solution for the estimates of the variances, developing the statistics (mean and standard deviation) of these estimates, and demonstrating the solution on two examples.
Log-Multiplicative Association Models as Item Response Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Yu, Hsiu-Ting

2007-01-01

Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented. First, we show that Anderson and colleagues (Anderson & Vermunt, 2000; Anderson & Bockenholt,…
Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)
Prospective Mathematics Teachers' Sense Making of Polynomial Multiplication and Factorization Modeled with Algebra Tiles

ERIC Educational Resources Information Center

Caglayan, Günhan

2013-01-01

This study is about prospective secondary mathematics teachers' understanding and sense making of representational quantities generated by algebra tiles, the quantitative units (linear vs. areal) inherent in the nature of these quantities, and the quantitative addition and multiplication operations--referent preserving versus referent…
A Solution to the Cosmic Conundrum including Cosmological Constant and Dark Energy Problems

NASA Astrophysics Data System (ADS)

Singh, A.

2009-12-01

A comprehensive solution to the cosmic conundrum is presented that also resolves key paradoxes of quantum mechanics and relativity. A simple mathematical model, the Gravity Nullification model (GNM), is proposed that integrates the missing physics of the spontaneous relativistic conversion of mass to energy into the existing physics theories, specifically a simplified general theory of relativity. Mechanistic mathematical expressions are derived for a relativistic universe expansion, which predict both the observed linear Hubble expansion in the nearby universe and the accelerating expansion exhibited by the supernova observations. The integrated model addresses the key questions haunting physics and Big Bang cosmology. It also provides a fresh perspective on the misconceived birth and evolution of the universe, especially the creation and dissolution of matter. The proposed model eliminates singularities from existing models and the need for the incredible and unverifiable assumptions including the superluminous inflation scenario, multiple universes, multiple dimensions, Anthropic principle, and quantum gravity. GNM predicts the observed features of the universe without any explicit consideration of time as a governing parameter.
Adaptive management for soil ecosystem services.

PubMed

Birgé, Hannah E; Bevans, Rebecca A; Allen, Craig R; Angeler, David G; Baer, Sara G; Wall, Diana H

2016-12-01

Ecosystem services provided by soil include regulation of the atmosphere and climate, primary (including agricultural) production, waste processing, decomposition, nutrient conservation, water purification, erosion control, medical resources, pest control, and disease mitigation. The simultaneous production of these multiple services arises from complex interactions among diverse aboveground and belowground communities across multiple scales. When a system is mismanaged, non-linear and persistent losses in ecosystem services can arise. Adaptive management is an approach to management designed to reduce uncertainty as management proceeds. By developing alternative hypotheses, testing these hypotheses and adjusting management in response to outcomes, managers can probe dynamic mechanistic relationships among aboveground and belowground soil system components. In doing so, soil ecosystem services can be preserved and critical ecological thresholds avoided. Here, we present an adaptive management framework designed to reduce uncertainty surrounding the soil system, even when soil ecosystem services production is not the explicit management objective, so that managers can reach their management goals without undermining soil multifunctionality or contributing to an irreversible loss of soil ecosystem services. Copyright © 2016. Published by Elsevier Ltd.
Exploring the Associations Among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum.

PubMed

Stage, Virginia C; Kolasa, Kathryn M; Díaz, Sebastián R; Duffrin, Melani W

2018-01-01

Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across North Carolina and Ohio; mean age 10 years old; gender (I = 53.2% female; C = 51.6% female). Dependent variable = post-test-nutrition knowledge; independent variables = baseline-nutrition knowledge, and post-test science and mathematics knowledge. Analyses included descriptive statistics and multiple linear regression. The hypothesized model predicted post-nutrition knowledge (F(437) = 149.4, p < .001; Adjusted R = .51). All independent variables were significant predictors with positive association. Science and mathematics knowledge were predictive of nutrition knowledge indicating use of an integrative science and mathematics curriculum to improve academic knowledge may also simultaneously improve nutrition knowledge among fourth-grade students. Teachers can benefit from integration by meeting multiple academic standards, efficiently using limited classroom time, and increasing nutrition education provided in the classroom. © 2018, American School Health Association.
Addressing Chronic Malnutrition through Multi-Sectoral, Sustainable Approaches: A Review of the Causes and Consequences

PubMed Central

Reinhardt, Kristina; Fanzo, Jessica

2014-01-01

Chronic malnutrition, including stunting, is an important example of a global challenge that spans multiple sectors, specifically health, agriculture, and the environment. The objective of this paper is to review current knowledge on the causes and consequences of chronic malnutrition and their relationship with multiple sectors. Understanding the causes includes approaching chronic malnutrition from the basic, underlying, and immediate levels. The causes reach from macro-level environmental influences to specific micronutrient intake. In order to effectively address stunting, it is important to understand the timing of stunting and the ability of individuals to catch up in terms of linear growth, cognitive ability, and immune function. The consequences of chronic malnutrition are transgenerational and they have an impact at the individual, community, and national level in the short- and long-term. There are still many gaps in knowledge regarding both the causes and consequences of chronic malnutrition, particularly when it comes to the interaction with agriculture and the environment, and understanding these gaps is important to addressing the burden of chronic malnutrition through evidence-based interventions. PMID:25988116
Synthesis of multiple shaped beam antenna patterns

NASA Technical Reports Server (NTRS)

Stutzman, W. L.; Coffey, E. L.

1973-01-01

Results are presented of research into the problem of finding an excitation of a given antenna such that the desired radiation pattern is approximated to within acceptable limits. This is to be done in such a fashion that boundary conditions involving hardware limitations may be inserted into the problem. The intended application is synthesis of multiple shaped beam antennas. Since this is perhaps the most difficult synthesis problem an antenna engineer is likely to encounter, the approach taken was to include as a by-product capability for synthesizing simpler patterns. The synthesis technique has been almost totally computerized. The class of antennas which may be synthesized with the computer program are those which may be represented as planar (continuous or discrete) current distributions. The technique is not limited in this sense and could indeed by extended to include, for example, the synthesis of conformal arrays or current distributions on the surface of reflectors. The antenna types which the program is set up to synthesize are: line source, rectangular aperture, circular aperture, linear array, rectangular array, and arbitrary planar array.
Application of Multiregressive Linear Models, Dynamic Kriging Models and Neural Network Models to Predictive Maintenance of Hydroelectric Power Systems

NASA Astrophysics Data System (ADS)

Lucifredi, A.; Mazzieri, C.; Rossi, M.

2000-05-01

Since the operational conditions of a hydroelectric unit can vary within a wide range, the monitoring system must be able to distinguish between the variations of the monitored variable caused by variations of the operation conditions and those due to arising and progressing of failures and misoperations. The paper aims to identify the best technique to be adopted for the monitoring system. Three different methods have been implemented and compared. Two of them use statistical techniques: the first, the linear multiple regression, expresses the monitored variable as a linear function of the process parameters (independent variables), while the second, the dynamic kriging technique, is a modified technique of multiple linear regression representing the monitored variable as a linear combination of the process variables in such a way as to minimize the variance of the estimate error. The third is based on neural networks. Tests have shown that the monitoring system based on the kriging technique is not affected by some problems common to the other two models e.g. the requirement of a large amount of data for their tuning, both for training the neural network and defining the optimum plane for the multiple regression, not only in the system starting phase but also after a trivial operation of maintenance involving the substitution of machinery components having a direct impact on the observed variable. Or, in addition, the necessity of different models to describe in a satisfactory way the different ranges of operation of the plant. The monitoring system based on the kriging statistical technique overrides the previous difficulties: it does not require a large amount of data to be tuned and is immediately operational: given two points, the third can be immediately estimated; in addition the model follows the system without adapting itself to it. The results of the experimentation performed seem to indicate that a model based on a neural network or on a linear multiple regression is not optimal, and that a different approach is necessary to reduce the amount of work during the learning phase using, when available, all the information stored during the initial phase of the plant to build the reference baseline, elaborating, if it is the case, the raw information available. A mixed approach using the kriging statistical technique and neural network techniques could optimise the result.
Is chloroquine chemoprophylaxis still effective to prevent low birth weight? Results of a study in Benin

