Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

Directory of Open Access Journals (Sweden)

Indranil Ghosh

2017-11-01

Full Text Available A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ .

Comparison of bipolar vs. tripolar concentric ring electrode Laplacian estimates.

Science.gov (United States)

Besio, W; Aakula, R; Dai, W

2004-01-01

Potentials on the body surface from the heart are of a spatial and temporal function. The 12-lead electrocardiogram (ECG) provides useful global temporal assessment, but it yields limited spatial information due to the smoothing effect caused by the volume conductor. The smoothing complicates identification of multiple simultaneous bioelectrical events. In an attempt to circumvent the smoothing problem, some researchers used a five-point method (FPM) to numerically estimate the analytical solution of the Laplacian with an array of monopolar electrodes. The FPM is generalized to develop a bi-polar concentric ring electrode system. We have developed a new Laplacian ECG sensor, a trielectrode sensor, based on a nine-point method (NPM) numerical approximation of the analytical Laplacian. For a comparison, the NPM, FPM and compact NPM were calculated over a 400 x 400 mesh with 1/400 spacing. Tri and bi-electrode sensors were also simulated and their Laplacian estimates were compared against the analytical Laplacian. We found that tri-electrode sensors have a much-improved accuracy with significantly less relative and maximum errors in estimating the Laplacian operator. Apart from the higher accuracy, our new electrode configuration will allow better localization of the electrical activity of the heart than bi-electrode configurations.

The advantages of the surface Laplacian in brain-computer interface research.

Science.gov (United States)

McFarland, Dennis J

2015-09-01

Brain-computer interface (BCI) systems frequently use signal processing methods, such as spatial filtering, to enhance performance. The surface Laplacian can reduce spatial noise and aid in identification of sources. In BCI research, these two functions of the surface Laplacian correspond to prediction accuracy and signal orthogonality. In the present study, an off-line analysis of data from a sensorimotor rhythm-based BCI task dissociated these functions of the surface Laplacian by comparing nearest-neighbor and next-nearest neighbor Laplacian algorithms. The nearest-neighbor Laplacian produced signals that were more orthogonal while the next-nearest Laplacian produced signals that resulted in better accuracy. Both prediction and signal identification are important for BCI research. Better prediction of user's intent produces increased speed and accuracy of communication and control. Signal identification is important for ruling out the possibility of control by artifacts. Identifying the nature of the control signal is relevant both to understanding exactly what is being studied and in terms of usability for individuals with limited motor control. Copyright © 2014 Elsevier B.V. All rights reserved.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

Science.gov (United States)

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

Spanning forests and the vector bundle Laplacian

OpenAIRE

Kenyon, Richard

2011-01-01

The classical matrix-tree theorem relates the determinant of the combinatorial Laplacian on a graph to the number of spanning trees. We generalize this result to Laplacians on one- and two-dimensional vector bundles, giving a combinatorial interpretation of their determinants in terms of so-called cycle rooted spanning forests (CRSFs). We construct natural measures on CRSFs for which the edges form a determinantal process. ¶ This theory gives a natural generalization of the spanning tre...

Reliability for some bivariate beta distributions

Directory of Open Access Journals (Sweden)

Nadarajah Saralees

2005-01-01

Full Text Available In the area of stress-strength models there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate beta. The calculations involve the use of special functions.

Reliability for some bivariate gamma distributions

Directory of Open Access Journals (Sweden)

Nadarajah Saralees

2005-01-01

Full Text Available In the area of stress-strength models, there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate gamma. The calculations involve the use of special functions.

The Second Eigenvalue of the p-Laplacian as p Goes to 1

Directory of Open Access Journals (Sweden)

Enea Parini

2010-01-01

Full Text Available The asymptotic behaviour of the second eigenvalue of the p-Laplacian operator as p goes to 1 is investigated. The limit setting depends only on the geometry of the domain. In the particular case of a planar disc, it is possible to show that the second eigenfunctions are nonradial if p is close enough to 1.

Self-adjointness of the Gaffney Laplacian on Vector Bundles

International Nuclear Information System (INIS)

Bandara, Lashi; Milatovic, Ognjen

2015-01-01

We study the Gaffney Laplacian on a vector bundle equipped with a compatible metric and connection over a Riemannian manifold that is possibly geodesically incomplete. Under the hypothesis that the Cauchy boundary is polar, we demonstrate the self-adjointness of this Laplacian. Furthermore, we show that negligible boundary is a necessary and sufficient condition for the self-adjointness of this operator

Self-adjointness of the Gaffney Laplacian on Vector Bundles

Energy Technology Data Exchange (ETDEWEB)

Bandara, Lashi, E-mail: lashi.bandara@chalmers.se [Chalmers University of Technology and University of Gothenburg, Mathematical Sciences (Sweden); Milatovic, Ognjen, E-mail: omilatov@unf.edu [University of North Florida, Department of Mathematics and Statistics (United States)

2015-12-15

We study the Gaffney Laplacian on a vector bundle equipped with a compatible metric and connection over a Riemannian manifold that is possibly geodesically incomplete. Under the hypothesis that the Cauchy boundary is polar, we demonstrate the self-adjointness of this Laplacian. Furthermore, we show that negligible boundary is a necessary and sufficient condition for the self-adjointness of this operator.

Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging.

Science.gov (United States)

Zhang, Shuanghui; Liu, Yongxiang; Li, Xiang; Bi, Guoan

2016-04-28

This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.

Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging

Directory of Open Access Journals (Sweden)

Shuanghui Zhang

2016-04-01

Full Text Available This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP estimation and the maximum likelihood estimation (MLE are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.

Approximation of bivariate copulas by patched bivariate Fréchet copulas

KAUST Repository

Zheng, Yanting; Yang, Jingping; Huang, Jianhua Z.

2011-01-01

Bivariate Fréchet (BF) copulas characterize dependence as a mixture of three simple structures: comonotonicity, independence and countermonotonicity. They are easily interpretable but have limitations when used as approximations to general dependence structures. To improve the approximation property of the BF copulas and keep the advantage of easy interpretation, we develop a new copula approximation scheme by using BF copulas locally and patching the local pieces together. Error bounds and a probabilistic interpretation of this approximation scheme are developed. The new approximation scheme is compared with several existing copula approximations, including shuffle of min, checkmin, checkerboard and Bernstein approximations and exhibits better performance, especially in characterizing the local dependence. The utility of the new approximation scheme in insurance and finance is illustrated in the computation of the rainbow option prices and stop-loss premiums. © 2010 Elsevier B.V.

Approximation of bivariate copulas by patched bivariate Fréchet copulas

KAUST Repository

Zheng, Yanting

2011-03-01

Bivariate Fréchet (BF) copulas characterize dependence as a mixture of three simple structures: comonotonicity, independence and countermonotonicity. They are easily interpretable but have limitations when used as approximations to general dependence structures. To improve the approximation property of the BF copulas and keep the advantage of easy interpretation, we develop a new copula approximation scheme by using BF copulas locally and patching the local pieces together. Error bounds and a probabilistic interpretation of this approximation scheme are developed. The new approximation scheme is compared with several existing copula approximations, including shuffle of min, checkmin, checkerboard and Bernstein approximations and exhibits better performance, especially in characterizing the local dependence. The utility of the new approximation scheme in insurance and finance is illustrated in the computation of the rainbow option prices and stop-loss premiums. © 2010 Elsevier B.V.

Linking EEG signals, brain functions and mental operations: Advantages of the Laplacian transformation.

Science.gov (United States)

Vidal, Franck; Burle, Boris; Spieser, Laure; Carbonnell, Laurence; Meckler, Cédric; Casini, Laurence; Hasbroucq, Thierry

2015-09-01

Electroencephalography (EEG) is a very popular technique for investigating brain functions and/or mental processes. To this aim, EEG activities must be interpreted in terms of brain and/or mental processes. EEG signals being a direct manifestation of neuronal activity it is often assumed that such interpretations are quite obvious or, at least, straightforward. However, they often rely on (explicit or even implicit) assumptions regarding the structures supposed to generate the EEG activities of interest. For these assumptions to be used appropriately, reliable links between EEG activities and the underlying brain structures must be established. Because of volume conduction effects and the mixture of activities they induce, these links are difficult to establish with scalp potential recordings. We present different examples showing how the Laplacian transformation, acting as an efficient source separation method, allowed to establish more reliable links between EEG activities and brain generators and, ultimately, with mental operations. The nature of those links depends on the depth of inferences that can vary from weak to strong. Along this continuum, we show that 1) while the effects of experimental manipulation can appear widely distributed with scalp potentials, Laplacian transformation allows to reveal several generators contributing (in different manners) to these modulations, 2) amplitude variations within the same set of generators can generate spurious differences in scalp potential topographies, often interpreted as reflecting different source configurations. In such a case, Laplacian transformation provides much more similar topographies, evidencing the same generator(s) set, and 3) using the LRP as an index of response activation most often produces ambiguous results, Laplacian-transformed response-locked ERPs obtained over motor areas allow resolving these ambiguities. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes

Science.gov (United States)

Ding, Quan; Besio, Walter G.

2015-01-01

Conventional electroencephalography with disc electrodes has major drawbacks including poor spatial resolution, selectivity and low signal-to-noise ratio that are critically limiting its use. Concentric ring electrodes, consisting of several elements including the central disc and a number of concentric rings, are a promising alternative with potential to improve all of the aforementioned aspects significantly. In our previous work, the tripolar concentric ring electrode was successfully used in a wide range of applications demonstrating its superiority to conventional disc electrode, in particular, in accuracy of Laplacian estimation. This paper takes the next step toward further improving the Laplacian estimation with novel multipolar concentric ring electrodes by completing and validating a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. An explicit formula based on inversion of a square Vandermonde matrix is derived to make computation of multipolar Laplacian more efficient. To confirm the analytic result of the accuracy of Laplacian estimate increasing with the increase of n and to assess the significance of this gain in accuracy for practical applications finite element method model analysis has been performed. Multipolar concentric ring electrode configurations with n ranging from 1 ring (bipolar electrode configuration) to 6 rings (septapolar electrode configuration) were directly compared and obtained results suggest the significance of the increase in Laplacian accuracy caused by increase of n. PMID:26693200

The Graph Laplacian and the Dynamics of Complex Networks

Energy Technology Data Exchange (ETDEWEB)

Thulasidasan, Sunil [Los Alamos National Laboratory

2012-06-11

In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

Optimized Laplacian image sharpening algorithm based on graphic processing unit

Science.gov (United States)

Ma, Tinghuai; Li, Lu; Ji, Sai; Wang, Xin; Tian, Yuan; Al-Dhelaan, Abdullah; Al-Rodhaan, Mznah

2014-12-01

In classical Laplacian image sharpening, all pixels are processed one by one, which leads to large amount of computation. Traditional Laplacian sharpening processed on CPU is considerably time-consuming especially for those large pictures. In this paper, we propose a parallel implementation of Laplacian sharpening based on Compute Unified Device Architecture (CUDA), which is a computing platform of Graphic Processing Units (GPU), and analyze the impact of picture size on performance and the relationship between the processing time of between data transfer time and parallel computing time. Further, according to different features of different memory, an improved scheme of our method is developed, which exploits shared memory in GPU instead of global memory and further increases the efficiency. Experimental results prove that two novel algorithms outperform traditional consequentially method based on OpenCV in the aspect of computing speed.

A comparison of tripolar concentric ring electrode and spline Laplacians on a four-layer concentric spherical model.

Science.gov (United States)

Liu, Xiang; Makeyev, Oleksandr; Besio, Walter

2011-01-01

We have simulated a four-layer concentric spherical head model. We calculated the spline and tripolar Laplacian estimates and compared them to the analytical Laplacian on the spherical surface. In the simulations we used five different dipole groups and two electrode configurations. The comparison shows that the tripolar Laplacian has higher correlation coefficient to the analytical Laplacian in the electrode configurations tested (19, standard 10/20 locations and 64 electrodes).

Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy

Directory of Open Access Journals (Sweden)

Yusuke Imai

2014-04-01

Full Text Available Because the cost of performance testing using actual products is expensive, manufacturers use lower-cost computer-aided design simulations for this function. In this paper, we propose using hexahedral meshes, which are more accurate than tetrahedral meshes, for finite element analysis. We propose automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated using a voxel-based algorithm. In our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vectors in the fitting to preserve sharp features. However, this method could not represent concave sharp features precisely. In this proposal, we improve our previous Laplacian energy minimization by adding a term that depends on multi-normal vectors instead of using normal vectors. Furthermore, we accentuate a convex/concave surface subset to represent concave sharp features.

Laplacian manifold regularization method for fluorescence molecular tomography

Science.gov (United States)

He, Xuelei; Wang, Xiaodong; Yi, Huangjian; Chen, Yanrong; Zhang, Xu; Yu, Jingjing; He, Xiaowei

2017-04-01

Sparse regularization methods have been widely used in fluorescence molecular tomography (FMT) for stable three-dimensional reconstruction. Generally, ℓ1-regularization-based methods allow for utilizing the sparsity nature of the target distribution. However, in addition to sparsity, the spatial structure information should be exploited as well. A joint ℓ1 and Laplacian manifold regularization model is proposed to improve the reconstruction performance, and two algorithms (with and without Barzilai-Borwein strategy) are presented to solve the regularization model. Numerical studies and in vivo experiment demonstrate that the proposed Gradient projection-resolved Laplacian manifold regularization method for the joint model performed better than the comparative algorithm for ℓ1 minimization method in both spatial aggregation and location accuracy.

STUDI PERBANDINGAN ANTARA ALGORITMA BIVARIATE MARGINAL DISTRIBUTION DENGAN ALGORITMA GENETIKA

Directory of Open Access Journals (Sweden)

Chastine Fatichah

2006-01-01

Full Text Available Bivariate Marginal Distribution Algorithm is extended from Estimation of Distribution Algorithm. This heuristic algorithm proposes the new approach for recombination of generate new individual that without crossover and mutation process such as genetic algorithm. Bivariate Marginal Distribution Algorithm uses connectivity variable the pair gene for recombination of generate new individual. Connectivity between variable is doing along optimization process. In this research, genetic algorithm performance with one point crossover is compared with Bivariate Marginal Distribution Algorithm performance in case Onemax, De Jong F2 function, and Traveling Salesman Problem. In this research, experimental results have shown performance the both algorithm is dependence of parameter respectively and also population size that used. For Onemax case with size small problem, Genetic Algorithm perform better with small number of iteration and more fast for get optimum result. However, Bivariate Marginal Distribution Algorithm perform better of result optimization for case Onemax with huge size problem. For De Jong F2 function, Genetic Algorithm perform better from Bivariate Marginal Distribution Algorithm of a number of iteration and time. For case Traveling Salesman Problem, Bivariate Marginal Distribution Algorithm have shown perform better from Genetic Algorithm of optimization result. Abstract in Bahasa Indonesia : Bivariate Marginal Distribution Algorithm merupakan perkembangan lebih lanjut dari Estimation of Distribution Algorithm. Algoritma heuristik ini mengenalkan pendekatan baru dalam melakukan rekombinasi untuk membentuk individu baru, yaitu tidak menggunakan proses crossover dan mutasi seperti pada Genetic Algorithm. Bivariate Marginal Distribution Algorithm menggunakan keterkaitan pasangan variabel dalam melakukan rekombinasi untuk membentuk individu baru. Keterkaitan antar variabel tersebut ditemukan selama proses optimasi berlangsung. Aplikasi yang

Solving Graph Laplacian Systems Through Recursive Bisections and Two-Grid Preconditioning

Energy Technology Data Exchange (ETDEWEB)

Ponce, Colin [Cornell Univ., Ithaca, NY (United States); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-02-18

We present a parallelizable direct method for computing the solution to graph Laplacian-based linear systems derived from graphs that can be hierarchically bipartitioned with small edge cuts. For a graph of size n with constant-size edge cuts, our method decomposes a graph Laplacian in time O(n log n), and then uses that decomposition to perform a linear solve in time O(n log n). We then use the developed technique to design a preconditioner for graph Laplacians that do not have this property. Finally, we augment this preconditioner with a two-grid method that accounts for much of the preconditioner's weaknesses. We present an analysis of this method, as well as a general theorem for the condition number of a general class of two-grid support graph-based preconditioners. Numerical experiments illustrate the performance of the studied methods.

Symmetries and Laplacians introduction to harmonic analysis, group representations and applications

CERN Document Server

Gurarie, D

1992-01-01

Designed as an introduction to harmonic analysis and group representations,this book covers a wide range of topics rather than delving deeply into anyparticular one. In the words of H. Weyl ...it is primarily meant forthe humble, who want to learn as new the things set forth therein, rather thanfor the proud and learned who are already familiar with the subject and merelylook for quick and exact information.... The main objective is tointroduce the reader to concepts, ideas, results and techniques that evolvearound symmetry-groups, representations and Laplacians. Morespecifically, the main interest concerns geometrical objects and structures{X}, discrete or continuous, that possess sufficiently large symmetrygroup G, such as regular graphs (Platonic solids), lattices, andsymmetric Riemannian manifolds. All such objects have a natural Laplacian&Dgr;, a linear operator on functions over X, invariant underthe group action. There are many problems associated with Laplacians onX, such as continuous or discrete...

Optimizing an objective function under a bivariate probability model

NARCIS (Netherlands)

X. Brusset; N.M. Temme (Nico)

2007-01-01

htmlabstractThe motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probability distribution functions that may be dependent. This method is applicable when results need to be

The Method of Subsuper Solutions for Weighted p(r-Laplacian Equation Boundary Value Problems

Directory of Open Access Journals (Sweden)

Zhimei Qiu

2008-10-01

Full Text Available This paper investigates the existence of solutions for weighted p(r-Laplacian ordinary boundary value problems. Our method is based on Leray-Schauder degree. As an application, we give the existence of weak solutions for p(x-Laplacian partial differential equations.

Bivariational calculations for radiation transfer in an inhomogeneous participating media

International Nuclear Information System (INIS)

El Wakil, S.A.; Machali, H.M.; Haggag, M.H.; Attia, M.T.

1986-07-01

Equations for radiation transfer are obtained for dispersive media with space dependent albedo. Bivariational bound principle is used to calculate the reflection and transmission coefficients for such media. Numerical results are given and compared. (author)

Eigenvalues of the -Laplacian and disconjugacy criteria

Directory of Open Access Journals (Sweden)

Pinasco Juan P

2006-01-01

Full Text Available We derive oscillation and nonoscillation criteria for the one-dimensional -Laplacian in terms of an eigenvalue inequality for a mixed problem. We generalize the results obtained in the linear case by Nehari and Willett, and the proof is based on a Picone-type identity.

Group theoretic reduction of Laplacian dynamical problems on fractal lattices

International Nuclear Information System (INIS)

Schwalm, W.A.; Schwalm, M.K.; Giona, M.

1997-01-01

Discrete forms of the Schroedinger equation, the diffusion equation, the linearized Landau-Ginzburg equation, and discrete models for vibrations and spin dynamics belong to a class of Laplacian-based finite difference models. Real-space renormalization of such models on finitely ramified regular fractals is known to give exact recursion relations. It is shown that these recursions commute with Lie groups representing continuous symmetries of the discrete models. Each such symmetry reduces the order of the renormalization recursions by one, resulting in a system of recursions with one fewer variable. Group trajectories are obtained from inverse images of fixed and invariant sets of the recursions. A subset of the Laplacian finite difference models can be mapped by change of boundary conditions and time dependence to a diffusion problem with closed boundaries. In such cases conservation of mass simplifies the group flow and obtaining the groups becomes easier. To illustrate this, the renormalization recursions for Green functions on four standard examples are decoupled. The examples are (1) the linear chain, (2) an anisotropic version of Dhar close-quote s 3-simplex, similar to a model dealt with by Hood and Southern, (3) the fourfold coordinated Sierpiacute nski lattice of Rammal and of Domany et al., and (4) a form of the Vicsek lattice. Prospects for applying the group theoretic method to more general dynamical systems are discussed. copyright 1997 The American Physical Society

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

Science.gov (United States)

Abdelnour, Farras; Dayan, Michael; Devinsky, Orrin; Thesen, Thomas; Raj, Ashish

2018-05-15

How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses. Copyright © 2018. Published by Elsevier Inc.

Bivariate generalized Pareto distribution for extreme atmospheric particulate matter

Science.gov (United States)

Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

2015-02-01

The high particulate matter (PM10) level is the prominent issue causing various impacts to human health and seriously affecting the economics. The asymptotic theory of extreme value is apply for analyzing the relation of extreme PM10 data from two nearby air quality monitoring stations. The series of daily maxima PM10 for Johor Bahru and Pasir Gudang stations are consider for year 2001 to 2010 databases. The 85% and 95% marginal quantile apply to determine the threshold values and hence construct the series of exceedances over the chosen threshold. The logistic, asymmetric logistic, negative logistic and asymmetric negative logistic models areconsidered as the dependence function to the joint distribution of a bivariate observation. Maximum likelihood estimation is employed for parameter estimations. The best fitted model is chosen based on the Akaike Information Criterion and the quantile plots. It is found that the asymmetric logistic model gives the best fitted model for bivariate extreme PM10 data and shows the weak dependence between two stations.

Picture change error in quasirelativistic electron/spin density, Laplacian and bond critical points

KAUST Repository

Bučinský , Luká š; Kucková , Lenka; Malček, Michal; Koží šek, Jozef; Biskupič, Stanislav; Jayatilaka, Dylan; Bü chel, Gabriel E.; Arion, Vladimir B.

2014-01-01

The change of picture of the quasirelativistic Hartree-Fock wave functions is considered for electron/spin densities, the negative Laplacian of electron density and the appropriate bond critical point characteristics from the Quantum Theory of Atoms In Molecules (QTAIM). [OsCl5(Hpz)]- and [RuCl5(NO)]2- transition metal complexes are considered. Both, scalar relativistic and spin-orbit effects have been accounted for using the Infinite Order Two Component (IOTC) Hamiltonian. Picture change error (PCE) correction in the electron and spin densities and the Laplacian of electron density are treated analytically. Generally, PCE is found significant only in the core region of the atoms for the electron/spin density as well as Laplacian.©2014 Elsevier B.V. All rights reserved.

Picture change error in quasirelativistic electron/spin density, Laplacian and bond critical points

KAUST Repository

Bučinský, Lukáš

2014-06-01

The change of picture of the quasirelativistic Hartree-Fock wave functions is considered for electron/spin densities, the negative Laplacian of electron density and the appropriate bond critical point characteristics from the Quantum Theory of Atoms In Molecules (QTAIM). [OsCl5(Hpz)]- and [RuCl5(NO)]2- transition metal complexes are considered. Both, scalar relativistic and spin-orbit effects have been accounted for using the Infinite Order Two Component (IOTC) Hamiltonian. Picture change error (PCE) correction in the electron and spin densities and the Laplacian of electron density are treated analytically. Generally, PCE is found significant only in the core region of the atoms for the electron/spin density as well as Laplacian.©2014 Elsevier B.V. All rights reserved.

Bivariate extreme value with application to PM10 concentration analysis

Science.gov (United States)

Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

2015-05-01

This study is focus on a bivariate extreme of renormalized componentwise maxima with generalized extreme value distribution as a marginal function. The limiting joint distribution of several parametric models are presented. Maximum likelihood estimation is employed for parameter estimations and the best model is selected based on the Akaike Information Criterion. The weekly and monthly componentwise maxima series are extracted from the original observations of daily maxima PM10 data for two air quality monitoring stations located in Pasir Gudang and Johor Bahru. The 10 years data are considered for both stations from year 2001 to 2010. The asymmetric negative logistic model is found as the best fit bivariate extreme model for both weekly and monthly maxima componentwise series. However the dependence parameters show that the variables for weekly maxima series is more dependence to each other compared to the monthly maxima.

Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes

Directory of Open Access Journals (Sweden)

Oleksandr Makeyev

2016-06-01

Full Text Available Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1-polar electrode with n rings using the (4n + 1-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2 and quadripolar (n = 3 electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected.

Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes

Science.gov (United States)

Makeyev, Oleksandr; Besio, Walter G.

2016-01-01

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected. PMID:27294933

The inverse spatial Laplacian of spherically symmetric spacetimes

International Nuclear Information System (INIS)

Fernandes, Karan; Lahiri, Amitabha

2017-01-01

We derive the inverse spatial Laplacian for static, spherically symmetric backgrounds by solving Poisson’s equation for a point source. This is different from the electrostatic Green function, which is defined on the four dimensional static spacetime, while the equation we consider is defined on the spatial hypersurface of such spacetimes. This Green function is relevant in the Hamiltonian dynamics of theories defined on spherically symmetric backgrounds, and closed form expressions for the solutions we find are absent in the literature. We derive an expression in terms of elementary functions for the Schwarzschild spacetime, and comment on the relation of this solution with the known Green function of the spacetime Laplacian operator. We also find an expression for the Green function on the static pure de-Sitter space in terms of hypergeometric functions. We conclude with a discussion of the constraints of the electromagnetic field. (paper)

Computer simulation comparison of tripolar, bipolar, and spline Laplacian electrocadiogram estimators.

Science.gov (United States)

Chen, T; Besio, W; Dai, W

2009-01-01

A comparison of the performance of the tripolar and bipolar concentric as well as spline Laplacian electrocardiograms (LECGs) and body surface Laplacian mappings (BSLMs) for localizing and imaging the cardiac electrical activation has been investigated based on computer simulation. In the simulation a simplified eccentric heart-torso sphere-cylinder homogeneous volume conductor model were developed. Multiple dipoles with different orientations were used to simulate the underlying cardiac electrical activities. Results show that the tripolar concentric ring electrodes produce the most accurate LECG and BSLM estimation among the three estimators with the best performance in spatial resolution.

Periodic and subharmonic solutions for second order p-Laplacian ...

Indian Academy of Sciences (India)

Periodic and subharmonic solutions; -Laplacian; difference equations; discrete variational theory. ... Packaging Engineering Institute, Jinan University, Zhuhai 519070, People's Republic of China; College of Mathematics and Information Sciences, Guangzhou University, Guangzhou 510006, People's Republic of China ...

Two new bivariate zero-inflated generalized Poisson distributions with a flexible correlation structure

Directory of Open Access Journals (Sweden)

Chi Zhang

2015-05-01

Full Text Available To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP distributions by incorporating a multiplicative factor (or dependency parameter λ, named as Type I and Type II bivariate ZIGP distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions of Type I bivariate ZIGP share a common parameter of zero inflation while the two marginal distributions of Type II bivariate ZIGP have their own parameters of zero inflation, resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including maximum likelihood estimations of parameters, standard errors estimation, bootstrap confidence intervals and related testing hypotheses are developed for the two distributions. A real data are thoroughly analyzed by using the proposed distributions and statistical methods. Several simulation studies are conducted to evaluate the performance of the proposed methods.

An acceleration system for Laplacian image fusion based on SoC

Science.gov (United States)

Gao, Liwen; Zhao, Hongtu; Qu, Xiujie; Wei, Tianbo; Du, Peng

2018-04-01

Based on the analysis of Laplacian image fusion algorithm, this paper proposes a partial pipelining and modular processing architecture, and a SoC based acceleration system is implemented accordingly. Full pipelining method is used for the design of each module, and modules in series form the partial pipelining with unified data formation, which is easy for management and reuse. Integrated with ARM processor, DMA and embedded bare-mental program, this system achieves 4 layers of Laplacian pyramid on the Zynq-7000 board. Experiments show that, with small resources consumption, a couple of 256×256 images can be fused within 1ms, maintaining a fine fusion effect at the same time.

Bivariate discrete beta Kernel graduation of mortality data.

Science.gov (United States)

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

Development of a Compact Wireless Laplacian Electrode Module for Electromyograms and Its Human Interface Applications

Directory of Open Access Journals (Sweden)

Akira Ichikawa

2013-02-01

Full Text Available In this study, we developed a compact wireless Laplacian electrode module for electromyograms (EMGs. One of the advantages of the Laplacian electrode configuration is that EMGs obtained with it are expected to be sensitive to the firing of the muscle directly beneath the measurement site. The performance of the developed electrode module was investigated in two human interface applications: character-input interface and detection of finger movement during finger Braille typing. In the former application, the electrode module was combined with an EMG-mouse click converter circuit. In the latter, four electrode modules were used for detection of finger movements during finger Braille typing. Investigation on the character-input interface indicated that characters could be input stably by contraction of (a the masseter, (b trapezius, (c anterior tibialis and (d flexor carpi ulnaris muscles. This wide applicability is desirable when the interface is applied to persons with physical disabilities because the disability differs one to another. The investigation also demonstrated that the electrode module can work properly without any skin preparation. Finger movement detection experiments showed that each finger movement was more clearly detectable when comparing to EMGs recorded with conventional electrodes, suggesting that the Laplacian electrode module is more suitable for detecting the timing of finger movement during typing. This could be because the Laplacian configuration enables us to record EMGs just beneath the electrode. These results demonstrate the advantages of the Laplacian electrode module.

Spectral density regression for bivariate extremes

KAUST Repository

Castro Camilo, Daniela

2016-05-11

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg

The exact Laplacian spectrum for the Dyson hierarchical network.

Science.gov (United States)

Agliari, Elena; Tavani, Flavia

2017-01-09

We consider the Dyson hierarchical graph , that is a weighted fully-connected graph, where the pattern of weights is ruled by the parameter σ ∈ (1/2, 1]. Exploiting the deterministic recursivity through which is built, we are able to derive explicitly the whole set of the eigenvalues and the eigenvectors for its Laplacian matrix. Given that the Laplacian operator is intrinsically implied in the analysis of dynamic processes (e.g., random walks) occurring on the graph, as well as in the investigation of the dynamical properties of connected structures themselves (e.g., vibrational structures and relaxation modes), this result allows addressing analytically a large class of problems. In particular, as examples of applications, we study the random walk and the continuous-time quantum walk embedded in , the relaxation times of a polymer whose structure is described by , and the community structure of in terms of modularity measures.

Spectral estimates for Dirichlet Laplacians on perturbed twisted tubes

Czech Academy of Sciences Publication Activity Database

Exner, Pavel; Barseghyan, Diana

2014-01-01

Roč. 8, č. 1 (2014), s. 167-183 ISSN 1846-3886 R&D Projects: GA ČR GAP203/11/0701 Institutional support: RVO:61389005 Keywords : Drichlet Laplacian * twisted tube * discrete spectrum * eigenvalue estimates Subject RIV: BE - Theoretical Physics Impact factor: 0.583, year: 2014

Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

Science.gov (United States)

Wang, Weiguang; Fu, Jianyu

2018-02-01

Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.

A Third-Order p-Laplacian Boundary Value Problem Solved by an SL(3,ℝ Lie-Group Shooting Method

Directory of Open Access Journals (Sweden)

Chein-Shan Liu

2013-01-01

Full Text Available The boundary layer problem for power-law fluid can be recast to a third-order p-Laplacian boundary value problem (BVP. In this paper, we transform the third-order p-Laplacian into a new system which exhibits a Lie-symmetry SL(3,ℝ. Then, the closure property of the Lie-group is used to derive a linear transformation between the boundary values at two ends of a spatial interval. Hence, we can iteratively solve the missing left boundary conditions, which are determined by matching the right boundary conditions through a finer tuning of r∈[0,1]. The present SL(3,ℝ Lie-group shooting method is easily implemented and is efficient to tackle the multiple solutions of the third-order p-Laplacian. When the missing left boundary values can be determined accurately, we can apply the fourth-order Runge-Kutta (RK4 method to obtain a quite accurate numerical solution of the p-Laplacian.