PubMed Central

Denoeud, Lise; Fievet, Nadine; Aubouy, Agnès; Ayemonna, Paul; Kiniffo, Richard; Massougbodji, Achille; Cot, Michel

2007-01-01

Background In areas of stable transmission, malaria during pregnancy is associated with severe maternal and foetal outcomes, especially low birth weight (LBW). To prevent these complications, weekly chloroquine (CQ) chemoprophylaxis is now being replaced by intermittent preventive treatment with sulfadoxine-pyrimethamine in West Africa. The prevalence of placental malaria and its burden on LBW were assessed in Benin to evaluate the efficacy of weekly CQ chemoprophylaxis, prior to its replacement by intermittent preventive treatment. Methods In two maternity clinics in Ouidah, an observational study was conducted between April 2004 and April 2005. At each delivery, placental blood smears were examined for malaria infection and women were interviewed on their pregnancy history including CQ intake and dosage. CQ was measured in the urine of a sub-sample (n = 166). Multiple logistic and linear regression were used to assess factors associated with LBW and placental malaria. Results Among 1090 singleton live births, prevalence of placental malaria and LBW were 16% and 17% respectively. After adjustment, there was a non-significant association between placental malaria and LBW (adjusted OR = 1.43; P = 0.10). Multiple linear regression showed a positive association between placental malaria and decreased birth weight in primigravidae. More than 98% of the women reported regular chemoprophylaxis and CQ was detectable in 99% of urine samples. Protection from LBW was high in women reporting regular CQ prophylaxis, with a strong duration-effect relationship (test for linear trend: P < 0,001). Conclusion Despite high parasite resistance and limited effect on placental malaria, a CQ chemoprophylaxis taken at adequate doses showed to be still effective in reducing LBW in Benin. PMID:17341298
[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

Multiple-region directed functional connectivity based on phase delays.

PubMed

Goelman, Gadi; Dan, Rotem

2017-03-01

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Assessing NARCCAP climate model effects using spatial confidence regions.

PubMed

French, Joshua P; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.
Information processing in the primate visual system - An integrated systems perspective

NASA Technical Reports Server (NTRS)

Van Essen, David C.; Anderson, Charles H.; Felleman, Daniel J.

1992-01-01

The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.
Sandia Unstructured Triangle Tabular Interpolation Package v 0.1 beta

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

2013-09-24

The software interpolates tabular data, such as for equations of state, provided on an unstructured triangular grid. In particular, interpolation occurs in a two dimensional space by looking up the triangle in which the desired evaluation point resides and then performing a linear interpolation over the n-tuples associated with the nodes of the chosen triangle. The interface to the interpolation routines allows for automated conversion of units from those tabulated to the desired output units. when multiple tables are included in a data file, new tables may be generated by on-the-fly mixing of the provided tables
Comparison of Nonlinear Random Response Using Equivalent Linearization and Numerical Simulation

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2000-01-01

A recently developed finite-element-based equivalent linearization approach for the analysis of random vibrations of geometrically nonlinear multiple degree-of-freedom structures is validated. The validation is based on comparisons with results from a finite element based numerical simulation analysis using a numerical integration technique in physical coordinates. In particular, results for the case of a clamped-clamped beam are considered for an extensive load range to establish the limits of validity of the equivalent linearization approach.
A chaotic view of behavior change: a quantum leap for health promotion.

PubMed

Resnicow, Ken; Vaughan, Roger

2006-09-12

The study of health behavior change, including nutrition and physical activity behaviors, has been rooted in a cognitive-rational paradigm. Change is conceptualized as a linear, deterministic process where individuals weigh pros and cons, and at the point at which the benefits outweigh the cost change occurs. Consistent with this paradigm, the associated statistical models have almost exclusively assumed a linear relationship between psychosocial predictors and behavior. Such a perspective however, fails to account for non-linear, quantum influences on human thought and action. Consider why after years of false starts and failed attempts, a person succeeds at increasing their physical activity, eating healthier or losing weight. Or, why after years of success a person relapses. This paper discusses a competing view of health behavior change that was presented at the 2006 annual ISBNPA meeting in Boston. Rather than viewing behavior change from a linear perspective it can be viewed as a quantum event that can be understood through the lens of Chaos Theory and Complex Dynamic Systems. Key principles of Chaos Theory and Complex Dynamic Systems relevant to understanding health behavior change include: 1) Chaotic systems can be mathematically modeled but are nearly impossible to predict; 2) Chaotic systems are sensitive to initial conditions; 3) Complex Systems involve multiple component parts that interact in a nonlinear fashion; and 4) The results of Complex Systems are often greater than the sum of their parts. Accordingly, small changes in knowledge, attitude, efficacy, etc may dramatically alter motivation and behavioral outcomes. And the interaction of such variables can yield almost infinite potential patterns of motivation and behavior change. In the linear paradigm unaccounted for variance is generally relegated to the catch all "error" term, when in fact such "error" may represent the chaotic component of the process. The linear and chaotic paradigms are however, not mutually exclusive, as behavior change may include both chaotic and cognitive processes. Studies of addiction suggest that many decisions to change are quantum rather than planned events; motivation arrives as opposed to being planned. Moreover, changes made through quantum processes appear more enduring than those that involve more rational, planned processes. How such processes may apply to nutrition and physical activity behavior and related interventions merits examination.
Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696
Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.
SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994
Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.
Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.
A Direct Method for Fuel Optimal Maneuvers of Distributed Spacecraft in Multiple Flight Regimes

NASA Technical Reports Server (NTRS)

Hughes, Steven P.; Cooley, D. S.; Guzman, Jose J.

2005-01-01

We present a method to solve the impulsive minimum fuel maneuver problem for a distributed set of spacecraft. We develop the method assuming a non-linear dynamics model and parameterize the problem to allow the method to be applicable to multiple flight regimes including low-Earth orbits, highly-elliptic orbits (HEO), Lagrange point orbits, and interplanetary trajectories. Furthermore, the approach is not limited by the inter-spacecraft separation distances and is applicable to both small formations as well as large constellations. Semianalytical derivatives are derived for the changes in the total AV with respect to changes in the independent variables. We also apply a set of constraints to ensure that the fuel expenditure is equalized over the spacecraft in formation. We conclude with several examples and present optimal maneuver sequences for both a HE0 and libration point formation.
Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis.

PubMed

Falk, Carl F; Cai, Li

2016-06-01

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang's (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock-Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.
Three-dimensional finite elements for the analysis of soil contamination using a multiple-porosity approach

NASA Astrophysics Data System (ADS)

El-Zein, Abbas; Carter, John P.; Airey, David W.

2006-06-01

A three-dimensional finite-element model of contaminant migration in fissured clays or contaminated sand which includes multiple sources of non-equilibrium processes is proposed. The conceptual framework can accommodate a regular network of fissures in 1D, 2D or 3D and immobile solutions in the macro-pores of aggregated topsoils, as well as non-equilibrium sorption. A Galerkin weighted-residual statement for the three-dimensional form of the equations in the Laplace domain is formulated. Equations are discretized using linear and quadratic prism elements. The system of algebraic equations is solved in the Laplace domain and solution is inverted to the time domain numerically. The model is validated and its scope is illustrated through the analysis of three problems: a waste repository deeply buried in fissured clay, a storage tank leaking into sand and a sanitary landfill leaching into fissured clay over a sand aquifer.
Subranging scheme for SQUID sensors

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor)

2008-01-01

A readout scheme for measuring the output from a SQUID-based sensor-array using an improved subranging architecture that includes multiple resolution channels (such as a coarse resolution channel and a fine resolution channel). The scheme employs a flux sensing circuit with a sensing coil connected in series to multiple input coils, each input coil being coupled to a corresponding SQUID detection circuit having a high-resolution SQUID device with independent linearizing feedback. A two-resolution configuration (course and fine) is illustrated with a primary SQUID detection circuit for generating a fine readout, and a secondary SQUID detection circuit for generating a course readout, both having feedback current coupled to the respective SQUID devices via feedback/modulation coils. The primary and secondary SQUID detection circuits function and derive independent feedback. Thus, the SQUID devices may be monitored independently of each other (and read simultaneously) to dramatically increase slew rates and dynamic range.
Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.
Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
A linear-dendritic cationic vector for efficient DNA grasp and delivery.