Successive overrelaxation for laplacian support vector machine.

Science.gov (United States)

Qi, Zhiquan; Tian, Yingjie; Shi, Yong

2015-04-01

Semisupervised learning (SSL) problem, which makes use of both a large amount of cheap unlabeled data and a few unlabeled data for training, in the last few years, has attracted amounts of attention in machine learning and data mining. Exploiting the manifold regularization (MR), Belkin et al. proposed a new semisupervised classification algorithm: Laplacian support vector machines (LapSVMs), and have shown the state-of-the-art performance in SSL field. To further improve the LapSVMs, we proposed a fast Laplacian SVM (FLapSVM) solver for classification. Compared with the standard LapSVM, our method has several improved advantages as follows: 1) FLapSVM does not need to deal with the extra matrix and burden the computations related to the variable switching, which make it more suitable for large scale problems; 2) FLapSVM’s dual problem has the same elegant formulation as that of standard SVMs. This means that the kernel trick can be applied directly into the optimization model; and 3) FLapSVM can be effectively solved by successive overrelaxation technology, which converges linearly to a solution and can process very large data sets that need not reside in memory. In practice, combining the strategies of random scheduling of subproblem and two stopping conditions, the computing speed of FLapSVM is rigidly quicker to that of LapSVM and it is a valid alternative to PLapSVM.

A non-stationary cost-benefit based bivariate extreme flood estimation approach

Science.gov (United States)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review

Science.gov (United States)

Kayser, Jürgen; Tenke, Craig E.

2015-01-01

Despite the recognition that the surface Laplacian may counteract adverse effects of volume conduction and recording reference for surface potential data, electrophysiology as a discipline has been reluctant to embrace this approach for data analysis. The reasons for such hesitation are manifold but often involve unfamiliarity with the nature of the underlying transformation, as well as intimidation by a perceived mathematical complexity, and concerns of signal loss, dense electrode array requirements, or susceptibility to noise. We revisit the pitfalls arising from volume conduction and the mandated arbitrary choice of EEG reference, describe the basic principle of the surface Laplacian transform in an intuitive fashion, and exemplify the differences between common reference schemes (nose, linked mastoids, average) and the surface Laplacian for frequently-measured EEG spectra (theta, alpha) and standard event-related potential (ERP) components, such as N1 or P3. We specifically review common reservations against the universal use of the surface Laplacian, which can be effectively addressed by employing spherical spline interpolations with an appropriate selection of the spline flexibility parameter and regularization constant. We argue from a pragmatic perspective that not only are these reservations unfounded but that the continued predominant use of surface potentials poses a considerable impediment on the progress of EEG and ERP research. PMID:25920962

Progressive image denoising through hybrid graph Laplacian regularization: a unified framework.

Science.gov (United States)

Liu, Xianming; Zhai, Deming; Zhao, Debin; Zhai, Guangtao; Gao, Wen

2014-04-01

Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned, which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space. In this procedure, the intrinsic manifold structure is explicitly considered using both measured and unmeasured samples, and the nonlocal self-similarity property is utilized as a fruitful resource for abstracting a priori knowledge of the images. On the other hand, between two successive scales, the proposed model is extended to a projected high-dimensional feature space through explicit kernel mapping to describe the interscale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. In this way, the proposed algorithm gradually recovers more and more image details and edges, which could not been recovered in previous scale. We test our algorithm on one typical image recovery task: impulse noise removal. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art algorithms.

An Affine Invariant Bivariate Version of the Sign Test.

Science.gov (United States)

1987-06-01

words: affine invariance, bivariate quantile, bivariate symmetry, model,. generalized median, influence function , permutation test, normal efficiency...calculate a bivariate version of the influence function , and the resulting form is bounded, as is the case for the univartate sign test, and shows the...terms of a blvariate analogue of IHmpel’s (1974) influence function . The latter, though usually defined as a von-Mises derivative of certain

On the solvability of Dirichlet problem for the weighted p-Laplacian

Directory of Open Access Journals (Sweden)

Ewa Szlachtowska

2012-01-01

Full Text Available The paper investigates the existence and uniqueness of weak solutions for a non-linear boundary value problem involving the weighted \\(p\\-Laplacian. Our approach is based on variational principles and representation properties of the associated spaces.

Potential theory, path integrals and the Laplacian of the indicator

NARCIS (Netherlands)

R.-J. Lange (Rutger-Jan)

2012-01-01

markdownabstractThis paper links the field of potential theory — i.e. the Dirichlet and Neumann problems for the heat and Laplace equation — to that of the Feynman path integral, by postulating the some seemingly ill-defined potential. The Laplacian of the indicator can be interpreted using the

Eigenvalues of the Laplacian and of the Hecke operators for PSL(2,Z)

International Nuclear Information System (INIS)

Steil, G.

1994-03-01

A new method is described to compute with high accuracy a large number of eigenvalues and eigenfunctions (Maass wave forms) of the Laplacian and of the Hecke operators for the modular group. It relies essentially on the theory of Hecke operators. The results of the computations confirm some important conjectures from number theory, namely Ramanujan-Petersson, Sato-Tate, and the conjecture that the discrete spectrum of the Laplacian be simple. Examples of the numerical data are included as a reference. The algorithm can be generalized to other non-cocompact but cofinite arithmetic groups, like Picard group PSL(2, Z)[i]) and Hecke triangle groups Γ(√2) and Γ(√3). (orig.)

Uniqueness of non-linear ground states for fractional Laplacians in R

DEFF Research Database (Denmark)

Frank, Rupert L.; Lenzmann, Enno

2013-01-01

We prove uniqueness of ground state solutions Q = Q(|x|) ≥ 0 of the non-linear equation (−Δ)sQ+Q−Qα+1=0inR,where 0 fractional Laplacian in one dimension. In particular, we answer affirmatively an open question...... recently raised by Kenig–Martel–Robbiano and we generalize (by completely different techniques) the specific uniqueness result obtained by Amick and Toland for s=12 and α = 1 in [5] for the Benjamin–Ono equation. As a technical key result in this paper, we show that the associated linearized operator L...... + = (−Δ) s +1−(α+1)Q α is non-degenerate; i.e., its kernel satisfies ker L + = span{Q′}. This result about L + proves a spectral assumption, which plays a central role for the stability of solitary waves and blowup analysis for non-linear dispersive PDEs with fractional Laplacians, such as the generalized...

Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.

Science.gov (United States)

Kayser, Jürgen; Tenke, Craig E

2015-09-01

Despite the recognition that the surface Laplacian may counteract adverse effects of volume conduction and recording reference for surface potential data, electrophysiology as a discipline has been reluctant to embrace this approach for data analysis. The reasons for such hesitation are manifold but often involve unfamiliarity with the nature of the underlying transformation, as well as intimidation by a perceived mathematical complexity, and concerns of signal loss, dense electrode array requirements, or susceptibility to noise. We revisit the pitfalls arising from volume conduction and the mandated arbitrary choice of EEG reference, describe the basic principle of the surface Laplacian transform in an intuitive fashion, and exemplify the differences between common reference schemes (nose, linked mastoids, average) and the surface Laplacian for frequently-measured EEG spectra (theta, alpha) and standard event-related potential (ERP) components, such as N1 or P3. We specifically review common reservations against the universal use of the surface Laplacian, which can be effectively addressed by employing spherical spline interpolations with an appropriate selection of the spline flexibility parameter and regularization constant. We argue from a pragmatic perspective that not only are these reservations unfounded but that the continued predominant use of surface potentials poses a considerable impediment on the progress of EEG and ERP research. Copyright © 2015 Elsevier B.V. All rights reserved.

Existence of Three Positive Solutions to Some p-Laplacian Boundary Value Problems

Directory of Open Access Journals (Sweden)

Moulay Rchid Sidi Ammi

2013-01-01

Full Text Available We obtain, by using the Leggett-Williams fixed point theorem, sufficient conditions that ensure the existence of at least three positive solutions to some p-Laplacian boundary value problems on time scales.

Comparison of Model Reliabilities from Single-Step and Bivariate Blending Methods

DEFF Research Database (Denmark)

Taskinen, Matti; Mäntysaari, Esa; Lidauer, Martin

2013-01-01

Model based reliabilities in genetic evaluation are compared between three methods: animal model BLUP, single-step BLUP, and bivariate blending after genomic BLUP. The original bivariate blending is revised in this work to better account animal models. The study data is extracted from...... be calculated. Model reliabilities by the single-step and the bivariate blending methods were higher than by animal model due to genomic information. Compared to the single-step method, the bivariate blending method reliability estimates were, in general, lower. Computationally bivariate blending method was......, on the other hand, lighter than the single-step method....

Laplacian eigenvectors of graphs Perron-Frobenius and Faber-Krahn type theorems

CERN Document Server

Biyikoğu, Türker; Stadler, Peter F

2007-01-01

Eigenvectors of graph Laplacians have not, to date, been the subject of expository articles and thus they may seem a surprising topic for a book. The authors propose two motivations for this new LNM volume: (1) There are fascinating subtle differences between the properties of solutions of Schrödinger equations on manifolds on the one hand, and their discrete analogs on graphs. (2) "Geometric" properties of (cost) functions defined on the vertex sets of graphs are of practical interest for heuristic optimization algorithms. The observation that the cost functions of quite a few of the well-studied combinatorial optimization problems are eigenvectors of associated graph Laplacians has prompted the investigation of such eigenvectors. The volume investigates the structure of eigenvectors and looks at the number of their sign graphs ("nodal domains"), Perron components, graphs with extremal properties with respect to eigenvectors. The Rayleigh quotient and rearrangement of graphs form the main methodology.

A note on 'Oriental magic mirrors and the Laplacian image'

International Nuclear Information System (INIS)

Riesz, Ferenc

2006-01-01

Berry has shown (2006 Eur. J. Phys. 27 109-18) that the image of an oriental magic mirror (an essentially flat mirror with small surface relief) is the Laplacian of the surface relief for low-curvature features. In this note, an alternative derivation is presented and the physical meaning of the used approximations is explained. (note)

Image denoising via adaptive eigenvectors of graph Laplacian

Science.gov (United States)

Chen, Ying; Tang, Yibin; Xu, Ning; Zhou, Lin; Zhao, Li

2016-07-01

An image denoising method via adaptive eigenvectors of graph Laplacian (EGL) is proposed. Unlike the trivial parameter setting of the used eigenvectors in the traditional EGL method, in our method, the eigenvectors are adaptively selected in the whole denoising procedure. In detail, a rough image is first built with the eigenvectors from the noisy image, where the eigenvectors are selected by using the deviation estimation of the clean image. Subsequently, a guided image is effectively restored with a weighted average of the noisy and rough images. In this operation, the average coefficient is adaptively obtained to set the deviation of the guided image to approximately that of the clean image. Finally, the denoised image is achieved by a group-sparse model with the pattern from the guided image, where the eigenvectors are chosen in the error control of the noise deviation. Moreover, a modified group orthogonal matching pursuit algorithm is developed to efficiently solve the above group sparse model. The experiments show that our method not only improves the practicality of the EGL methods with the dependence reduction of the parameter setting, but also can outperform some well-developed denoising methods, especially for noise with large deviations.

Covariate analysis of bivariate survival data

Energy Technology Data Exchange (ETDEWEB)

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.

On Consensus of Star-Composed Networks with an Application of Laplacian Spectrum

Directory of Open Access Journals (Sweden)

Da Huang

2017-01-01

Full Text Available In this paper, we mainly study the performance of star-composed networks which can achieve consensus. Specifically, we investigate the convergence speed and robustness of the consensus of the networks, which can be measured by the smallest nonzero eigenvalue λ2 of the Laplacian matrix and the H2 norm of the graph, respectively. In particular, we introduce the notion of the corona of two graphs to construct star-composed networks and apply the Laplacian spectrum to discuss the convergence speed and robustness for the communication network. Finally, the performances of the star-composed networks have been compared, and we find that the network in which the centers construct a balanced complete bipartite graph has the most advantages of performance. Our research would provide a new insight into the combination between the field of consensus study and the theory of graph spectra.

Spectral estimates for Dirichlet Laplacians and Schrodinger operators on geometrically nontrivial cusps

Czech Academy of Sciences Publication Activity Database

Exner, Pavel; Barseghyan, Diana

2013-01-01

Roč. 3, č. 4 (2013), s. 465-484 ISSN 1664-039X R&D Projects: GA ČR GAP203/11/0701 Institutional support: RVO:61389005 Keywords : Dirichlet Laplacian * cusp-shaped region * Lieb-Thirring inequalities * bending and twisting Subject RIV: BE - Theoretical Physics

Ordinal bivariate inequality

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlationincreasing switches and/or median......-preserving spreads. For the canonical 2x2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....

On Two Functionals Connected to the Laplacian in a Class of ...

Indian Academy of Sciences (India)

Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 1. On Two Functionals Connected to the Laplacian in a Class of Doubly Connected Domains in Space-Forms. M H C Anisa A R Aithal. Volume 115 Issue 1 February ... M H C Anisa1 A R Aithal1. Department of Mathematics, University of Mumbai, ...

Spherical Dunkl-monogenics and a factorization of the Dunkl-Laplacian

International Nuclear Information System (INIS)

Fei Minggang; Cerejeiras, Paula; Kaehler, Uwe

2010-01-01

In this paper, we consider and study a factorization of the Dunkl-Laplacian in terms of spherical coordinates. This allows for the construction of a direct sum decomposition of spherical Dunkl-harmonics. By explicit representation in spherical coordinates of Dunkl-harmonics, one obtains explicit projection operators from Dunkl-harmonics to inner (resp. outer) Dunkl-monogenics. Concrete examples of spherical Dunkl-monogenics will be given at the end.

Second-order periodic problem with Phi-Laplacian and impulses

Czech Academy of Sciences Publication Activity Database

Rachůnková, I.; Tvrdý, Milan

2005-01-01

Roč. 63, 5-7/Sp.Is/ (2005), e257-e266 ISSN 0362-546X. [Invited Talks from the Fourth World Congress of Nonlinear Analysts (WCNA 2004). Orlando , 30.7.2004-7.8.2004] R&D Projects: GA ČR(CZ) GA201/04/1077 Institutional research plan: CEZ:AV0Z1019905 Keywords : Laplacian * impulses * lower/upper functions Subject RIV: BA - General Mathematics Impact factor: 0.519, year: 2005 www.elsevier.com/locate/na

Tail-weighted dependence measures with limit being the tail dependence coefficient

KAUST Repository

Lee, David

2017-12-02

For bivariate continuous data, measures of monotonic dependence are based on the rank transformations of the two variables. For bivariate extreme value copulas, there is a family of estimators (Formula presented.), for (Formula presented.), of the extremal coefficient, based on a transform of the absolute difference of the α power of the ranks. In the case of general bivariate copulas, we obtain the probability limit (Formula presented.) of (Formula presented.) as the sample size goes to infinity and show that (i) (Formula presented.) for (Formula presented.) is a measure of central dependence with properties similar to Kendall\\'s tau and Spearman\\'s rank correlation, (ii) (Formula presented.) is a tail-weighted dependence measure for large α, and (iii) the limit as (Formula presented.) is the upper tail dependence coefficient. We obtain asymptotic properties for the rank-based measure (Formula presented.) and estimate tail dependence coefficients through extrapolation on (Formula presented.). A data example illustrates the use of the new dependence measures for tail inference.

Tail-weighted dependence measures with limit being the tail dependence coefficient

KAUST Repository

Lee, David; Joe, Harry; Krupskii, Pavel

2017-01-01

For bivariate continuous data, measures of monotonic dependence are based on the rank transformations of the two variables. For bivariate extreme value copulas, there is a family of estimators (Formula presented.), for (Formula presented.), of the extremal coefficient, based on a transform of the absolute difference of the α power of the ranks. In the case of general bivariate copulas, we obtain the probability limit (Formula presented.) of (Formula presented.) as the sample size goes to infinity and show that (i) (Formula presented.) for (Formula presented.) is a measure of central dependence with properties similar to Kendall's tau and Spearman's rank correlation, (ii) (Formula presented.) is a tail-weighted dependence measure for large α, and (iii) the limit as (Formula presented.) is the upper tail dependence coefficient. We obtain asymptotic properties for the rank-based measure (Formula presented.) and estimate tail dependence coefficients through extrapolation on (Formula presented.). A data example illustrates the use of the new dependence measures for tail inference.