PubMed

Yang, Bin; Sun, Yun-xia; Yi, Wen-jie; Yang, Juan; Liu, Chen-wei; Cheng, Han; Feng, Jun; Zhang, Xian-zheng; Zhuo, Ren-xi

2012-07-01

This paper presents an attempt to design an efficient and biocompatible cationic gene vector via structural optimization that favors the efficient utilization of amine groups for DNA condensation. To this end, a linear-dendritic block copolymer of methoxyl-poly(ethylene glycol)-dendritic polyglycerol-graft-tris(2-aminoethyl)amine (mPEG-DPG-g-TAEA) was prepared with specially designed multiple functions including strong DNA affinity, endosomal buffering and expected serum-tolerance. Based on the transfection in serum-free and serum-conditioned media, the influences of the polymer structures including the degree of polymerization of DPG and TAEA substitution degree were explored. As compared to polyethylenimine (M(w)=5 kDa) (PEI5k) with similar molecular weight and higher amine density, mPEG-DPG-g-TAEA displayed comparably high DNA affinity due to the special linear-dendritic architecture. Consequently, at very low N/P ratio, mPEG-DPG-g-TAEA vectors could mediate efficient in vitro luciferase expression at levels that are comparable with or even superior to the commercially available Lipofectamine™ 2000, while being apparently higher than PEI5k. The designed vectors exhibit considerably higher cell biocompatibility and better resistance against bovine serum albumin adsorption than PEI5k. The stability of the complexes on coincubation with heparin was found to be largely dependent on the polymer structure. As concluded from the comparative transfection study in the absence/presence of chloroquine, it is likely that the polycation itself could produce endosomal buffering. This linear-dendritic vector shows promising potential for the application of gene delivery. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
An extended car-following model considering random safety distance with different probabilities

NASA Astrophysics Data System (ADS)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.
[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Tuning diagonal components of static linear and first nonlinear polarizabilities of doped quantum dots by Gaussian white noise

NASA Astrophysics Data System (ADS)

Ganguly, Jayanta; Ghosh, Manas

2015-07-01

We investigate the modulation of diagonal components of static linear (αxx, αyy) and first nonlinear (βxxx, βyyy) polarizabilities of quantum dots by Gaussian white noise. Quantum dot is doped with impurity represented by a Gaussian potential and repulsive in nature. The study reveals the importance of mode of application of noise (additive/multiplicative) on the polarizability components. The doped system is further exposed to a static external electric field of given intensity. As important observation we have found that the strength of additive noise becomes unable to influence the polarizability components. However, the multiplicative noise influences them conspicuously and gives rise to additional interesting features. Multiplicative noise even enhances the magnitude of the polarizability components immensely. The present investigation deems importance in view of the fact that noise seriously affects the optical properties of doped quantum dot devices.
Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

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

NASA Astrophysics Data System (ADS)

Saulskiy, V. K.

2009-04-01

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

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.
Predictive inference for best linear combination of biomarkers subject to limits of detection.

PubMed

Coolen-Maturi, Tahani

2017-08-15

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Beam optical design of in-flight fragment separator for high-power heavy ion beam

NASA Astrophysics Data System (ADS)

Yun, C. C.; Kim, Mi-Jung; Kim, D. G.; Song, J. S.; Kim, Myeong-Jin; Kim, J. W.; Kim, J. R.; Wan, W.

2013-12-01

An in-flight fragment separator has been designed for the rare isotope science project (RISP) in Korea. A beam used for the design is 238U in the energy of 200 MeV/u with the maximum beam power of 400 kW. The use of high-power beam requires careful removal of the primary beam by pre-separator, for which its configuration was revised to employ four dipole magnets instead of two. Different configurations of the separator have been tested in search of optimal design in non-linear optics, which was complicated by the space needed for the target, beam dump and radiation shielding. Non-linear optical calculations have been carried out using GICOSY and COSY Infinity including the fringe fields of large-aperture quadrupole magnets. Correction of non-linear terms is made with multipole coils located inside the superconducting quadrupole magnets and by external multipole magnets. Beam simulations using LISE++ and MOCADI have been performed to consider the effects of multiple charge states of the primary and isotope beams produced at the target. Layout of the separator is being finalized, and detailed optics simulation will continue to refine its design.
Using polyacrylate-coated SPME fibers to quantify sorption of polar and ionic organic contaminants to dissolved organic carbon.

PubMed

Haftka, Joris J-H; Scherpenisse, Peter; Jonker, Michiel T O; Hermens, Joop L M

2013-05-07

A passive sampling method using polyacrylate-coated solid-phase microextraction (SPME) fibers was applied to determine sorption of polar and ionic organic contaminants to dissolved organic carbon (DOC). The tested contaminants included pharmaceuticals, industrial chemicals, hormones, and pesticides and represented neutral, anionic, and cationic structures. Prior to the passive sampler application, sorption of the chemicals to the fibers was characterized. This was needed in order to accurately translate concentrations measured in fibers to freely dissolved aqueous concentrations during the sorption tests with DOC. Sorption isotherms of neutral compounds to the fiber were linear, whereas isotherms of basic chemicals covered a nonlinear and a linear range. Sorption of acidic and basic compounds to the fiber was pH-dependent and was dominated by sorption of the neutral sorbate species. Fiber- and DOC-water partition coefficients of neutral compounds were both linearly related to octanol-water partition coefficients (log Kow). The results of this study show that polyacrylate fibers can be used to quantify sorption to DOC of neutral and ionic contaminants, having multiple functional groups and spanning a wide hydrophobicity range (log Kow = 2.5-7.5).
Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

PubMed

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.
The Integration of Teacher's Pedagogical Content Knowledge Components in Teaching Linear Equation

ERIC Educational Resources Information Center

Yusof, Yusminah Mohd.; Effandi, Zakaria

2015-01-01

This qualitative research aimed to explore the integration of the components of pedagogical content knowledge (PCK) in teaching Linear Equation with one unknown. For the purpose of the study, a single local case study with multiple participants was used. The selection of the participants was made based on various criteria: having more than 5 years…
The Effects of Multiple Linked Representations on Students' Learning of Linear Relationships

ERIC Educational Resources Information Center

Ozgun-Koca, S. Asli

2004-01-01

The focus of this study was on comparing three groups of Algebra I 9th-year students: one group using linked representation software, the second group using similar software but with semi-linked representations, and the control group in order to examine the effects on students' understanding of linear relationships. Data collection methods…
Hierarchical Linear Modeling (HLM): An Introduction to Key Concepts within Cross-Sectional and Growth Modeling Frameworks. Technical Report #1308

ERIC Educational Resources Information Center

Anderson, Daniel

2012-01-01

This manuscript provides an overview of hierarchical linear modeling (HLM), as part of a series of papers covering topics relevant to consumers of educational research. HLM is tremendously flexible, allowing researchers to specify relations across multiple "levels" of the educational system (e.g., students, classrooms, schools, etc.).…
Creating Discussions with Classroom Voting in Linear Algebra

ERIC Educational Resources Information Center

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…
Applying Agrep to r-NSA to solve multiple sequences approximate matching.

PubMed

Ni, Bing; Wong, Man-Hon; Lam, Chi-Fai David; Leung, Kwong-Sak

2014-01-01

This paper addresses the approximate matching problem in a database consisting of multiple DNA sequences, where the proposed approach applies Agrep to a new truncated suffix array, r-NSA. The construction time of the structure is linear to the database size, and the computations of indexing a substring in the structure are constant. The number of characters processed in applying Agrep is analysed theoretically, and the theoretical upper-bound can approximate closely the empirical number of characters, which is obtained through enumerating the characters in the actual structure built. Experiments are carried out using (synthetic) random DNA sequences, as well as (real) genome sequences including Hepatitis-B Virus and X-chromosome. Experimental results show that, compared to the straight-forward approach that applies Agrep to multiple sequences individually, the proposed approach solves the matching problem in much shorter time. The speed-up of our approach depends on the sequence patterns, and for highly similar homologous genome sequences, which are the common cases in real-life genomes, it can be up to several orders of magnitude.
Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.
All set! Evidence of simultaneous attentional control settings for multiple target colors.

PubMed

Irons, Jessica L; Folk, Charles L; Remington, Roger W

2012-06-01

Although models of visual search have often assumed that attention can only be set for a single feature or property at a time, recent studies have suggested that it may be possible to maintain more than one attentional control setting. The aim of the present study was to investigate whether spatial attention could be guided by multiple attentional control settings for color. In a standard spatial cueing task, participants searched for either of two colored targets accompanied by an irrelevantly colored distractor. Across five experiments, results consistently showed that nonpredictive cues matching either target color produced a significant spatial cueing effect, while irrelevantly colored cues did not. This was the case even when the target colors could not be linearly separated from irrelevantly cue colors in color space, suggesting that participants were not simply adopting one general color set that included both target colors. The results could not be explained by intertrial priming by previous targets, nor could they be explained by a single inhibitory set for the distractor color. Overall, the results are most consistent with the maintenance of multiple attentional control settings.
How does a planet excite multiple spiral arms?

NASA Astrophysics Data System (ADS)

Bae, Jaehan; Zhu, Zhaohuan

2018-01-01

Protoplanetary disk simulations show that a single planet excites multiple spiral arms in the background disk, potentially supported by the multi-armed spirals revealed with recent high-resolution observations in some disks. The existence of multiple spiral arms is of importance in many aspects. It is empirically found that the arm-to-arm separation increases as a function of the planetary mass, so one can use the morphology of observed spiral arms to infer the mass of unseen planets. In addition, a spiral arm opens a radial gap as it steepens into a shock, so when a planet excites multiple spiral arms it can open multiple gaps in the disk. Despite the important implications, however, the formation mechanism of multiple spiral arms has not been fully understood by far.In this talk, we explain how a planet excites multiple spiral arms. The gravitational potential of a planet can be decomposed into a Fourier series, a sum of individual azimuthal modes having different azimuthal wavenumbers. Using a linear wave theory, we first demonstrate that appropriate sets of Fourier decomposed waves can be in phase, raising a possibility that constructive interference among the waves can produce coherent structures - spiral arms. More than one spiral arm can form since such constructive interference can occur at different positions in the disk for different sets of waves. We then verify this hypothesis using a suite of two-dimensional hydrodynamic simulations. Finally, we present non-linear behavior in the formation of multiple spiral arms.
Multiplicity distributions of shower particles and target fragments in 84 Kr 36-emulsion interactions at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

Singh, M. K.; Soma, A. K.; Pathak, Ramji; Singh, V.

2014-03-01

This article focuses on multiplicity distributions of shower particles and target fragments for interaction of 84 Kr 36 with NIKFI BR-2 nuclear emulsion target at kinetic energy of 1 GeV per nucleon. Experimental multiplicity distributions of shower particles, grey particles, black particles and heavily ionization particles are well described by multi-component Erlang distribution of multi-source thermal model. We have observed a linear correlation in multiplicities for the above mentioned particles or fragments. Further experimental studies have shown a saturation phenomenon in shower particle multiplicity with the increase of target fragment multiplicity.
Laser-Induced Linear-Field Particle Acceleration in Free Space

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

Wong, Liang Jie; Hong, Kyung -Han; Carbajo, Sergio

Linear-field particle acceleration in free space (which is distinct from geometries like the linac that requires components in the vicinity of the particle) has been studied for over 20 years, and its ability to eventually produce high-quality, high energy multi-particle bunches has remained a subject of great interest. Arguments can certainly be made that linear-field particle acceleration in free space is very doubtful given that first-order electron-photon interactions are forbidden in free space. Nevertheless, we chose to develop an accurate and truly predictive theoretical formalism to explore this remote possibility when intense, few-cycle electromagnetic pulses are used in a computationalmore » experiment. The formalism includes exact treatment of Maxwell’s equations and exact treatment of the interaction among the multiple individual particles at near and far field. Several surprising results emerge. We find that electrons interacting with intense laser pulses in free space are capable of gaining substantial amounts of energy that scale linearly with the feld amplitude. For example, 30keV electrons (2.5% energy spread) are accelerated to 61MeV (0.5% spread) and to 205MeV (0.25% spread) using 250 mJ and 2.5J lasers respectively. Furthermore, these findings carry important implications for our understanding of ultrafast electron-photon interactions in strong fields.« less
Laser-Induced Linear-Field Particle Acceleration in Free Space

DOE PAGES

Wong, Liang Jie; Hong, Kyung -Han; Carbajo, Sergio; ...

2017-09-11

Linear-field particle acceleration in free space (which is distinct from geometries like the linac that requires components in the vicinity of the particle) has been studied for over 20 years, and its ability to eventually produce high-quality, high energy multi-particle bunches has remained a subject of great interest. Arguments can certainly be made that linear-field particle acceleration in free space is very doubtful given that first-order electron-photon interactions are forbidden in free space. Nevertheless, we chose to develop an accurate and truly predictive theoretical formalism to explore this remote possibility when intense, few-cycle electromagnetic pulses are used in a computationalmore » experiment. The formalism includes exact treatment of Maxwell’s equations and exact treatment of the interaction among the multiple individual particles at near and far field. Several surprising results emerge. We find that electrons interacting with intense laser pulses in free space are capable of gaining substantial amounts of energy that scale linearly with the feld amplitude. For example, 30keV electrons (2.5% energy spread) are accelerated to 61MeV (0.5% spread) and to 205MeV (0.25% spread) using 250 mJ and 2.5J lasers respectively. Furthermore, these findings carry important implications for our understanding of ultrafast electron-photon interactions in strong fields.« less
Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

A Multi-Trait, Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature, Fatness and Reproduction in Beef Cattle

PubMed Central

Bolormaa, Sunduimijid; Pryce, Jennie E.; Reverter, Antonio; Zhang, Yuandan; Barendse, William; Kemper, Kathryn; Tier, Bruce; Savin, Keith; Hayes, Ben J.; Goddard, Michael E.

2014-01-01

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t'V−1t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups. PMID:24675618
Multiple Streaming and the Probability Distribution of Density in Redshift Space

NASA Astrophysics Data System (ADS)

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

2000-07-01

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

PubMed Central

Hoppe, Adam D.; Scott, Brandon L.; Welliver, Timothy P.; Straight, Samuel W.; Swanson, Joel A.

2013-01-01

Fluorescence Resonance Energy Transfer (FRET) microscopy has emerged as a powerful tool to visualize nanoscale protein-protein interactions while capturing their microscale organization and millisecond dynamics. Recently, FRET microscopy was extended to imaging of multiple donor-acceptor pairs, thereby enabling visualization of multiple biochemical events within a single living cell. These methods require numerous equations that must be defined on a case-by-case basis. Here, we present a universal multispectral microscopy method (N-Way FRET) to enable quantitative imaging for any number of interacting and non-interacting FRET pairs. This approach redefines linear unmixing to incorporate the excitation and emission couplings created by FRET, which cannot be accounted for in conventional linear unmixing. Experiments on a three-fluorophore system using blue, yellow and red fluorescent proteins validate the method in living cells. In addition, we propose a simple linear algebra scheme for error propagation from input data to estimate the uncertainty in the computed FRET images. We demonstrate the strength of this approach by monitoring the oligomerization of three FP-tagged HIV Gag proteins whose tight association in the viral capsid is readily observed. Replacement of one FP-Gag molecule with a lipid raft-targeted FP allowed direct observation of Gag oligomerization with no association between FP-Gag and raft-targeted FP. The N-Way FRET method provides a new toolbox for capturing multiple molecular processes with high spatial and temporal resolution in living cells. PMID:23762252
Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data

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

Kim, Yangho; Lee, Byung-Kook, E-mail: bklee@sch.ac.kr

Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008-2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium andmore » mercury, the difference in eGFR levels associated with doubling of blood lead were -2.624 mL/min per 1.73 m Superscript-Two (95% CI: -3.803 to -1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was -3.835 mL/min per 1.73 m Superscript-Two (95% CI: -5.730 to -1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 {mu}g/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.« less
A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.