Ordinal Bivariate Inequality

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

2016-01-01

This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlation-increasing switches and....../or median-preserving spreads. For the canonical 2 × 2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....

On the number of negative eigenvalues of the Laplacian on a metric graph

International Nuclear Information System (INIS)

Behrndt, Jussi; Luger, Annemarie

2010-01-01

The number of negative eigenvalues of self-adjoint Laplacians on metric graphs is calculated in terms of the boundary conditions and the underlying geometric structure. This extends and complements earlier results by Kostrykin and Schrader (2006 Contemp. Math. 415 201-25).

On the number of negative eigenvalues of the Laplacian on a metric graph

Energy Technology Data Exchange (ETDEWEB)

Behrndt, Jussi [Institut fuer Mathematik, MA 6-4, Technische Universitaet Berlin, Strasse des 17. Juni 136, 10623 Berlin (Germany); Luger, Annemarie, E-mail: behrndt@math.tu-berlin.d, E-mail: luger@maths.lth.s [Center for Mathematical Sciences, Lund Institute of Technology/Lund University, Box 118, SE-221 00 Lund (Sweden)

2010-11-26

The number of negative eigenvalues of self-adjoint Laplacians on metric graphs is calculated in terms of the boundary conditions and the underlying geometric structure. This extends and complements earlier results by Kostrykin and Schrader (2006 Contemp. Math. 415 201-25).

Bivariate copula in fitting rainfall data

Science.gov (United States)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

Science.gov (United States)

Rahimi, A.; Zhang, L.

2012-12-01

Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further

Bivariable analysis of ventricular late potentials in high resolution ECG records

International Nuclear Information System (INIS)

Orosco, L; Laciar, E

2007-01-01

In this study the bivariable analysis for ventricular late potentials detection in high-resolution electrocardiographic records is proposed. The standard time-domain analysis and the application of the time-frequency technique to high-resolution ECG records are briefly described as well as their corresponding results. In the proposed technique the time-domain parameter, QRSD and the most significant time-frequency index, EN QRS are used like variables. A bivariable index is defined, that combines the previous parameters. The propose technique allows evaluating the risk of ventricular tachycardia in post-myocardial infarct patients. The results show that the used bivariable index allows discriminating between the patient's population with ventricular tachycardia and the subjects of the control group. Also, it was found that the bivariable technique obtains a good valuation as diagnostic test. It is concluded that comparatively, the valuation of the bivariable technique as diagnostic test is superior to that of the time-domain method and the time-frequency technique evaluated individually

Class of nonsingular exact solutions for Laplacian pattern formation

International Nuclear Information System (INIS)

Mineev-Weinstein, M.B.; Dawson, S.P.

1994-01-01

We present a class of exact solutions for the so-called Laplacian growth equation describing the zero-surface-tension limit of a variety of two-dimensional pattern formation problems. These solutions are free of finite-time singularities (cusps) for quite general initial conditions. They reproduce various features of viscous fingering observed in experiments and numerical simulations with surface tension, such as existence of stagnation points, screening, tip splitting, and coarsening. In certain cases the asymptotic interface consists of N separated moving Saffman-Taylor fingers

Building Bivariate Tables: The compareGroups Package for R

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Isaac Subirana

2014-05-01

Full Text Available The R package compareGroups provides functions meant to facilitate the construction of bivariate tables (descriptives of several variables for comparison between groups and generates reports in several formats (LATEX, HTML or plain text CSV. Moreover, bivariate tables can be viewed directly on the R console in a nice format. A graphical user interface (GUI has been implemented to build the bivariate tables more easily for those users who are not familiar with the R software. Some new functions and methods have been incorporated in the newest version of the compareGroups package (version 1.x to deal with time-to-event variables, stratifying tables, merging several tables, and revising the statistical methods used. The GUI interface also has been improved, making it much easier and more intuitive to set the inputs for building the bivariate tables. The ?rst version (version 0.x and this version were presented at the 2010 useR! conference (Sanz, Subirana, and Vila 2010 and the 2011 useR! conference (Sanz, Subirana, and Vila 2011, respectively. Package compareGroups is available from the Comprehensive R Archive Network at http://CRAN.R-project.org/package=compareGroups.

The relative performance of bivariate causality tests in small samples

NARCIS (Netherlands)

Bult, J..R.; Leeflang, P.S.H.; Wittink, D.R.

1997-01-01

Causality tests have been applied to establish directional effects and to reduce the set of potential predictors, For the latter type of application only bivariate tests can be used, In this study we compare bivariate causality tests. Although the problem addressed is general and could benefit

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

Science.gov (United States)

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

Positive periodic solution for p-Laplacian neutral Rayleigh equation with singularity of attractive type.

Science.gov (United States)

Xin, Yun; Liu, Hongmin; Cheng, Zhibo

2018-01-01

In this paper, we consider a kind of p -Laplacian neutral Rayleigh equation with singularity of attractive type, [Formula: see text] By applications of an extension of Mawhin's continuation theorem, sufficient conditions for the existence of periodic solution are established.

Existence and multiplicity of homoclinic solutions for p(t-Laplacian systems with subquadratic potentials

Directory of Open Access Journals (Sweden)

Bin Qin

2014-04-01

Full Text Available By using the genus properties, we establish some criteria for the second-order p(t-Laplacian system $$ \\frac{d}{dt}\\big(|\\dot{u}(t|^{p(t-2}\\dot{u}(t\\big-a(t|u(t|^{p(t-2}u(t +\

A Hartman–Nagumo inequality for the vector ordinary -Laplacian and applications to nonlinear boundary value problems

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Ureña Antonio J

2002-01-01

Full Text Available A generalization of the well-known Hartman–Nagumo inequality to the case of the vector ordinary -Laplacian and classical degree theory provide existence results for some associated nonlinear boundary value problems.

Study on a kind of ϕ-Laplacian Liénard equation with attractive and repulsive singularities.

Science.gov (United States)

Xin, Yun; Cheng, Zhibo

2017-01-01

In this paper, by application of the Manasevich-Mawhin continuation theorem, we investigate the existence of a positive periodic solution for a kind of ϕ -Laplacian singular Liénard equation with attractive and repulsive singularities.

Efficient estimation of semiparametric copula models for bivariate survival data

KAUST Repository

Cheng, Guang

2014-01-01

A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

Factorization of the Laplacian and families of elementary particles

International Nuclear Information System (INIS)

Keller, J.

1994-01-01

It is shown that multi-vector Clifford algebra allows a series of factorizations of the Laplacian operator and associated Dirac-like equations, this set of related equations generates 3 families of elementary particles with the experimentally observed lepton and quark content for each family and the experimentally observed electroweak color interactions and other related properties. In contrast to the usual approach to the standard model the properties for the different fields of the model are consequences of the relative properties of the equations, among themselves and in relation to space-time, and therefore, they do not need to be postulates of the theory. 11 refs

Communication Dependent Control of Multi-Vehicle Formations

Science.gov (United States)

2016-05-11

On Maximizing the Second Smallest Eigen- value of a State-Dependent Graph Laplacian,” IEEE Transactions on Au- tomatic Control, vol. 51, no. 1, pp...Collective Motion With Limited Communication,” IEEE Transactions on Au- tomatic Control, vol. 53, no. 3, pp. 706–719, 2008. [Online]. Available: http

A generalized right truncated bivariate Poisson regression model with applications to health data.

Science.gov (United States)

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

Symbol Error Rate of MPSK over EGK Channels Perturbed by a Dominant Additive Laplacian Noise

KAUST Repository

Souri, Hamza; Alouini, Mohamed-Slim

2015-01-01

The Laplacian noise has received much attention during the recent years since it affects many communication systems. We consider in this paper the probability of error of an M-ary phase shift keying (PSK) constellation operating over a generalized fading channel in presence of a dominant additive Laplacian noise. In this context, the decision regions of the receiver are determined using the maximum likelihood and the minimum distance detectors. Once the decision regions are extracted, the resulting symbol error rate expressions are computed and averaged over an Extended Generalized-K fading distribution. Generic closed form expressions of the conditional and the average probability of error are obtained in terms of the Fox’s H function. Simplifications for some special cases of fading are presented and the resulting formulas end up being often expressed in terms of well known elementary functions. Finally, the mathematical formalism is validated using some selected analytical-based numerical results as well as Monte- Carlo simulation-based results.

Symbol Error Rate of MPSK over EGK Channels Perturbed by a Dominant Additive Laplacian Noise

KAUST Repository

Souri, Hamza

2015-06-01

The Laplacian noise has received much attention during the recent years since it affects many communication systems. We consider in this paper the probability of error of an M-ary phase shift keying (PSK) constellation operating over a generalized fading channel in presence of a dominant additive Laplacian noise. In this context, the decision regions of the receiver are determined using the maximum likelihood and the minimum distance detectors. Once the decision regions are extracted, the resulting symbol error rate expressions are computed and averaged over an Extended Generalized-K fading distribution. Generic closed form expressions of the conditional and the average probability of error are obtained in terms of the Fox’s H function. Simplifications for some special cases of fading are presented and the resulting formulas end up being often expressed in terms of well known elementary functions. Finally, the mathematical formalism is validated using some selected analytical-based numerical results as well as Monte- Carlo simulation-based results.

Solvability of fractional multi-point boundary-value problems with p-Laplacian operator at resonance

Directory of Open Access Journals (Sweden)

Tengfei Shen

2014-02-01

Full Text Available In this article, we consider the multi-point boundary-value problem for nonlinear fractional differential equations with $p$-Laplacian operator: $$\\displaylines{ D_{0^+}^\\beta \\varphi_p (D_{0^+}^\\alpha u(t = f(t,u(t,D_{0^+}^{\\alpha - 2} u(t,D_{0^+}^{\\alpha - 1} u(t, D_{0^+}^\\alpha u(t,\\quad t \\in (0,1, \\cr u(0 = u'(0=D_{0^+}^\\alpha u(0 = 0,\\quad D_{0^+}^{\\alpha - 1} u(1 = \\sum_{i = 1}^m {\\sigma_i D_{0^+}^{\\alpha - 1} u(\\eta_i } , }$$ where $2 < \\alpha \\le 3$, $0 < \\beta \\le 1$, $3 < \\alpha + \\beta \\le 4$, $\\sum_{i = 1}^m {\\sigma_i } = 1$, $D_{0^+}^\\alpha$ is the standard Riemann-Liouville fractional derivative. $\\varphi_{p}(s=|s|^{p-2}s$ is p-Laplacians operator. The existence of solutions for above fractional boundary value problem is obtained by using the extension of Mawhin's continuation theorem due to Ge, which enrich konwn results. An example is given to illustrate the main result.

Sufficient condition for existence of solutions for higher-order resonance boundary value problem with one-dimensional p-Laplacian

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Liu Yang

2007-10-01

Full Text Available By using coincidence degree theory of Mawhin, existence results for some higher order resonance multipoint boundary value problems with one dimensional p-Laplacian operator are obtained.

A comparison of bivariate and univariate QTL mapping in livestock populations

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Sorensen Daniel

2003-11-01

Full Text Available Abstract This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML. The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL's map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.

Existence of Subharmonic Solutions for a Class of Second-Order p-Laplacian Systems with Impulsive Effects

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Wen-Zhen Gong

2012-01-01

Full Text Available By using minimax methods in critical point theory, a new existence theorem of infinitely many periodic solutions is obtained for a class of second-order p-Laplacian systems with impulsive effects. Our result generalizes many known works in the literature.

Infinitely many solutions for Schrodinger-Kirchhoff type equations involving the fractional p-Laplacian and critical exponent

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Li Wang

2016-12-01

Full Text Available In this article, we show the existence of infinitely many solutions for the fractional p-Laplacian equations of Schrodinger-Kirchhoff type equation $$ M([u]_{s, p}^p (-\\Delta _p^s u+V(x|u|^{p-2}u= \\alpha |u|^{ p_s^{*}-2 }u+\\beta k(x|u|^{q-2}u \\quad x\\in \\mathbb{R}^N, $$ where $(-\\Delta ^s_p$ is the fractional p-Laplacian operator, $[u]_{s,p}$ is the Gagliardo p-seminorm, $0 sp$, $1

Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

Science.gov (United States)

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.

Comparison between two bivariate Poisson distributions through the ...

African Journals Online (AJOL)

These two models express themselves by their probability mass function. ... To remedy this problem, Berkhout and Plug proposed a bivariate Poisson distribution accepting the correlation as well negative, equal to zero, that positive.

Bivariate value-at-risk

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Giuseppe Arbia

2007-10-01

Full Text Available In this paper we extend the concept of Value-at-risk (VaR to bivariate return distributions in order to obtain measures of the market risk of an asset taking into account additional features linked to downside risk exposure. We first present a general definition of risk as the probability of an adverse event over a random distribution and we then introduce a measure of market risk (b-VaR that admits the traditional b of an asset in portfolio management as a special case when asset returns are normally distributed. Empirical evidences are provided by using Italian stock market data.

Causal networks clarify productivity-richness interrelations, bivariate plots do not

Science.gov (United States)

Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

2014-01-01

Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding.

Regression analysis for bivariate gap time with missing first gap time data.

Science.gov (United States)

Huang, Chia-Hui; Chen, Yi-Hau

2017-01-01

We consider ordered bivariate gap time while data on the first gap time are unobservable. This study is motivated by the HIV infection and AIDS study, where the initial HIV contracting time is unavailable, but the diagnosis times for HIV and AIDS are available. We are interested in studying the risk factors for the gap time between initial HIV contraction and HIV diagnosis, and gap time between HIV and AIDS diagnoses. Besides, the association between the two gap times is also of interest. Accordingly, in the data analysis we are faced with two-fold complexity, namely data on the first gap time is completely missing, and the second gap time is subject to induced informative censoring due to dependence between the two gap times. We propose a modeling framework for regression analysis of bivariate gap time under the complexity of the data. The estimating equations for the covariate effects on, as well as the association between, the two gap times are derived through maximum likelihood and suitable counting processes. Large sample properties of the resulting estimators are developed by martingale theory. Simulations are performed to examine the performance of the proposed analysis procedure. An application of data from the HIV and AIDS study mentioned above is reported for illustration.

A bivariate model for analyzing recurrent multi-type automobile failures

Science.gov (United States)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by

Unadjusted Bivariate Two-Group Comparisons: When Simpler is Better.

Science.gov (United States)

Vetter, Thomas R; Mascha, Edward J

2018-01-01

Hypothesis testing involves posing both a null hypothesis and an alternative hypothesis. This basic statistical tutorial discusses the appropriate use, including their so-called assumptions, of the common unadjusted bivariate tests for hypothesis testing and thus comparing study sample data for a difference or association. The appropriate choice of a statistical test is predicated on the type of data being analyzed and compared. The unpaired or independent samples t test is used to test the null hypothesis that the 2 population means are equal, thereby accepting the alternative hypothesis that the 2 population means are not equal. The unpaired t test is intended for comparing dependent continuous (interval or ratio) data from 2 study groups. A common mistake is to apply several unpaired t tests when comparing data from 3 or more study groups. In this situation, an analysis of variance with post hoc (posttest) intragroup comparisons should instead be applied. Another common mistake is to apply a series of unpaired t tests when comparing sequentially collected data from 2 study groups. In this situation, a repeated-measures analysis of variance, with tests for group-by-time interaction, and post hoc comparisons, as appropriate, should instead be applied in analyzing data from sequential collection points. The paired t test is used to assess the difference in the means of 2 study groups when the sample observations have been obtained in pairs, often before and after an intervention in each study subject. The Pearson chi-square test is widely used to test the null hypothesis that 2 unpaired categorical variables, each with 2 or more nominal levels (values), are independent of each other. When the null hypothesis is rejected, 1 concludes that there is a probable association between the 2 unpaired categorical variables. When comparing 2 groups on an ordinal or nonnormally distributed continuous outcome variable, the 2-sample t test is usually not appropriate. The

Distortion Correction in Fetal EPI Using Non-Rigid Registration With a Laplacian Constraint.