PubMed

De Silva, Anurika Priyanjali; Moreno-Betancur, Margarita; De Livera, Alysha Madhu; Lee, Katherine Jane; Simpson, Julie Anne

2017-07-25

Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies. We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems. The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one. We recommend the use of FCS or MVNI in a similar longitudinal setting, and when encountering convergence issues due to a large number of time points or variables with missing values, the two-fold FCS with exploration of a suitable time window.
WATER VAPOR IN NEARBY INFRARED GALAXIES AS PROBED BY HERSCHEL

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

Yang Chentao; Gao Yu; Liu Daizhong

2013-07-10

We report the first systematic study of the submillimeter water vapor rotational emission lines in infrared (IR) galaxies based on the Fourier Transform Spectrometer (FTS) data of Herschel SPIRE. Among the 176 galaxies with publicly available FTS data, 45 have at least one H{sub 2}O emission line detected. The H{sub 2}O line luminosities range from {approx}1 Multiplication-Sign 10{sup 5} L{sub Sun} to {approx}5 Multiplication-Sign 10{sup 7} L{sub Sun} while the total IR luminosities (L{sub IR}) have a similar spread ({approx}1-300 Multiplication-Sign 10{sup 10} L{sub Sun }). In addition, emission lines of H{sub 2}O{sup +} and H{sub 2}{sup 18}O are alsomore » detected. H{sub 2}O is found, for most galaxies, to be the strongest molecular emitter after CO in FTS spectra. The luminosity of the five most important H{sub 2}O lines is near-linearly correlated with L{sub IR}, regardless of whether or not strong active galactic nucleus signature is present. However, the luminosity of H{sub 2}O(2{sub 11}-2{sub 02}) and H{sub 2}O(2{sub 20}-2{sub 11}) appears to increase slightly faster than linear with L{sub IR}. Although the slope turns out to be slightly steeper when z {approx} 2-4 ULIRGs are included, the correlation is still closely linear. We find that L{sub H{sub 2O}}/L{sub IR} decreases with increasing f{sub 25}/f{sub 60}, but see no dependence on f{sub 60}/f{sub 100}, possibly indicating that very warm dust contributes little to the excitation of the submillimeter H{sub 2}O lines. The average spectral line energy distribution (SLED) of the entire sample is consistent with individual SLEDs and the IR pumping plus collisional excitation model, showing that the strongest lines are H{sub 2}O(2{sub 02}-1{sub 11}) and H{sub 2}O(3{sub 21}-3{sub 12}).« less
Risk factors for development of multiple-class resistance to Streptococcus pneumoniae Strains in Belgium over a 10-year period: antimicrobial consumption, population density, and geographic location.

PubMed

Van Eldere, Johan; Mera, Robertino M; Miller, Linda A; Poupard, James A; Amrine-Madsen, Heather

2007-10-01

We investigated the impact of the usage of antibiotics in ambulatory patients in Belgium in 147 defined geographical circumscriptions and at the individual isolate level. The study included 14,448 Streptococcus pneumoniae strains collected by the Belgium national reference lab from 1994 to 2004. Additional risk factors for resistance, such as population density/structure and day care attendance, were investigated for the same time-space window. A statistical model that included resistance to two or more antimicrobial classes offered the best fit for measuring the changes in nonsusceptibility to penicillin, macrolides, and tetracycline over time and place in Belgium. Analysis at the geographic level identified antimicrobial consumption with a 1-year lag (0.5% increase per additional defined daily dose) and population density as independent predictors of multiple resistance. Independent risk factors at the isolate level were age (odds ratio [OR], 1.55 for children aged <5 years), population density (7% increase in multiple resistance per 100 inhabitants/km(2)), conjugate 7-valent vaccine serotype (OR, 14.3), location (OR, 1.55 for regions bordering high-resistance France), and isolate source (OR, 1.54 for ear isolates). The expansion of multiple-resistant strains explains most of the overall twofold increase and subsequent decrease in single antimicrobial resistance between 1994 and 2004. We conclude that factors in addition to antibiotic use, such as high population density and proximity to high-resistance regions, favor multiple resistance. Regional resistance rates are not linearly related to actual antibiotic use but are linked to past antibiotic use plus a combination of demographic and geographic factors.
Clinically Practical Approach for Screening of Low Muscularity Using Electronic Linear Measures on Computed Tomography Images in Critically Ill Patients.

PubMed

Avrutin, Egor; Moisey, Lesley L; Zhang, Roselyn; Khattab, Jenna; Todd, Emma; Premji, Tahira; Kozar, Rosemary; Heyland, Daren K; Mourtzakis, Marina

2017-12-06

Computed tomography (CT) scans performed during routine hospital care offer the opportunity to quantify skeletal muscle and predict mortality and morbidity in intensive care unit (ICU) patients. Existing methods of muscle cross-sectional area (CSA) quantification require specialized software, training, and time commitment that may not be feasible in a clinical setting. In this article, we explore a new screening method to identify patients with low muscle mass. We analyzed 145 scans of elderly ICU patients (≥65 years old) using a combination of measures obtained with a digital ruler, commonly found on hospital radiological software. The psoas and paraspinal muscle groups at the level of the third lumbar vertebra (L3) were evaluated by using 2 linear measures each and compared with an established method of CT image analysis of total muscle CSA in the L3 region. There was a strong association between linear measures of psoas and paraspinal muscle groups and total L3 muscle CSA (R 2 = 0.745, P < 0.001). Linear measures, age, and sex were included as covariates in a multiple logistic regression to predict those with low muscle mass; receiver operating characteristic (ROC) area under the curve (AUC) of the combined psoas and paraspinal linear index model was 0.920. Intraclass correlation coefficients (ICCs) were used to evaluate intrarater and interrater reliability, resulting in scores of 0.979 (95% CI: 0.940-0.992) and 0.937 (95% CI: 0.828-0.978), respectively. A digital ruler can reliably predict L3 muscle CSA, and these linear measures may be used to identify critically ill patients with low muscularity who are at risk for worse clinical outcomes. © 2017 American Society for Parenteral and Enteral Nutrition.
ADME evaluation in drug discovery. 1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs.

PubMed

Hou, Tingjun; Xu, Xiaojie

2002-12-01

In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the models were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statistical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent-accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. Moreover, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predictions for the two external sets with 37 diverse compounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.
Ultrasonic Fluid Quality Sensor System

DOEpatents

Gomm, Tyler J.; Kraft, Nancy C.; Phelps, Larry D.; Taylor, Steven C.

2003-10-21

A system for determining the composition of a multiple-component fluid and for determining linear flow comprising at least one sing-around circuit that determines the velocity of a signal in the multiple-component fluid and that is correlatable to a database for the multiple-component fluid. A system for determining flow uses two of the inventive circuits, one of which is set at an angle that is not perpendicular to the direction of flow.
Ultrasonic fluid quality sensor system

DOEpatents

Gomm, Tyler J.; Kraft, Nancy C.; Phelps, Larry D.; Taylor, Steven C.

2002-10-08

A system for determining the composition of a multiple-component fluid and for determining linear flow comprising at least one sing-around circuit that determines the velocity of a signal in the multiple-component fluid and that is correlatable to a database for the multiple-component fluid. A system for determining flow uses two of the inventive circuits, one of which is set at an angle that is not perpendicular to the direction of flow.
Serum Folate Shows an Inverse Association with Blood Pressure in a Cohort of Chinese Women of Childbearing Age: A Cross-Sectional Study

PubMed Central

Shen, Minxue; Tan, Hongzhuan; Zhou, Shujin; Retnakaran, Ravi; Smith, Graeme N.; Davidge, Sandra T.; Trasler, Jacquetta; Walker, Mark C.; Wen, Shi Wu

2016-01-01

Background It has been reported that higher folate intake from food and supplementation is associated with decreased blood pressure (BP). The association between serum folate concentration and BP has been examined in few studies. We aim to examine the association between serum folate and BP levels in a cohort of young Chinese women. Methods We used the baseline data from a pre-conception cohort of women of childbearing age in Liuyang, China, for this study. Demographic data were collected by structured interview. Serum folate concentration was measured by immunoassay, and homocysteine, blood glucose, triglyceride and total cholesterol were measured through standardized clinical procedures. Multiple linear regression and principal component regression model were applied in the analysis. Results A total of 1,532 healthy normotensive non-pregnant women were included in the final analysis. The mean concentration of serum folate was 7.5 ± 5.4 nmol/L and 55% of the women presented with folate deficiency (< 6.8 nmol/L). Multiple linear regression and principal component regression showed that serum folate levels were inversely associated with systolic and diastolic BP, after adjusting for demographic, anthropometric, and biochemical factors. Conclusions Serum folate is inversely associated with BP in non-pregnant women of childbearing age with high prevalence of folate deficiency. PMID:27182603
Factors associated to clinical learning in nursing students in primary health care: an analytical cross-sectional study

PubMed Central

Serrano-Gallardo, Pilar; Martínez-Marcos, Mercedes; Espejo-Matorrales, Flora; Arakawa, Tiemi; Magnabosco, Gabriela Tavares; Pinto, Ione Carvalho

2016-01-01

ABSTRACT Objective: to identify the students' perception about the quality of clinical placements and asses the influence of the different tutoring processes in clinical learning. Methods: analytical cross-sectional study on second and third year nursing students (n=122) about clinical learning in primary health care. The Clinical Placement Evaluation Tool and a synthetic index of attitudes and skills were computed to give scores to the clinical learning (scale 0-10). Univariate, bivariate and multivariate (multiple linear regression) analyses were performed. Results: the response rate was 91.8%. The most commonly identified tutoring process was "preceptor-professor" (45.2%). The clinical placement was assessed as "optimal" by 55.1%, relationship with team-preceptor was considered good by 80.4% of the cases and the average grade for clinical learning was 7.89. The multiple linear regression model with more explanatory capacity included the variables "Academic year" (beta coefficient = 1.042 for third-year students), "Primary Health Care Area (PHC)" (beta coefficient = 0.308 for Area B) and "Clinical placement perception" (beta coefficient = - 0.204 for a suboptimal perception). Conclusions: timeframe within the academic program, location and clinical placement perception were associated with students' clinical learning. Students' perceptions of setting quality were positive and a good team-preceptor relationship is a matter of relevance. PMID:27627124
Overview of Recent Alcator C-Mod Highlights

NASA Astrophysics Data System (ADS)

Marmar, Earl; C-Mod Team

2013-10-01

Analysis and modeling of recent C-Mod experiments has yielded significant results across multiple research topics. I-mode provides routine access to high confinement plasma (H98 up to 1.2) in quasi-steady state, without large ELMs; pedestal pressure and impurity transport are regulated by short-wavelength EM waves, and core turbulence is reduced. Multi-channel transport is being investigated in Ohmic and RF-heated plasmas, using advanced diagnostics to validate non-linear gyrokinetic simulations. Results from the new field-aligned ICRF antenna, including significantly reduced high-Z metal impurity contamination, and greatly improved load-tolerance, are being understood through antenna-plasma modeling. Reduced LHCD efficiency at high density correlates with parametric decay and enhanced edge absorption. Strong flow drive and edge turbulence suppression are seen from LHRF, providing new approaches for plasma control. Plasma density profiles directly in front of the LH coupler show non-linear modifications, with important consequences for wave coupling. Disruption-mitigation experiments using massive gas injection at multiple toroidal locations show unexpected results, with potentially significant implications for ITER. First results from a novel accelerator-based PMI diagnostic are presented. What would be the world's first actively-heated high-temperature advanced tungsten divertor is designed and ready for construction. Conceptual designs are being developed for an ultra-advanced divertor facility, Alcator DX, to attack key FNSF and DEMO heat-flux challenges integrated with a high-performance core. Supported by USDOE.
Internal and external environmental factors affecting the performance of hospital-based home nursing care.

PubMed

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.
Performance metric comparison study for non-magnetic bi-stable energy harvesters

NASA Astrophysics Data System (ADS)

Udani, Janav P.; Wrigley, Cailin; Arrieta, Andres F.

2017-04-01

Energy harvesting employing non-linear systems offers considerable advantages over linear systems given the broadband resonant response which is favorable for applications involving diverse input vibrations. In this respect, the rich dynamics of bi-stable systems present a promising means for harvesting vibrational energy from ambient sources. Harvesters deriving their bi-stability from thermally induced stresses as opposed to magnetic forces are receiving significant attention as it reduces the need for ancillary components and allows for bio- compatible constructions. However, the design of these bi-stable harvesters still requires further optimization to completely exploit the dynamic behavior of these systems. This study presents a comparison of the harvesting capabilities of non-magnetic, bi-stable composite laminates under variations in the design parameters as evaluated utilizing established power metrics. Energy output characteristics of two bi-stable composite laminate plates with a piezoelectric patch bonded on the top surface are experimentally investigated for variations in the thickness ratio and inertial mass positions for multiple load conditions. A particular design configuration is found to perform better over the entire range of testing conditions which include single and multiple frequency excitation, thus indicating that design optimization over the geometry of the harvester yields robust performance. The experimental analysis further highlights the need for appropriate design guidelines for optimization and holistic performance metrics to account for the range of operational conditions.
Estimation in Linear Systems Featuring Correlated Uncertain Observations Coming from Multiple Sensors

NASA Astrophysics Data System (ADS)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2009-08-01

In this paper, the state least-squares linear estimation problem from correlated uncertain observations coming from multiple sensors is addressed. It is assumed that, at each sensor, the state is measured in the presence of additive white noise and that the uncertainty in the observations is characterized by a set of Bernoulli random variables which are only correlated at consecutive time instants. Assuming that the statistical properties of such variables are not necessarily the same for all the sensors, a recursive filtering algorithm is proposed, and the performance of the estimators is illustrated by a numerical simulation example wherein a signal is estimated from correlated uncertain observations coming from two sensors with different uncertainty characteristics.
Linearly polarized vector modes: enabling MIMO-free mode-division multiplexing.

PubMed

Wang, Lixian; Nejad, Reza Mirzaei; Corsi, Alessandro; Lin, Jiachuan; Messaddeq, Younès; Rusch, Leslie; LaRochelle, Sophie

2017-05-15

We experimentally investigate mode-division multiplexing in an elliptical ring core fiber (ERCF) that supports linearly polarized vector modes (LPV). Characterization show that the ERCF exhibits good polarization maintaining properties over eight LPV modes with effective index difference larger than 1 × 10 -4 . The ERCF further displays stable mode power and polarization extinction ratio when subjected to external perturbations. Crosstalk between the LPV modes, after propagating through 0.9 km ERCF, is below -14 dB. By using six LPV modes as independent data channels, we achieved the transmission of 32 Gbaud QPSK over 0.9 km ERCF without any multiple-input-multiple-output (MIMO) or polarization-division multiplexing (PDM) signal processing.
Optical computing using optical flip-flops in Fourier processors: use in matrix multiplication and discrete linear transforms.