Science.gov (United States)

Kuklisova-Murgasova, Maria; Lockwood Estrin, Georgia; Nunes, Rita G; Malik, Shaihan J; Rutherford, Mary A; Rueckert, Daniel; Hajnal, Joseph V

2018-01-01

Geometric distortion induced by the main B0 field disrupts the consistency of fetal echo planar imaging (EPI) data, on which diffusion and functional magnetic resonance imaging is based. In this paper, we present a novel data-driven method for simultaneous motion and distortion correction of fetal EPI. A motion-corrected and reconstructed T2 weighted single shot fast spin echo (ssFSE) volume is used as a model of undistorted fetal brain anatomy. Our algorithm interleaves two registration steps: estimation of fetal motion parameters by aligning EPI slices to the model; and deformable registration of EPI slices to slices simulated from the undistorted model to estimate the distortion field. The deformable registration is regularized by a physically inspired Laplacian constraint, to model distortion induced by a source-free background B0 field. Our experiments show that distortion correction significantly improves consistency of reconstructed EPI volumes with ssFSE volumes. In addition, the estimated distortion fields are consistent with fields calculated from acquired field maps, and the Laplacian constraint is essential for estimation of plausible distortion fields. The EPI volumes reconstructed from different scans of the same subject were more consistent when the proposed method was used in comparison with EPI volumes reconstructed from data distortion corrected using a separately acquired B0 field map.

Triple solutions for a Dirichlet boundary value problem involving a perturbed discrete p(k-Laplacian operator

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Khaleghi Moghadam Mohsen

2017-08-01

Full Text Available Triple solutions are obtained for a discrete problem involving a nonlinearly perturbed one-dimensional p(k-Laplacian operator and satisfying Dirichlet boundary conditions. The methods for existence rely on a Ricceri-local minimum theorem for differentiable functionals. Several examples are included to illustrate the main results.

Probability distributions with truncated, log and bivariate extensions

CERN Document Server

Thomopoulos, Nick T

2018-01-01

This volume presents a concise and practical overview of statistical methods and tables not readily available in other publications. It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data. The book will be highly useful to anyone who does statistical and probability analysis. This in...

Energy decay for wave equations of phi-Laplacian type with weakly nonlinear dissipation

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Aissa Guesmia

2008-08-01

Full Text Available In this paper, first we prove the existence of global solutions in Sobolev spaces for the initial boundary value problem of the wave equation of $phi$-Laplacian with a general dissipation of the form $$ (|u'|^{l-2}u''-Delta_{phi}u+sigma(t g(u'=0 quadext{in } Omegaimes mathbb{R}_+ , $$ where $Delta_{phi}=sum_{i=1}^n partial_{x_i}igl(phi (|partial_{x_i}|^2partial_{x_i}igr$. Then we prove general stability estimates using multiplier method and general weighted integral inequalities proved by the second author in [18]. Without imposing any growth condition at the origin on $g$ and $phi$, we show that the energy of the system is bounded above by a quantity, depending on $phi$, $sigma$ and $g$, which tends to zero (as time approaches infinity. These estimates allows us to consider large class of functions $g$ and $phi$ with general growth at the origin. We give some examples to illustrate how to derive from our general estimates the polynomial, exponential or logarithmic decay. The results of this paper improve and generalize many existing results in the literature, and generate some interesting open problems.

GIS-Based bivariate statistical techniques for groundwater potential ...

Indian Academy of Sciences (India)

24

This study shows the potency of two GIS-based data driven bivariate techniques namely ... In the view of these weaknesses , there is a strong requirement for reassessment of .... Font color: Text 1, Not Expanded by / Condensed by , ...... West Bengal (India) using remote sensing, geographical information system and multi-.

Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity

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Songjoon Baek

2017-05-01

Full Text Available In response to activating signals, transcription factors (TFs bind DNA and regulate gene expression. TF binding can be measured by protection of the bound sequence from DNase digestion (i.e., footprint. Here, we report that 80% of TF binding motifs do not show a measurable footprint, partly because of a variable cleavage pattern within the motif sequence. To more faithfully portray the effect of TFs on chromatin, we developed an algorithm that captures two TF-dependent effects on chromatin accessibility: footprinting and motif-flanking accessibility. The algorithm, termed bivariate genomic footprinting (BaGFoot, efficiently detects TF activity. BaGFoot is robust to different accessibility assays (DNase-seq, ATAC-seq, all examined peak-calling programs, and a variety of cut bias correction approaches. BaGFoot reliably predicts TF binding and provides valuable information regarding the TFs affecting chromatin accessibility in various biological systems and following various biological events, including in cases where an absolute footprint cannot be determined.

Assessing the copula selection for bivariate frequency analysis ...

Indian Academy of Sciences (India)

58

Copulas are applied to overcome the restriction of traditional bivariate frequency ... frequency analysis methods cannot describe the random variable properties that ... In order to overcome the limitation of multivariate distributions, a copula is a ..... The Mann-Kendall (M-K) test is a non-parametric statistical test which is used ...

Existence of Positive Solutions for a Coupled System of (p, q-Laplacian Fractional Higher Order Boundary Value Problems

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K.R. Prasad

2015-11-01

Full Text Available In this paper, we establish the existence of at least three positive solutions for a system of (p,q-Laplacian fractional order two-point boundary value problems by applying five functionals fixed point theorem under suitable conditions on a cone in a Banach space.

About some properties of bivariate splines with shape parameters

Science.gov (United States)

Caliò, F.; Marchetti, E.

2017-07-01

The paper presents and proves geometrical properties of a particular bivariate function spline, built and algorithmically implemented in previous papers. The properties typical of this family of splines impact the field of computer graphics in particular that of the reverse engineering.

Preconditioned steepest descent methods for some nonlinear elliptic equations involving p-Laplacian terms

Energy Technology Data Exchange (ETDEWEB)

Feng, Wenqiang, E-mail: wfeng1@vols.utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States); Salgado, Abner J., E-mail: asalgad1@utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States); Wang, Cheng, E-mail: cwang1@umassd.edu [Department of Mathematics, The University of Massachusetts, North Dartmouth, MA 02747 (United States); Wise, Steven M., E-mail: swise1@utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States)

2017-04-01

We describe and analyze preconditioned steepest descent (PSD) solvers for fourth and sixth-order nonlinear elliptic equations that include p-Laplacian terms on periodic domains in 2 and 3 dimensions. The highest and lowest order terms of the equations are constant-coefficient, positive linear operators, which suggests a natural preconditioning strategy. Such nonlinear elliptic equations often arise from time discretization of parabolic equations that model various biological and physical phenomena, in particular, liquid crystals, thin film epitaxial growth and phase transformations. The analyses of the schemes involve the characterization of the strictly convex energies associated with the equations. We first give a general framework for PSD in Hilbert spaces. Based on certain reasonable assumptions of the linear pre-conditioner, a geometric convergence rate is shown for the nonlinear PSD iteration. We then apply the general theory to the fourth and sixth-order problems of interest, making use of Sobolev embedding and regularity results to confirm the appropriateness of our pre-conditioners for the regularized p-Lapacian problems. Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works. We demonstrate rigorously how to apply the theory in the finite dimensional setting using finite difference discretization methods. Numerical simulations for some important physical application problems – including thin film epitaxy with slope selection and the square phase field crystal model – are carried out to verify the efficiency of the scheme.

A New Measure Of Bivariate Asymmetry And Its Evaluation

International Nuclear Information System (INIS)

Ferreira, Flavio Henn; Kolev, Nikolai Valtchev

2008-01-01

In this paper we propose a new measure of bivariate asymmetry, based on conditional correlation coefficients. A decomposition of the Pearson correlation coefficient in terms of its conditional versions is studied and an example of application of the proposed measure is given.

Proof of concept Laplacian estimate derived for noninvasive tripolar concentric ring electrode with incorporated radius of the central disc and the widths of the concentric rings.

Science.gov (United States)

Makeyev, Oleksandr; Lee, Colin; Besio, Walter G

2017-07-01

Tripolar concentric ring electrodes are showing great promise in a range of applications including braincomputer interface and seizure onset detection due to their superiority to conventional disc electrodes, in particular, in accuracy of surface Laplacian estimation. Recently, we proposed a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. This approach has been used to introduce novel multipolar and variable inter-ring distances concentric ring electrode configurations verified using finite element method. The obtained results suggest their potential to improve Laplacian estimation compared to currently used constant interring distances tripolar concentric ring electrodes. One of the main limitations of the proposed (4n + 1)-point method is that the radius of the central disc and the widths of the concentric rings are not included and therefore cannot be optimized. This study incorporates these two parameters by representing the central disc and both concentric rings as clusters of points with specific radius and widths respectively as opposed to the currently used single point and concentric circles. A proof of concept Laplacian estimate is derived for a tripolar concentric ring electrode with non-negligible radius of the central disc and non-negligible widths of the concentric rings clearly demonstrating how both of these parameters can be incorporated into the (4n + 1)-point method.

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

Science.gov (United States)

Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

Spectrum-based estimators of the bivariate Hurst exponent

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2014-01-01

Roč. 90, č. 6 (2014), art. 062802 ISSN 1539-3755 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : bivariate Hurst exponent * power- law cross-correlations * estimation Subject RIV: AH - Economics Impact factor: 2.288, year: 2014 http://library.utia.cas.cz/separaty/2014/E/kristoufek-0436818.pdf

Triple Positive Solutions of a Nonlocal Boundary Value Problem for Singular Differential Equations with p-Laplacian

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Jufang Wang

2013-01-01

Full Text Available We establish the existence of triple positive solutions of an m-point boundary value problem for the nonlinear singular second-order differential equations of mixed type with a p-Laplacian operator by Leggett-William fixed point theorem. At last, we give an example to demonstrate the use of the main result of this paper. The conclusions in this paper essentially extend and improve the known results.

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

Maadooliat, Mehdi

2015-10-21

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

Maadooliat, Mehdi; Zhou, Lan; Najibi, Seyed Morteza; Gao, Xin; Huang, Jianhua Z.

2015-01-01

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

Existence of standing waves for Schrodinger equations involving the fractional Laplacian

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Everaldo S. de Medeiros

2017-03-01

Full Text Available We study a class of fractional Schrodinger equations of the form $$ \\varepsilon^{2\\alpha}(-\\Delta^\\alpha u+ V(xu = f(x,u \\quad\\text{in } \\mathbb{R}^N, $$ where $\\varepsilon$ is a positive parameter, $0 < \\alpha < 1$, $2\\alpha < N$, $(-\\Delta^\\alpha$ is the fractional Laplacian, $V:\\mathbb{R}^{N}\\to \\mathbb{R}$ is a potential which may be bounded or unbounded and the nonlinearity $f:\\mathbb{R}^{N}\\times \\mathbb{R}\\to \\mathbb{R}$ is superlinear and behaves like $|u|^{p-2}u$ at infinity for some $2

An Existence Principle for Nonlocal Difference Boundary Value Problems with φ-Laplacian and Its Application to Singular Problems

Directory of Open Access Journals (Sweden)

Svatoslav Stanêk

2008-03-01

Full Text Available The paper presents an existence principle for solving a large class of nonlocal regular discrete boundary value problems with the φ-Laplacian. Applications of the existence principle to singular discrete problems are given.

Overt foot movement detection in one single Laplacian EEG derivation.

Science.gov (United States)

Solis-Escalante, Teodoro; Müller-Putz, Gernot; Pfurtscheller, Gert

2008-10-30

In this work one single Laplacian derivation and a full description of band power values in a broad frequency band are used to detect brisk foot movement execution in the ongoing EEG. Two support vector machines (SVM) are trained to detect the event-related desynchronization (ERD) during motor execution and the following beta rebound (event-related synchronization, ERS) independently. Their performance is measured through the simulation of an asynchronous brain switch. ERS (true positive rate=0.74+/-0.21) after motor execution is shown to be more stable than ERD (true positive rate=0.21+/-0.12). A novel combination of ERD and post-movement ERS is introduced. The SVM outputs are combined with a product rule to merge ERD and ERS detection. For this novel approach the average information transfer rate obtained was 11.19+/-3.61bits/min.

Bivariate Rayleigh Distribution and its Properties

Directory of Open Access Journals (Sweden)

Ahmad Saeed Akhter

2007-01-01

Full Text Available Rayleigh (1880 observed that the sea waves follow no law because of the complexities of the sea, but it has been seen that the probability distributions of wave heights, wave length, wave induce pitch, wave and heave motions of the ships follow the Rayleigh distribution. At present, several different quantities are in use for describing the state of the sea; for example, the mean height of the waves, the root mean square height, the height of the “significant waves” (the mean height of the highest one-third of all the waves the maximum height over a given interval of the time, and so on. At present, the ship building industry knows less than any other construction industry about the service conditions under which it must operate. Only small efforts have been made to establish the stresses and motions and to incorporate the result of such studies in to design. This is due to the complexity of the problem caused by the extensive variability of the sea and the corresponding response of the ships. Although the problem appears feasible, yet it is possible to predict service conditions for ships in an orderly and relatively simple manner Rayleigh (1980 derived it from the amplitude of sound resulting from many independent sources. This distribution is also connected with one or two dimensions and is sometimes referred to as “random walk” frequency distribution. The Rayleigh distribution can be derived from the bivariate normal distribution when the variate are independent and random with equal variances. We try to construct bivariate Rayleigh distribution with marginal Rayleigh distribution function and discuss its fundamental properties.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

Science.gov (United States)

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.

Science.gov (United States)

Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza

2016-01-01

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.

Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

Science.gov (United States)

Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

2017-11-01

Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

Laplacian eigenmodes for spherical spaces

International Nuclear Information System (INIS)

Lachieze-Rey, M; Caillerie, S

2005-01-01

The possibility that our space is multi-rather than singly-connected has gained renewed interest after the discovery of the low power for the first multipoles of the CMB by WMAP. To test the possibility that our space is a multi-connected spherical space, it is necessary to know the eigenmodes of such spaces. Except for lens and prism space, and to some extent for dodecahedral space, this remains an open problem. Here we derive the eigenmodes of all spherical spaces. For dodecahedral space, the demonstration is much shorter, and the calculation method much simpler than before. We also apply our method to tetrahedric, octahedric and icosahedric spaces. This completes the knowledge of eigenmodes for spherical spaces, and opens the door to new observational tests of the cosmic topology. The vector space V k of the eigenfunctions of the Laplacian on the 3-sphere S 3 , corresponding to the same eigenvalue λ k = -k(k + 2), has dimension (k + 1) 2 . We show that the Wigner functions provide a basis for such a space. Using the properties of the latter, we express the behaviour of a general function of V k under an arbitrary rotation G of SO(4). This offers the possibility of selecting those functions of V k which remain invariant under G. Specifying G to be a generator of the holonomy group of a spherical space X, we give the expression of the vector space V x k of the eigenfunctions of X. We provide a method to calculate the eigenmodes up to an arbitrary order. As an illustration, we give the first modes for the spherical spaces mentioned

Existence of Positive Solutions to Singular -Laplacian General Dirichlet Boundary Value Problems with Sign Changing Nonlinearity

Directory of Open Access Journals (Sweden)

Qiying Wei

2009-01-01

Full Text Available By using the well-known Schauder fixed point theorem and upper and lower solution method, we present some existence criteria for positive solution of an -point singular -Laplacian dynamic equation on time scales with the sign changing nonlinearity. These results are new even for the corresponding differential (=ℝ and difference equations (=ℤ, as well as in general time scales setting. As an application, an example is given to illustrate the results.

Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

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Jacques Duchêne

2008-05-01

Full Text Available The aim of this paper was to compare empirical mode decomposition (EMD and two new extended methods of  EMD named complex empirical mode decomposition (complex-EMD and bivariate empirical mode decomposition (bivariate-EMD. All methods were used to analyze stabilogram center of pressure (COP time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.

Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

DEFF Research Database (Denmark)

Wu, Yili; Duan, Haiping; Tian, Xiaocao

2018-01-01

Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....

Multiple Positive Solutions of a Nonlinear Four-Point Singular Boundary Value Problem with a p-Laplacian Operator on Time Scales

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Shihuang Hong

2009-01-01

Full Text Available We present sufficient conditions for the existence of at least twin or triple positive solutions of a nonlinear four-point singular boundary value problem with a p-Laplacian dynamic equation on a time scale. Our results are obtained via some new multiple fixed point theorems.

Semi-automated detection of aberrant chromosomes in bivariate flow karyotypes

NARCIS (Netherlands)

Boschman, G. A.; Manders, E. M.; Rens, W.; Slater, R.; Aten, J. A.

1992-01-01

A method is described that is designed to compare, in a standardized procedure, bivariate flow karyotypes of Hoechst 33258 (HO)/Chromomycin A3 (CA) stained human chromosomes from cells with aberrations with a reference flow karyotype of normal chromosomes. In addition to uniform normalization of

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

Science.gov (United States)

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

Science.gov (United States)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

International Nuclear Information System (INIS)

Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

2017-01-01

As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data. (paper)

The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

Science.gov (United States)

Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

2017-07-01

As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data.

Positive Solutions of the One-Dimensional p-Laplacian with Nonlinearity Defined on a Finite Interval

OpenAIRE

Ruyun Ma; Chunjie Xie; Abubaker Ahmed

2013-01-01

We use the quadrature method to show the existence and multiplicity of positive solutions of the boundary value problems involving one-dimensional $p$ -Laplacian ${\\left({u}^{\\prime }\\left(t\\right){|}^{p-2}{u}^{\\prime }\\left(t\\right)\\right)}^{\\prime }+\\lambda f\\left(u\\left(t\\right)\\right)=0$ , $t\\in \\left(0,1\\right)$ , $u\\left(0\\right)=u\\left(1\\right)=0$ , where $p\\in \\left(1,2\\right]$ , $\\lambda \\in \\left(0,\\mathrm{\\infty }\\right)$ is a parameter, $f\\in {C}^{1}\\left(\\left[0,r\\right),\\l...

Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping.

Science.gov (United States)

Besio, W; Chen, T

2007-05-01

The electrocardiogram (ECG) provides useful global temporal assessment of the cardiac activity, but has limited spatial capabilities. The Laplacian electrocardiogram (LECG), an improvement over the ECG, provides high spatiotemporal distributed information about cardiac electrical activation. We designed and developed LECG tripolar concentric ring electrode active sensors based on the finite element algorithm 'nine-point method' (NPM). The active sensors were used in an array of 6 by 12 (72) locations to record bipolar and tripolar LECG from the body surface over the anterolateral chest. Compared to bipolar LECG, tripolar LECG showed significantly higher spatial selectivity which may be helpful in inferring information about cardiac activations detected on the body surface. In this study the moment of activation (MOA), an indicator of a depolarization wave passing below the active sensors, was used to surmise possible timing information of the cardiac electrical activation below the active sensors' recording sites. The MOA on the body surface was used to generate isochronal maps that may some day be used by clinicians in diagnosing arrhythmias and assessing the efficacy of therapies.

On the matched pairs sign test using bivariate ranked set sampling ...

African Journals Online (AJOL)

BVRSS) is introduced and investigated. We show that this test is asymptotically more efficient than its counterpart sign test based on a bivariate simple random sample (BVSRS). The asymptotic null distribution and the efficiency of the test are derived.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

Science.gov (United States)

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

Science.gov (United States)

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Bivariate return period for levee failure monitoring

Science.gov (United States)

Isola, M.; Caporali, E.

2017-12-01

Levee breaches are strongly linked with the interaction processes among water, soil and structure, thus many are the factors that affect the breach development. One of the main is the hydraulic load, characterized by intensity and duration, i.e. by the flood event hydrograph. On the magnitude of the hydraulic load is based the levee design, generally without considering the fatigue failure due to the load duration. Moreover, many are the cases in which the levee breach are characterized by flood of magnitude lower than the design one. In order to implement the strategies of flood risk management, we built here a procedure based on a multivariate statistical analysis of flood peak and volume together with the analysis of the past levee failure events. Particularly, in order to define the probability of occurrence of the hydraulic load on a levee, a bivariate copula model is used to obtain the bivariate joint distribution of flood peak and volume. Flood peak is the expression of the load magnitude, while the volume is the expression of the stress over time. We consider the annual flood peak and the relative volume. The volume is given by the hydrograph area between the beginning and the end of event. The beginning of the event is identified as an abrupt rise of the discharge by more than 20%. The end is identified as the point from which the receding limb is characterized by the baseflow, using a nonlinear reservoir algorithm as baseflow separation technique. By this, with the aim to define warning thresholds we consider the past levee failure events and the relative bivariate return period (BTr) compared with the estimation of a traditional univariate model. The discharge data of 30 hydrometric stations of Arno River in Tuscany, Italy, in the period 1995-2016 are analysed. The database of levee failure events, considering for each event the location as well as the failure mode, is also created. The events were registered in the period 2000-2014 by EEA

Selberg trace formula for bordered Riemann surfaces: Hyperbolic, elliptic and parabolic conjugacy classes, and determinants of Maass-Laplacians

International Nuclear Information System (INIS)

Bolte, J.

1992-08-01

The Selberg trace formula for automorphic forms of weight m ε- Z, on bordered Riemann surfaces is developed. The trace formula is formulated for arbitrary Fuchsian groups of the first kind which include hyperbolic, elliptic and parabolic conjugacy classes. In the case of compact bordered Riemann surfaces we can explicitly evaluate determinants of Maass-Laplacians for both Dirichlet and Neumann boundary-conditions, respectively. Some implications for the open bosonic string theory are mentioned. (orig.)

Robust bivariate error detection in skewed data with application to historical radiosonde winds

KAUST Repository

Sun, Ying

2017-01-18

The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

Robust bivariate error detection in skewed data with application to historical radiosonde winds

KAUST Repository

Sun, Ying; Hering, Amanda S.; Browning, Joshua M.

2017-01-01

The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

Chain Plot: A Tool for Exploiting Bivariate Temporal Structures

OpenAIRE

Taylor, CC; Zempeni, A

2004-01-01

In this paper we present a graphical tool useful for visualizing the cyclic behaviour of bivariate time series. We investigate its properties and link it to the asymmetry of the two variables concerned. We also suggest adding approximate confidence bounds to the points on the plot and investigate the effect of lagging to the chain plot. We conclude our paper by some standard Fourier analysis, relating and comparing this to the chain plot.

Bivariate tensor product ( p , q $(p, q$ -analogue of Kantorovich-type Bernstein-Stancu-Schurer operators

Directory of Open Access Journals (Sweden)

Qing-Bo Cai

2017-11-01

Full Text Available Abstract In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of ( p , q $(p, q$ -integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.

Heat kernel estimates for pseudodifferential operators, fractional Laplacians and Dirichlet-to-Neumann operators

DEFF Research Database (Denmark)

Gimperlein, Heiko; Grubb, Gerd

2014-01-01

The purpose of this article is to establish upper and lower estimates for the integral kernel of the semigroup exp(−t P) associated to a classical, strongly elliptic pseudodifferential operator P of positive order on a closed manifold. The Poissonian bounds generalize those obtained for perturbat......The purpose of this article is to establish upper and lower estimates for the integral kernel of the semigroup exp(−t P) associated to a classical, strongly elliptic pseudodifferential operator P of positive order on a closed manifold. The Poissonian bounds generalize those obtained...... for perturbations of fractional powers of the Laplacian. In the selfadjoint case, extensions to t∈C+  are studied. In particular, our results apply to the Dirichlet-to-Neumann semigroup....

Attributed community mining using joint general non-negative matrix factorization with graph Laplacian

Science.gov (United States)

Chen, Zigang; Li, Lixiang; Peng, Haipeng; Liu, Yuhong; Yang, Yixian

2018-04-01

Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian (LJGNMF) to implement community mining of complex social networks with link and attribute information according to different application needs. Theoretical derivation result shows that the proposed LJGNMF is fully compatible with previous methods of integrating traditional NMF and symmetric NMF. In addition, experimental results show that the proposed LJGNMF can meet the needs of different community minings by adjusting its parameters, and the effect is better than traditional NMF in the community vertices attributes entropy.

Conformal invariant powers of the Laplacian, Fefferman-Graham ambient metric and Ricci gauging

International Nuclear Information System (INIS)

Manvelyan, Ruben; Mkrtchyan, Karapet; Mkrtchyan, Ruben

2007-01-01

The hierarchy of conformally invariant kth powers of the Laplacian acting on a scalar field with scaling dimensions Δ (k) =k-d/2, k=1,2,3, as obtained in the recent work [R. Manvelyan, D.H. Tchrakian, Phys. Lett. B 644 (2007) 370, (hep-th/0611077)] is rederived using the Fefferman-Graham (d+2)-dimensional ambient space approach. The corresponding mysterious 'holographic' structure of these operators is clarified. We explore also the (d+2)-dimensional ambient space origin of the Ricci gauging procedure proposed by A. Iorio, L. O'Raifeartaigh, I. Sachs and C. Wiesendanger as another method of constructing the Weyl invariant Lagrangians. The corresponding gauged ambient metric, Fefferman-Graham expansion and extended Penrose-Brown-Henneaux transformations are proposed and analyzed

A Variance Minimization Criterion to Feature Selection Using Laplacian Regularization.

Science.gov (United States)

He, Xiaofei; Ji, Ming; Zhang, Chiyuan; Bao, Hujun

2011-10-01

In many information processing tasks, one is often confronted with very high-dimensional data. Feature selection techniques are designed to find the meaningful feature subset of the original features which can facilitate clustering, classification, and retrieval. In this paper, we consider the feature selection problem in unsupervised learning scenarios, which is particularly difficult due to the absence of class labels that would guide the search for relevant information. Based on Laplacian regularized least squares, which finds a smooth function on the data manifold and minimizes the empirical loss, we propose two novel feature selection algorithms which aim to minimize the expected prediction error of the regularized regression model. Specifically, we select those features such that the size of the parameter covariance matrix of the regularized regression model is minimized. Motivated from experimental design, we use trace and determinant operators to measure the size of the covariance matrix. Efficient computational schemes are also introduced to solve the corresponding optimization problems. Extensive experimental results over various real-life data sets have demonstrated the superiority of the proposed algorithms.

On the Symbol Error Rate of M-ary MPSK over Generalized Fading Channels with Additive Laplacian Noise

KAUST Repository

Soury, Hamza

2015-01-07

This work considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox’s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations [1].

On the Symbol Error Rate of M-ary MPSK over Generalized Fading Channels with Additive Laplacian Noise

KAUST Repository

Soury, Hamza; Alouini, Mohamed-Slim

2015-01-01

This work considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox’s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations [1].

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain.

Science.gov (United States)

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

Directory of Open Access Journals (Sweden)

Hossein Rabbani

2013-01-01

Full Text Available In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

A simple approximation to the bivariate normal distribution with large correlation coefficient

NARCIS (Netherlands)

Albers, Willem/Wim; Kallenberg, W.C.M.

1994-01-01

The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the

On a Volume Constrained for the First Eigenvalue of the P-Laplacian Operator

International Nuclear Information System (INIS)

Ly, Idrissa

2009-10-01

In this paper, we are interested in a shape optimization problem which consists in minimizing the functional that associates to an open set the first eigenvalue for p-Laplacian operator with homogeneous boundary condition. The minimum is taken among all open subsets with prescribed measure of a given bounded domain. We study an existence result for the associate variational problem. Our technique consists in enlarging the class of admissible functions to the whole space W 0 1,p (D), penalizing those functions whose level sets have a measure which is less than those required. In fact, we study the minimizers of a family of penalized functionals J λ , λ > 0 showing they are Hoelder continuous. And we prove that such functions minimize the initial problem provided the penalization parameter λ is large enough. (author)

On the symbol error rate of M-ary MPSK over generalized fading channels with additive Laplacian noise

KAUST Repository

Soury, Hamza

2014-06-01

This paper considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox\\'s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations. © 2014 IEEE.

On the symbol error rate of M-ary MPSK over generalized fading channels with additive Laplacian noise

KAUST Repository

Soury, Hamza; Alouini, Mohamed-Slim

2014-01-01

This paper considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox's H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations. © 2014 IEEE.

On minimum divergence adaptation of discrete bivariate distributions to given marginals

Czech Academy of Sciences Publication Activity Database

Vajda, Igor; van der Meulen, E. C.

2005-01-01

Roč. 51, č. 1 (2005), s. 313-320 ISSN 0018-9448 R&D Projects: GA ČR GA201/02/1391; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : approximation of contingency tables * bivariate discrete distributions * minimization of divergences Subject RIV: BD - Theory of Information Impact factor: 2.183, year: 2005

A Liouville type theorem for Lane-Emden systems involving the fractional Laplacian

Science.gov (United States)

Quaas, Alexander; Xia, Aliang

2016-08-01

We establish a Liouville type theorem for the fractional Lane-Emden system: {(-Δ)αu=vqin  RN,(-Δ)αv=upin  RN, where α \\in (0,1) , N>2α and p, q are positive real numbers and in an appropriate new range. To prove our result we will use the local realization of fractional Laplacian, which can be constructed as a Dirichlet-to-Neumann operator of a degenerate elliptic equation in the spirit of Caffarelli and Silvestre (2007 Commun. PDE 32 1245-60). Our proof is based on a monotonicity argument for suitable transformed functions and the method of moving planes in a half infinite cylinder ({IR}× S+N , where S+N is the half unit sphere in {{{R}}N+1} ) based on maximum principles which are obtained by barrier functions and a coupling argument using a fractional Sobolev trace inequality.

Morphology of Laplacian growth processes and statistics of equivalent many-body systems

International Nuclear Information System (INIS)

Blumenfeld, R.

1994-01-01

The authors proposes a theory for the nonlinear evolution of two dimensional interfaces in Laplacian fields. The growing region is conformally mapped onto the unit disk, generating an equivalent many-body system whose dynamics and statistics are studied. The process is shown to be Hamiltonian, with the Hamiltonian being the imaginary part of the complex electrostatic potential. Surface effects are introduced through the Hamiltonian as an external field. An extension to a continuous density of particles is presented. The results are used to study the morphology of the interface using statistical mechanics for the many-body system. The distribution of the curvature and the moments of the growth probability along the interface are calculated exactly from the distribution of the particles. In the dilute limit, the distribution of the curvature is shown to develop algebraic tails, which may, for the first time, explain the origin of fractality in diffusion controlled processes

A bivariate space-time downscaler under space and time misalignment.

Science.gov (United States)

Berrocal, Veronica J; Gelfand, Alan E; Holland, David M

2010-12-01

Ozone and particulate matter PM(2.5) are co-pollutants that have long been associated with increased public health risks. Information on concentration levels for both pollutants come from two sources: monitoring sites and output from complex numerical models that produce concentration surfaces over large spatial regions. In this paper, we offer a fully-model based approach for fusing these two sources of information for the pair of co-pollutants which is computationally feasible over large spatial regions and long periods of time. Due to the association between concentration levels of the two environmental contaminants, it is expected that information regarding one will help to improve prediction of the other. Misalignment is an obvious issue since the monitoring networks for the two contaminants only partly intersect and because the collection rate for PM(2.5) is typically less frequent than that for ozone.Extending previous work in Berrocal et al. (2009), we introduce a bivariate downscaler that provides a flexible class of bivariate space-time assimilation models. We discuss computational issues for model fitting and analyze a dataset for ozone and PM(2.5) for the ozone season during year 2002. We show a modest improvement in predictive performance, not surprising in a setting where we can anticipate only a small gain.

Automatic Seizure Detection in Rats Using Laplacian EEG and Verification with Human Seizure Signals

Science.gov (United States)

Feltane, Amal; Boudreaux-Bartels, G. Faye; Besio, Walter

2012-01-01

Automated detection of seizures is still a challenging problem. This study presents an approach to detect seizure segments in Laplacian electroencephalography (tEEG) recorded from rats using the tripolar concentric ring electrode (TCRE) configuration. Three features, namely, median absolute deviation, approximate entropy, and maximum singular value were calculated and used as inputs into two different classifiers: support vector machines and adaptive boosting. The relative performance of the extracted features on TCRE tEEG was examined. Results are obtained with an overall accuracy between 84.81 and 96.51%. In addition to using TCRE tEEG data, the seizure detection algorithm was also applied to the recorded EEG signals from Andrzejak et al. database to show the efficiency of the proposed method for seizure detection. PMID:23073989

Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

Science.gov (United States)

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.

The bivariate probit model of uncomplicated control of tumor: a heuristic exposition of the methodology

International Nuclear Information System (INIS)

Herbert, Donald

1997-01-01

Purpose: To describe the concept, models, and methods for the construction of estimates of joint probability of uncomplicated control of tumors in radiation oncology. Interpolations using this model can lead to the identification of more efficient treatment regimens for an individual patient. The requirement to find the treatment regimen that will maximize the joint probability of uncomplicated control of tumors suggests a new class of evolutionary experimental designs--Response Surface Methods--for clinical trials in radiation oncology. Methods and Materials: The software developed by Lesaffre and Molenberghs is used to construct bivariate probit models of the joint probability of uncomplicated control of cancer of the oropharynx from a set of 45 patients for each of whom the presence/absence of recurrent tumor (the binary event E-bar 1 /E 1 ) and the presence/absence of necrosis (the binary event E 2 /E-bar 2 ) of the normal tissues of the target volume is recorded, together with the treatment variables dose, time, and fractionation. Results: The bivariate probit model can be used to select a treatment regime that will give a specified probability, say P(S) = 0.60, of uncomplicated control of tumor by interpolation within a set of treatment regimes with known outcomes of recurrence and necrosis. The bivariate probit model can be used to guide a sequence of clinical trials to find the maximum probability of uncomplicated control of tumor for patients in a given prognostic stratum using Response Surface methods by extrapolation from an initial set of treatment regimens. Conclusions: The design of treatments for individual patients and the design of clinical trials might be improved by use of a bivariate probit model and Response Surface Methods

Technical note: Towards a continuous classification of climate using bivariate colour mapping

NARCIS (Netherlands)

Teuling, A.J.

2011-01-01

Climate is often defined in terms of discrete classes. Here I use bivariate colour mapping to show that the global distribution of K¨oppen-Geiger climate classes can largely be reproduced by combining the simple means of two key states of the climate system 5 (i.e., air temperature and relative

The Path Resistance Method for Bounding the Smallest Nontrivial Eigenvalue of a Laplacian

Science.gov (United States)

Guattery, Stephen; Leighton, Tom; Miller, Gary L.

1997-01-01

We introduce the path resistance method for lower bounds on the smallest nontrivial eigenvalue of the Laplacian matrix of a graph. The method is based on viewing the graph in terms of electrical circuits; it uses clique embeddings to produce lower bounds on lambda(sub 2) and star embeddings to produce lower bounds on the smallest Rayleigh quotient when there is a zero Dirichlet boundary condition. The method assigns priorities to the paths in the embedding; we show that, for an unweighted tree T, using uniform priorities for a clique embedding produces a lower bound on lambda(sub 2) that is off by at most an 0(log diameter(T)) factor. We show that the best bounds this method can produce for clique embeddings are the same as for a related method that uses clique embeddings and edge lengths to produce bounds.

Twin Positive Solutions of a Nonlinear m-Point Boundary Value Problem for Third-Order p-Laplacian Dynamic Equations on Time Scales

Directory of Open Access Journals (Sweden)

Wei Han

2008-01-01

Full Text Available Several existence theorems of twin positive solutions are established for a nonlinear m-point boundary value problem of third-order p-Laplacian dynamic equations on time scales by using a fixed point theorem. We present two theorems and four corollaries which generalize the results of related literature. As an application, an example to demonstrate our results is given. The obtained conditions are different from some known results.

Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

Science.gov (United States)

Wali, Behram; Khattak, Asad J; Xu, Jingjing

2018-01-01

The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability

A method of moments to estimate bivariate survival functions: the copula approach

Directory of Open Access Journals (Sweden)

Silvia Angela Osmetti

2013-05-01

Full Text Available In this paper we discuss the problem on parametric and non parametric estimation of the distributions generated by the Marshall-Olkin copula. This copula comes from the Marshall-Olkin bivariate exponential distribution used in reliability analysis. We generalize this model by the copula and different marginal distributions to construct several bivariate survival functions. The cumulative distribution functions are not absolutely continuous and they unknown parameters are often not be obtained in explicit form. In order to estimate the parameters we propose an easy procedure based on the moments. This method consist in two steps: in the first step we estimate only the parameters of marginal distributions and in the second step we estimate only the copula parameter. This procedure can be used to estimate the parameters of complex survival functions in which it is difficult to find an explicit expression of the mixed moments. Moreover it is preferred to the maximum likelihood one for its simplex mathematic form; in particular for distributions whose maximum likelihood parameters estimators can not be obtained in explicit form.

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Science.gov (United States)

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Holder continuity of bounded weak solutions to generalized parabolic p-Laplacian equations II: singular case

Directory of Open Access Journals (Sweden)

Sukjung Hwang

2015-11-01

Full Text Available Here we generalize quasilinear parabolic p-Laplacian type equations to obtain the prototype equation $$ u_t - \\hbox{div} \\Big(\\frac{g(|Du|}{|Du|} Du\\Big = 0, $$ where g is a nonnegative, increasing, and continuous function trapped in between two power functions $|Du|^{g_0 -1}$ and $|Du|^{g_1 -1}$ with $1

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

DEFF Research Database (Denmark)

Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L

2017-01-01

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone...... as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total...

Computational approach to Thornley's problem by bivariate operational calculus

Science.gov (United States)

Bazhlekova, E.; Dimovski, I.

2012-10-01

Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.

Transformation Laplacian metamaterials: recent advances in manipulating thermal and dc fields

International Nuclear Information System (INIS)

Han, Tiancheng; Qiu, Cheng-Wei

2016-01-01

The full control of single or even multiple physical fields has attracted intensive research attention in the past decade, thanks to the development of metamaterials and transformation optics. Significant progress has been made in vector fields (e.g., optics, electromagnetics, and acoustics), leading to a host of strikingly functional metamaterials, such as invisibility cloaks, illusion devices, concentrators, and rotators. However, metamaterials in vector fields, designed through coordinate transformation of Maxwell’s equations, usually require extreme parameters and impose challenges on the actual realization. In this context, metamaterials in scalar fields (e.g., thermal and dc fields), which are mostly governed by the Laplace equation, lead to more plausible and facile implementations, since there are native insulators and excellent conductors (serving as two extreme cases). This paper therefore is particularly dedicated to reviewing the most recent advances in Laplacian metamaterials in manipulating thermal (both transient and steady states) and dc fields, separately and (or) simultaneously. We focus on the theory, design, and realization of thermal/dc functional metamaterials that can be used to control heat flux and electric current at will. We also provide an outlook toward the challenges and future directions in this fascinating area. (review)

Transformation Laplacian metamaterials: recent advances in manipulating thermal and dc fields

Science.gov (United States)

Han, Tiancheng; Qiu, Cheng-Wei

2016-04-01

The full control of single or even multiple physical fields has attracted intensive research attention in the past decade, thanks to the development of metamaterials and transformation optics. Significant progress has been made in vector fields (e.g., optics, electromagnetics, and acoustics), leading to a host of strikingly functional metamaterials, such as invisibility cloaks, illusion devices, concentrators, and rotators. However, metamaterials in vector fields, designed through coordinate transformation of Maxwell’s equations, usually require extreme parameters and impose challenges on the actual realization. In this context, metamaterials in scalar fields (e.g., thermal and dc fields), which are mostly governed by the Laplace equation, lead to more plausible and facile implementations, since there are native insulators and excellent conductors (serving as two extreme cases). This paper therefore is particularly dedicated to reviewing the most recent advances in Laplacian metamaterials in manipulating thermal (both transient and steady states) and dc fields, separately and (or) simultaneously. We focus on the theory, design, and realization of thermal/dc functional metamaterials that can be used to control heat flux and electric current at will. We also provide an outlook toward the challenges and future directions in this fascinating area.

Improved stochastic estimation of quark propagation with Laplacian Heaviside smearing in lattice QCD

International Nuclear Information System (INIS)

Morningstar, C.; Lenkner, D.; Wong, C.H.; Bulava, J.; Foley, J.; Juge, K.J.; Peardon, M.

2011-08-01

A new method of stochastically estimating the low-lying effects of quark propagation is proposed which allows accurate determinations of temporal correlations of single-hadron and multi-hadron operators in lattice QCD. The method is well suited for calculations in large volumes. Contributions involving quark propagation connecting hadron sink operators at the same final time can be handled in a straightforward manner, even for a large number of final time slices. The method exploits Laplacian Heaviside (LapH) smearing. Z N noise is introduced in a novel way, and variance reduction is achieved using judiciously-chosen noise dilution projectors. The method is tested using isoscalar mesons in the scalar, pseudoscalar, and vector channels, and using the two-pion system of total isospin I=0,1,2 on large anisotropic 24 3 x 128 lattices with spatial spacing a s ∝0.12 fm and temporal spacing a t ∝0.034 fm for pion masses m π ∼ 390 and 240 MeV. (orig.)

Self-dual form of Ruijsenaars–Schneider models and ILW equation with discrete Laplacian

Directory of Open Access Journals (Sweden)

A. Zabrodin

2018-02-01

Full Text Available We discuss a self-dual form or the Bäcklund transformations for the continuous (in time variable glN Ruijsenaars–Schneider model. It is based on the first order equations in N+M complex variables which include N positions of particles and M dual variables. The latter satisfy equations of motion of the glM Ruijsenaars–Schneider model. In the elliptic case it holds M=N while for the rational and trigonometric models M is not necessarily equal to N. Our consideration is similar to the previously obtained results for the Calogero–Moser models which are recovered in the non-relativistic limit. We also show that the self-dual description of the Ruijsenaars–Schneider models can be derived from complexified intermediate long wave equation with discrete Laplacian by means of the simple pole ansatz likewise the Calogero–Moser models arise from ordinary intermediate long wave and Benjamin–Ono equations.

Carbon and oxygen isotopic ratio bi-variate distribution for marble artifacts quarry assignment

International Nuclear Information System (INIS)

Pentia, M.

1995-01-01

Statistical description, by a Gaussian bi-variate probability distribution of 13 C/ 12 C and 18 O/ 16 O isotopic ratios in the ancient marble quarries has been done and the new method for obtaining the confidence level quarry assignment for marble artifacts has been presented. (author) 8 figs., 3 tabs., 4 refs

Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering.

Science.gov (United States)

Chah, E; Hok, V; Della-Chiesa, A; Miller, J J H; O'Mara, S M; Reilly, R B

2011-02-01

This study presents a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means clustering. The performance of the proposed method was compared against previously reported algorithms such as principal component analysis (PCA) and amplitude-based feature extraction. Two types of classifier (namely k-means and classification expectation-maximization) were incorporated within the spike sorting algorithms, in order to find a suitable classifier for the feature sets. Simulated data sets and in-vivo tetrode multichannel recordings were employed to assess the performance of the spike sorting algorithms. The results show that the proposed algorithm yields significantly improved performance with mean sorting accuracy of 73% and sorting error of 10% compared to PCA which combined with k-means had a sorting accuracy of 58% and sorting error of 10%.A correction was made to this article on 22 February 2011. The spacing of the title was amended on the abstract page. No changes were made to the article PDF and the print version was unaffected.

Genetic overlap between impulsivity and alcohol dependence: a large-scale national twin study.

Science.gov (United States)

Khemiri, L; Kuja-Halkola, R; Larsson, H; Jayaram-Lindström, N

2016-04-01

Alcohol dependence is associated with increased levels of impulsivity, but the genetic and environmental underpinnings of this overlap remain unclear. The purpose of the current study was to investigate the degree to which genetic and environmental factors contribute to the overlap between alcohol dependence and impulsivity. Univariate and bivariate twin model fitting was conducted for alcohol dependence and impulsivity in a national sample of 16 819 twins born in Sweden from 1959 to 1985. The heritability estimate for alcohol dependence was 44% [95% confidence interval (CI) 31-57%] for males and 62% (95% CI 52-72%) for females. For impulsivity, the heritability was 33% (95% CI 30-36%) in males and females. The bivariate twin analysis indicated a statistically significant genetic correlation between alcohol dependence and impulsivity of 0.40 (95% CI 0.23-0.58) in males and 0.20 (95% CI 0.07-0.33) in females. The phenotypic correlation between alcohol dependence and impulsivity was 0.20 and 0.17 for males and females, respectively, and the bivariate heritability was 80% (95% CI 47-117%) for males and 53% (95% CI 19-86%) for females. The remaining variance in all models was accounted for by non-shared environmental factors. The association between alcohol dependence and impulsivity can be partially accounted for by shared genetic factors. The genetic correlation was greater in men compared with women, which may indicate different pathways to the development of alcohol dependence between sexes. The observed genetic overlap has clinical implications regarding treatment and prevention, and partially explains the substantial co-morbidity between alcohol dependence and psychiatric disorders characterized by impulsive behaviour.

Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.

Science.gov (United States)

Kuss, Oliver; Hoyer, Annika; Solms, Alexander

2014-01-15

There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration. Copyright © 2013 John Wiley & Sons, Ltd.

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

Science.gov (United States)

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-12-30

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.

Recurrence of random walks with long-range steps generated by fractional Laplacian matrices on regular networks and simple cubic lattices

Science.gov (United States)

Michelitsch, T. M.; Collet, B. A.; Riascos, A. P.; Nowakowski, A. F.; Nicolleau, F. C. G. A.

2017-12-01

We analyze a Markovian random walk strategy on undirected regular networks involving power matrix functions of the type L\\frac{α{2}} where L indicates a ‘simple’ Laplacian matrix. We refer to such walks as ‘fractional random walks’ with admissible interval 0walk. From these analytical results we establish a generalization of Polya’s recurrence theorem for fractional random walks on d-dimensional infinite lattices: The fractional random walk is transient for dimensions d > α (recurrent for d≤slantα ) of the lattice. As a consequence, for 0walk is transient for all lattice dimensions d=1, 2, .. and in the range 1≤slantα walk is transient only for lattice dimensions d≥slant 3 . The generalization of Polya’s recurrence theorem remains valid for the class of random walks with Lévy flight asymptotics for long-range steps. We also analyze the mean first passage probabilities, mean residence times, mean first passage times and global mean first passage times (Kemeny constant) for the fractional random walk. For an infinite 1D lattice (infinite ring) we obtain for the transient regime 0walk is generated by the non-diagonality of the fractional Laplacian matrix with Lévy-type heavy tailed inverse power law decay for the probability of long-range moves. This non-local and asymptotic behavior of the fractional random walk introduces small-world properties with the emergence of Lévy flights on large (infinite) lattices.

Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

Science.gov (United States)

Zscheischler, Jakob; Orth, Rene; Seneviratne, Sonia I.

2017-07-01

Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature-precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 %) than models relying directly on temperature and precipitation as predictors (36 %). Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate-crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.