PubMed

Ando, S; Sekine, S; Mita, M; Katsuo, S

1989-12-15

An architecture and the algorithms for matrix multiplication using optical flip-flops (OFFs) in optical processors are proposed based on residue arithmetic. The proposed system is capable of processing all elements of matrices in parallel utilizing the information retrieving ability of optical Fourier processors. The employment of OFFs enables bidirectional data flow leading to a simpler architecture and the burden of residue-to-decimal (or residue-to-binary) conversion to operation time can be largely reduced by processing all elements in parallel. The calculated characteristics of operation time suggest a promising use of the system in a real time 2-D linear transform.
Highly stable multi-wavelength erbium-doped fiber linear laser based on modal interference

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Nonlinear Diophantine equation 11 x +13 y = z 2

NASA Astrophysics Data System (ADS)

Sugandha, A.; Tripena, A.; Prabowo, A.; Sukono, F.

2018-03-01

This research aims to obtaining the solutions (if any) from the Non Linear Diophantine equation of 11 x + 13 y = z 2. There are 3 possibilities to obtain the solutions (if any) from the Non Linear Diophantine equation, namely single, multiple, and no solution. This research is conducted in two stages: (1) by utilizing simulation to obtain the solutions (if any) from the Non Linear Diophantine equation of 11 x + 13 y = z 2 and (2) by utilizing congruency theory with its characteristics proven that the Non Linear Diophantine equation has no solution for non negative whole numbers (integers) of x, y, z.
Dynamic Measurement: The Crossroad of Area and Multiplication

ERIC Educational Resources Information Center

Panorkou, Nicole

2017-01-01

In this exploratory study, our goal was to engage students in dynamic experiences of area as a continuous quantity that can be measured by multiplicatively composing two linear measures (lengths), an approach we refer to as 'dynamic measurement,' or DYME. In this paper, we present the learning trajectory constructed from two cycles of teaching…
Goal programming for land use planning.

Treesearch

Enoch F. Bell

1976-01-01

A simple transformation of the linear programing model used in land use planning to a goal programing model allows the multiple goals implied by multiple use management to be explicitly recognized. This report outlines the procedure for accomplishing the transformation and discusses problems with use of goal programing. Of particular concern are the expert opinions...
On the Convenience of Using the Complete Linearization Method in Modelling the BLR of AGN

NASA Astrophysics Data System (ADS)

Patriarchi, P.; Perinotto, M.

The Complete Linearization Method (Mihalas, 1978) consists in the determination of the radiation field (at a set of frequency points), atomic level populations, temperature, electron density etc., by resolving the system of radiative transfer, thermal equilibrium, statistical equilibrium equations simultaneously and self-consistently. Since the system is not linear, it must be solved by iteration after linearization, using a perturbative method, starting from an initial guess solution. Of course the Complete Linearization Method is more time consuming than the previous one. But how great can this disadvantage be in the age of supercomputers? It is possible to approximately evaluate the CPU time needed to run a model by computing the number of multiplications necessary to solve the system.
HYDRORECESSION: A toolbox for streamflow recession analysis

NASA Astrophysics Data System (ADS)

Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.
Zeroth-order design report for the next linear collider. Volume 2

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

Raubenheimer, T.O.

This Zeroth-Order Design Report (ZDR) for the Next Linear Collider (NLC) has been completed as a feasibility study for a TeV-scale linear collider that incorporates a room-temperature accelerator powered by rf microwaves at 11.424 GHz--similar to that presently used in the SLC, but at four times the rf frequency. The purpose of this study is to examine the complete systems of such a collider, to understand how the parts fit together, and to make certain that every required piece has been included. The ``design`` presented here is not fully engineered in any sense, but to be assured that the NLCmore » can be built, attention has been given to a number of critical components and issues that present special challenges. More engineering and development of a number of mechanical and electrical systems remain to be done, but the conclusion of this study is that indeed the NLC is technically feasible and can be expected to reach the performance levels required to perform research at the TeV energy scale. Volume II covers the following: collimation systems; IP switch and big bend; final focus; the interaction region; multiple bunch issues; control systems; instrumentation; machine protection systems; NLC reliability considerations; NLC conventional facilities. Also included are four appendices on the following topics: An RF power source upgrade to the NLC; a second interaction region for gamma-gamma, gamma-electron; ground motion: theory and measurement; and beam-based feedback: theory and implementation.« less
Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

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

2013-01-01

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

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.
Shared Dosimetry Error in Epidemiological Dose-Response Analyses

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

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

2015-03-23

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

PubMed Central

2014-01-01

Background This study aimed to clarify how community mental healthcare systems can be improved. Methods We included 79 schizophrenic patients, aged 20 to 80 years, residing in the Tokyo metropolitan area who regularly visited rehabilitation facilities offering assistance to psychiatric patients and were receiving treatment on an outpatient basis. No subjects had severe cognitive disorders or were taking medication with side effects that could prevent the completion of questionnaires. Questionnaires included items related to quality of life, self-efficacy, self-esteem, psychosis based on the Behavior and Symptom Identification Scale, health locus of control, and socio-demographic factors. We performed multiple linear regression analysis with quality of life as the dependent variable and, based on covariance structural analysis, evaluated the goodness of fit of the resulting structural equations models. Results Self-efficacy, self-esteem, and degree of psychosis significantly impacted quality of life. Marital status, age, and types of medications also influenced quality of life. Multiple linear regression analysis revealed psychiatric symptoms (Behavior and Symptom Identification Scale-32 [daily living and role functioning] (Beta = −0.537, p < 0.001) and self-efficacy (Beta = 0.249, p < 0.05) to be predictors of total quality of life score. Based on covariance structural analysis, the resulting model was found to exhibit reasonable goodness of fit. Conclusions Self-efficacy had an especially strong and direct impact on QOL. Therefore, it is important to provide more positive feedback to patients, provide social skills training based on cognitive behavioral therapy, and engage patients in role playing to improve self-efficacy and self-concept. PMID:25101143
Ghrelin level negatively predicts quality of life in obese women.

PubMed

Lu, P H; Song, Y L; Hsu, C H

2017-02-01

A cross-sectional cohort study was conducted to investigate whether ghrelin level in obese women predicts the quality of life (QOL). A total of 307 subjects fulfilled the criteria: (1) age between 20 and 65 years old, (2) body mass index ≥27 kg/m 2 (3) waist circumference ≥80 cm were enrolled in the study. All subjects were assigned to one of the plasma ghrelin level categories according to the quartiles. The median of age and BMI of the 307 obese women were 45 ± 18 years and 29.9 ± 4.1 kg/m 2 , respectively. The main outcome evaluated is the associations of plasma ghrelin level and QOL, which were evaluated using multiple linear regression analysis. Results of linear trend test show significant statistical difference in plasma lipoproteins (triglyceride, cholesterol, HDL-cholestero and LDL-cholesterol = and levels of obesity-related hormone peptides, including leptin, adiponectin, insulin among quartiles of ghrelin. Multiple liner regression analysis of serum obesity-related hormone peptide level and QOL using stepwise method shows ghrelin concentration was the only predictor of QOL, including PCS-12 level (β = -0.18, p = 0.001), MCS-12 level (β = -0.14, p = 0.009), WHOQOL-BREF scores: physical (β = -0.13, p = 0.03), psychological (β = -0.16, p = 0.007), social (β = -0.21, p = < 0.001), and environmental (β = -0.22, p = <0.001), after adjusting other factors for obese female subjects. This study demonstrated that ghrelin concentration is strongly associated with QOL level among obese women. Hence, ghrelin concentration might be a valuable marker to be monitored in obese women.
Longitudinal erythronychia: individual or multiple linear red bands of the nail plate: a review of clinical features and associated conditions.

PubMed

Cohen, Philip R

2011-08-01

Longitudinal erythronychia is a linear red band on the nail plate that originates at the proximal nail fold, traverses the lunula, and extends to the free edge of the nail plate. Longitudinal erythronychia is classified based upon the number of nails affected and the number of red streaks present on each nail as follows: type Ia (monodactylous - single band), type Ib (monodactylous - bifid bands), type IIa (polydactylous - single band), and type IIb (polydactylous - multiple bands). Associated morphologic findings that can be present at the distal tip of the nail with longitudinal erythronychia include fragility, onycholysis, splinter hemorrhage, splitting, subungual keratosis, thinning, and V-shaped nick. Some patients with longitudinal erythronychia seek medical evaluation because of pain in the associated distal digit; however, the linear red nail plate dyschromia is often asymptomatic and the individual is concerned about the cosmetic appearance or distal nail fragility. Longitudinal erythronychia can be a clinical manifestation of an underlying local or systemic condition. Benign tumors (glomus tumor, onychopapilloma, and warty dyskeratoma), malignant neoplasms (malignant melanoma and squamous cell carcinoma), and other conditions (hemiplegia and postsurgical scar) can be associated with monodactylous longitudinal erythronychia or it may be idiopathic or the initial stage of polydactylous longitudinal erythronychia-associated systemic conditions. Polydactylous longitudinal erythronychia is most commonly reported in patients with Darier disease (keratosis follicularis); other associated conditions include acantholytic dyskeratotic epidermal nevus, acantholytic epidermolysis bullosa, acrokeratosis verruciformis of Hopf, amyloidosis, graft-versus-host disease, lichen planus, and pseudobulbar syndrome. Polydactylous longitudinal erythronychia has also been observed as an idiopathic finding. Biopsy of the nail matrix and nail bed may be necessary to establish the diagnosis of a longitudinal erythronychia-associated condition. Indeed, a biopsy should be seriously considered in patients aged more than 50 years who present with a monodactylous longitudinal red band to exclude squamous cell carcinoma. Treatment of longitudinal erythronychia depends on the etiology. For patients with longitudinal erythronychia-associated discomfort or severe nail splitting, a surgical excision may provide not only the underlying diagnosis of the nail dyschromia, but also relief of related symptoms.
Operation in the turbulent jet field of a linear array of multiple rectangular jets using a two-dimensional jet (Variation of mean velocity field)

NASA Astrophysics Data System (ADS)

Fujita, Shigetaka; Harima, Takashi

2016-03-01

The mean flowfield of a linear array of multiple rectangular jets run through transversely with a two-dimensional jet, has been investigated, experimentally. The object of this experiment is to operate both the velocity scale and the length scale of the multiple rectangular jets using a two-dimensional jet. The reason of the adoption of this nozzle exit shape was caused by the reports of authors in which the cruciform nozzle promoted the inward secondary flows strongly on both the two jet axes. Aspect ratio of the rectangular nozzle used in this experiment was 12.5. Reynolds number based on the nozzle width d and the exit mean velocity Ue (≅ 39 m / s) was kept constant 25000. Longitudinal mean velocity was measured using an X-array Hot-Wire Probe (lh = 3.1 μm in diameter, dh = 0.6 mm effective length : dh / lh = 194) operated by the linearized constant temperature anemometers (DANTEC), and the spanwise and the lateral mean velocities were measured using a yaw meter. The signals from the anemometers were passed through the low-pass filters and sampled using A.D. converter. The processing of the signals was made by a personal computer. Acquisition time of the signals was usually 60 seconds. From this experiment, it was revealed that the magnitude of the inward secondary flows on both the y and z axes in the upstream region of the present jet was promoted by a two-dimensional jet which run through transversely perpendicular to the multiple rectangular jets, therefore the potential core length on the x axis of the present jet extended 2.3 times longer than that of the multiple rectangular jets, and the half-velocity width on the rectangular jet axis of the present jet was suppressed 41% shorter compared with that of the multiple rectangular jets.
Multiple epitope presentation and surface density control enabled by chemoselective immobilization lead to enhanced performance in IgE-binding fingerprinting on peptide microarrays.

PubMed

Gori, Alessandro; Cretich, Marina; Vanna, Renzo; Sola, Laura; Gagni, Paola; Bruni, Giulia; Liprino, Marta; Gramatica, Furio; Burastero, Samuele; Chiari, Marcella

2017-08-29

Multiple ligand presentation is a powerful strategy to enhance the affinity of a probe for its corresponding target. A promising application of this concept lies in the analytical field, where surface immobilized probes interact with their corresponding targets in the context of complex biological samples. Here we investigate the effect of multiple epitope presentation (MEP) in the challenging context of IgE-detection in serum samples using peptide microarrays, and evaluate the influence of probes surface density on the assay results. Using the milk allergen alpha-lactalbumin as a model, we have synthesized three immunoreactive epitope sequences in a linear, branched and tandem form and exploited a chemoselective click strategy (CuAAC) for their immobilization on the surface of two biosensors, a microarray and an SPR chip both modified with the same clickable polymeric coating. We first demonstrated that a fine tuning of the surface peptide density plays a crucial role to fully exploit the potential of oriented and multiple peptide display. We then compared the three multiple epitope presentations in a microarray assay using sera samples from milk allergic patients, confirming that a multiple presentation, in particular that of the tandem construct, allows for a more efficient characterization of IgE-binding fingerprints at a statistically significant level. To gain insights on the binding parameters that characterize antibody/epitopes affinity, we selected the most reactive epitope of the series (LAC1) and performed a Surface Plasmon Resonance Imaging (SPRi) analysis comparing different epitope architectures (linear versus branched versus tandem). We demonstrated that the tandem peptide provides an approximately twofold increased binding capacity with respect to the linear and branched peptides, that could be attributed to a lower rate of dissociation (K d ). Copyright © 2017 Elsevier B.V. All rights reserved.
An Empirical Comparison of Five Linear Equating Methods for the NEAT Design

ERIC Educational Resources Information Center

Suh, Youngsuk; Mroch, Andrew A.; Kane, Michael T.; Ripkey, Douglas R.

2009-01-01

In this study, a data base containing the responses of 40,000 candidates to 90 multiple-choice questions was used to mimic data sets for 50-item tests under the "nonequivalent groups with anchor test" (NEAT) design. Using these smaller data sets, we evaluated the performance of five linear equating methods for the NEAT design with five levels of…
Building "e-rater"® Scoring Models Using Machine Learning Methods. Research Report. ETS RR-16-04

ERIC Educational Resources Information Center

Chen, Jing; Fife, James H.; Bejar, Isaac I.; Rupp, André A.

2016-01-01

The "e-rater"® automated scoring engine used at Educational Testing Service (ETS) scores the writing quality of essays. In the current practice, e-rater scores are generated via a multiple linear regression (MLR) model as a linear combination of various features evaluated for each essay and human scores as the outcome variable. This…
The Effects of the Concrete-Representational-Abstract Integration Strategy on the Ability of Students with Learning Disabilities to Multiply Linear Expressions within Area Problems

ERIC Educational Resources Information Center

Strickland, Tricia K.; Maccini, Paula

2013-01-01

We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…
Simultaneous spectrophotometric determination of salbutamol and bromhexine in tablets.

PubMed

Habib, I H I; Hassouna, M E M; Zaki, G A

2005-03-01

Typical anti-mucolytic drugs called salbutamol hydrochloride and bromhexine sulfate encountered in tablets were determined simultaneously either by using linear regression at zero-crossing wavelengths of the first derivation of UV-spectra or by application of multiple linear partial least squares regression method. The results obtained by the two proposed mathematical methods were compared with those obtained by the HPLC technique.
Maximizing the Information and Validity of a Linear Composite in the Factor Analysis Model for Continuous Item Responses

ERIC Educational Resources Information Center

Ferrando, Pere J.

2008-01-01

This paper develops results and procedures for obtaining linear composites of factor scores that maximize: (a) test information, and (b) validity with respect to external variables in the multiple factor analysis (FA) model. I treat FA as a multidimensional item response theory model, and use Ackerman's multidimensional information approach based…
High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

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

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