A COMPARISON OF SOME ROBUST BIVARIATE CONTROL CHARTS FOR INDIVIDUAL OBSERVATIONS

Directory of Open Access Journals (Sweden)

Moustafa Omar Ahmed Abu - Shawiesh

2014-06-01

Full Text Available This paper proposed and considered some bivariate control charts to monitor individual observations from a statistical process control. Usual control charts which use mean and variance-covariance estimators are sensitive to outliers. We consider the following robust alternatives to the classical Hoteling's T2: T2MedMAD, T2MCD, T2MVE a simulation study has been conducted to compare the performance of these control charts. Two real life data are analyzed to illustrate the application of these robust alternatives.

A comparison between multivariate and bivariate analysis used in marketing research

Directory of Open Access Journals (Sweden)

Constantin, C.

2012-01-01

Full Text Available This paper is about an instrumental research conducted in order to compare the information given by two multivariate data analysis in comparison with the usual bivariate analysis. The outcomes of the research reveal that sometimes the multivariate methods use more information from a certain variable, but sometimes they use only a part of the information considered the most important for certain associations. For this reason, a researcher should use both categories of data analysis in order to obtain entirely useful information.

Positive solutions of three-point boundary-value problems for p-Laplacian singular differential equations

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George N. Galanis

2005-10-01

Full Text Available In this paper we prove the existence of positive solutions for the three-point singular boundary-value problem$$ -[phi _{p}(u']'=q(tf(t,u(t,quad 0Laplacian operator, $0

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

Science.gov (United States)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

Improved stochastic estimation of quark propagation with Laplacian Heaviside smearing in lattice QCD

Energy Technology Data Exchange (ETDEWEB)

Morningstar, C.; Lenkner, D.; Wong, C.H. [Pittsburgh Univ., PA (United States). Dept. of Physics; Bulava, J. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Foley, J. [Utah Univ., Salt Lake City, UT (United States). Dept. of Physics and Astronomy; Juge, K.J. [University of the Pacific, Stockton, CA (United States). Dept. of Physics; Peardon, M. [Trinity College, Dublin (Ireland). School of Mathematics

2011-08-15

A new method of stochastically estimating the low-lying effects of quark propagation is proposed which allows accurate determinations of temporal correlations of single-hadron and multi-hadron operators in lattice QCD. The method is well suited for calculations in large volumes. Contributions involving quark propagation connecting hadron sink operators at the same final time can be handled in a straightforward manner, even for a large number of final time slices. The method exploits Laplacian Heaviside (LapH) smearing. Z{sub N} noise is introduced in a novel way, and variance reduction is achieved using judiciously-chosen noise dilution projectors. The method is tested using isoscalar mesons in the scalar, pseudoscalar, and vector channels, and using the two-pion system of total isospin I=0,1,2 on large anisotropic 24{sup 3} x 128 lattices with spatial spacing a{sub s} {proportional_to}0.12 fm and temporal spacing a{sub t} {proportional_to}0.034 fm for pion masses m{sub {pi}} {approx} 390 and 240 MeV. (orig.)

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

KAUST Repository

Maadooliat, Mehdi; Gao, Xin; Huang, Jianhua Z.

2012-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence-structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu. edu/~madoliat/LagSVD) that can be used to produce informative animations. © The Author 2012. Published by Oxford University Press.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

KAUST Repository

Maadooliat, Mehdi

2012-08-27

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence-structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu. edu/~madoliat/LagSVD) that can be used to produce informative animations. © The Author 2012. Published by Oxford University Press.

A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times.

Science.gov (United States)

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-01-01

A generalized linear modeling framework to the analysis of responses and response times is outlined. In this framework, referred to as bivariate generalized linear item response theory (B-GLIRT), separate generalized linear measurement models are specified for the responses and the response times that are subsequently linked by cross-relations. The cross-relations can take various forms. Here, we focus on cross-relations with a linear or interaction term for ability tests, and cross-relations with a curvilinear term for personality tests. In addition, we discuss how popular existing models from the psychometric literature are special cases in the B-GLIRT framework depending on restrictions in the cross-relation. This allows us to compare existing models conceptually and empirically. We discuss various extensions of the traditional models motivated by practical problems. We also illustrate the applicability of our approach using various real data examples, including data on personality and cognitive ability.

A non-parametric conditional bivariate reference region with an application to height/weight measurements on normal girls

DEFF Research Database (Denmark)

Petersen, Jørgen Holm

2009-01-01

A conceptually simple two-dimensional conditional reference curve is described. The curve gives a decision basis for determining whether a bivariate response from an individual is "normal" or "abnormal" when taking into account that a third (conditioning) variable may influence the bivariate...... response. The reference curve is not only characterized analytically but also by geometric properties that are easily communicated to medical doctors - the users of such curves. The reference curve estimator is completely non-parametric, so no distributional assumptions are needed about the two......-dimensional response. An example that will serve to motivate and illustrate the reference is the study of the height/weight distribution of 7-8-year-old Danish school girls born in 1930, 1950, or 1970....

Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

Directory of Open Access Journals (Sweden)

J. Zscheischler

2017-07-01

Full Text Available Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature–precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 % than models relying directly on temperature and precipitation as predictors (36 %. Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate–crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.

Improving the modelling of redshift-space distortions - I. A bivariate Gaussian description for the galaxy pairwise velocity distributions

Science.gov (United States)

Bianchi, Davide; Chiesa, Matteo; Guzzo, Luigi

2015-01-01

As a step towards a more accurate modelling of redshift-space distortions (RSD) in galaxy surveys, we develop a general description of the probability distribution function of galaxy pairwise velocities within the framework of the so-called streaming model. For a given galaxy separation r, such function can be described as a superposition of virtually infinite local distributions. We characterize these in terms of their moments and then consider the specific case in which they are Gaussian functions, each with its own mean μ and dispersion σ. Based on physical considerations, we make the further crucial assumption that these two parameters are in turn distributed according to a bivariate Gaussian, with its own mean and covariance matrix. Tests using numerical simulations explicitly show that with this compact description one can correctly model redshift-space distortions on all scales, fully capturing the overall linear and non-linear dynamics of the galaxy flow at different separations. In particular, we naturally obtain Gaussian/exponential, skewed/unskewed distribution functions, depending on separation as observed in simulations and data. Also, the recently proposed single-Gaussian description of RSD is included in this model as a limiting case, when the bivariate Gaussian is collapsed to a two-dimensional Dirac delta function. We also show how this description naturally allows for the Taylor expansion of 1 + ξS(s) around 1 + ξR(r), which leads to the Kaiser linear formula when truncated to second order, explicating its connection with the moments of the velocity distribution functions. More work is needed, but these results indicate a very promising path to make definitive progress in our programme to improve RSD estimators.

Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

Science.gov (United States)

Mathias, Samuel R; Knowles, Emma E M; Kent, Jack W; McKay, D Reese; Curran, Joanne E; de Almeida, Marcio A A; Dyer, Thomas D; Göring, Harald H H; Olvera, Rene L; Duggirala, Ravi; Fox, Peter T; Almasy, Laura; Blangero, John; Glahn, David C

2016-01-01

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk. © 2015 Wiley Periodicals, Inc.

Comparison of Six Methods for the Detection of Causality in a Bivariate Time Series

Czech Academy of Sciences Publication Activity Database

Krakovská, A.; Jakubík, J.; Chvosteková, M.; Coufal, David; Jajcay, Nikola; Paluš, Milan

2018-01-01

Roč. 97, č. 4 (2018), č. článku 042207. ISSN 2470-0045 R&D Projects: GA MZd(CZ) NV15-33250A Institutional support: RVO:67985807 Keywords : comparative study * causality detection * bivariate models * Granger causality * transfer entropy * convergent cross mappings Impact factor: 2.366, year: 2016 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.042207

Bivariate- distribution for transition matrix elements in Breit-Wigner to Gaussian domains of interacting particle systems.

Science.gov (United States)

Kota, V K B; Chavda, N D; Sahu, R

2006-04-01

Interacting many-particle systems with a mean-field one-body part plus a chaos generating random two-body interaction having strength lambda exhibit Poisson to Gaussian orthogonal ensemble and Breit-Wigner (BW) to Gaussian transitions in level fluctuations and strength functions with transition points marked by lambda = lambda c and lambda = lambda F, respectively; lambda F > lambda c. For these systems a theory for the matrix elements of one-body transition operators is available, as valid in the Gaussian domain, with lambda > lambda F, in terms of orbital occupation numbers, level densities, and an integral involving a bivariate Gaussian in the initial and final energies. Here we show that, using a bivariate-t distribution, the theory extends below from the Gaussian regime to the BW regime up to lambda = lambda c. This is well tested in numerical calculations for 6 spinless fermions in 12 single-particle states.

Variation of the material laplacian of G1 with the radius of the uranium bar; Variation du laplacien matiere de G1 avec le rayon du barreau d'uranium

Energy Technology Data Exchange (ETDEWEB)

Tanguy, P [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1957-07-01

In this report are described and interpreted some experiments, carried out in the pile G1 during a period of shut-down, which have made it possible to measure the variation of the material Laplacian of the lattice with the radius of the uranium bar. The variation of the reactivity of the pile is measured when an increasing number of fuel elements are progressively replaced in the central region by fuel elements of greater diameter; it is shown that, starting from measurements based on less than ten per cent of the total number of elements, the variation of reactivity corresponding to the replacement of all the elements can be determined; it is then easy to deduce the variations of the Laplacian. Results: the variations of the Laplacian with the uranium rod diameter are 0 (d. 26 mm), +0.065 {+-} 0.004 m{sup -2} (d. 28 mm) and +0.080 {+-} 0.008 m{sup -2} (d. 32 mm). (author) [French] Dans ce rapport sont decrites et interpretees des experiences realisees sur la pile G1 'froide', experiences qui ont permis de mesurer la variation du Laplacien matiere du reseau avec le rayon du barreau d'uranium. On mesure la variation de reactivite de la pile lorsqu'on remplace progressivement dans la region centrale un nombre croissant de cartouches par des cartouches de plus gros diametre; on montre qu'a partir de mesures portant sur moins de dix pour cent du nombre total de cartouches, on peut determiner la variation de reactivite qui correspondrait au remplacement de toutes les cartouches; il est facile d'en deduire les variations du Laplacien. Resultats: les variations du Laplacien en fonction du diametre du barreau d'uranium sont: 0 (d. 26 mm), +0.065 {+-} 0.004 m{sup -2} (d. 28 mm) and +0.080 {+-} 0.008 m{sup -2} (d. 32 mm). (auteur)

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

Science.gov (United States)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

On the construction of bivariate exponential distributions with an arbitrary correlation coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase {type distributions, The latter property is potentially important for the development hypothesis testing in linear models. Thirdly, it is very easy to simulate...

Evolution of association between renal and liver functions while awaiting heart transplant: An application using a bivariate multiphase nonlinear mixed effects model.

Science.gov (United States)

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Barnard, John

2018-07-01

In many longitudinal follow-up studies, we observe more than one longitudinal outcome. Impaired renal and liver functions are indicators of poor clinical outcomes for patients who are on mechanical circulatory support and awaiting heart transplant. Hence, monitoring organ functions while waiting for heart transplant is an integral part of patient management. Longitudinal measurements of bilirubin can be used as a marker for liver function and glomerular filtration rate for renal function. We derive an approximation to evolution of association between these two organ functions using a bivariate nonlinear mixed effects model for continuous longitudinal measurements, where the two submodels are linked by a common distribution of time-dependent latent variables and a common distribution of measurement errors.

A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League

NARCIS (Netherlands)

Koopman, S.J.; Lit, R.

2015-01-01

Summary: We develop a statistical model for the analysis and forecasting of football match results which assumes a bivariate Poisson distribution with intensity coefficients that change stochastically over time. The dynamic model is a novelty in the statistical time series analysis of match results

Bivariate pointing movements on large touch screens: investigating the validity of a refined Fitts' Law.

Science.gov (United States)

Bützler, Jennifer; Vetter, Sebastian; Jochems, Nicole; Schlick, Christopher M

2012-01-01

On the basis of three empirical studies Fitts' Law was refined for bivariate pointing tasks on large touch screens. In the first study different target width parameters were investigated. The second study considered the effect of the motion angle. Based on the results of the two studies a refined model for movement time in human-computer interaction was formulated. A third study, which is described here in detail, concerns the validation of the refined model. For the validation study 20 subjects had to execute a bivariate pointing task on a large touch screen. In the experimental task 250 rectangular target objects were displayed at a randomly chosen position on the screen covering a broad range of ID values (ID= [1.01; 4.88]). Compared to existing refinements of Fitts' Law, the new model shows highest predictive validity. A promising field of application of the model is the ergonomic design and evaluation of project management software. By using the refined model, software designers can calculate a priori the appropriate angular position and the size of buttons, menus or icons.

Automatic arrival time detection for earthquakes based on Modified Laplacian of Gaussian filter

Science.gov (United States)

Saad, Omar M.; Shalaby, Ahmed; Samy, Lotfy; Sayed, Mohammed S.

2018-04-01

Precise identification of onset time for an earthquake is imperative in the right figuring of earthquake's location and different parameters that are utilized for building seismic catalogues. P-wave arrival detection of weak events or micro-earthquakes cannot be precisely determined due to background noise. In this paper, we propose a novel approach based on Modified Laplacian of Gaussian (MLoG) filter to detect the onset time even in the presence of very weak signal-to-noise ratios (SNRs). The proposed algorithm utilizes a denoising-filter algorithm to smooth the background noise. In the proposed algorithm, we employ the MLoG mask to filter the seismic data. Afterward, we apply a Dual-threshold comparator to detect the onset time of the event. The results show that the proposed algorithm can detect the onset time for micro-earthquakes accurately, with SNR of -12 dB. The proposed algorithm achieves an onset time picking accuracy of 93% with a standard deviation error of 0.10 s for 407 field seismic waveforms. Also, we compare the results with short and long time average algorithm (STA/LTA) and the Akaike Information Criterion (AIC), and the proposed algorithm outperforms them.

Selection effects in the bivariate brightness distribution for spiral galaxies

International Nuclear Information System (INIS)

Phillipps, S.; Disney, M.

1986-01-01

The joint distribution of total luminosity and characteristic surface brightness (the bivariate brightness distribution) is investigated for a complete sample of spiral galaxies in the Virgo cluster. The influence of selection and physical limits of various kinds on the apparent distribution are detailed. While the distribution of surface brightness for bright galaxies may be genuinely fairly narrow, faint galaxies exist right across the (quite small) range of accessible surface brightnesses so no statement can be made about the true extent of the distribution. The lack of high surface brightness bright galaxies in the Virgo sample relative to an overall RC2 sample (mostly field galaxies) supports the contention that the star-formation rate is reduced in the inner region of the cluster for environmental reasons. (author)

Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2015-01-01

Roč. 431, č. 1 (2015), s. 124-127 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : Correlations * Power- law cross-correlations * Bivariate Hurst exponent * Spectrum coherence Subject RIV: AH - Economics Impact factor: 1.785, year: 2015 http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452314.pdf

Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

Energy Technology Data Exchange (ETDEWEB)

Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

2016-07-01

Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

Science.gov (United States)

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of bivariate mapping for hydrological classification and analysis of temporal change and scale effects in Switzerland

NARCIS (Netherlands)

Speich, Matthias J.R.; Bernhard, Luzi; Teuling, Ryan; Zappa, Massimiliano

2015-01-01

Hydrological classification schemes are important tools for assessing the impacts of a changing climate on the hydrology of a region. In this paper, we present bivariate mapping as a simple means of classifying hydrological data for a quantitative and qualitative assessment of temporal change.

Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes

Directory of Open Access Journals (Sweden)

Ling-Yun Dai

2017-01-01

Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

Science.gov (United States)

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males.

Directory of Open Access Journals (Sweden)

Yao-Zhong Liu

2009-08-01

Full Text Available Current genome-wide association studies (GWAS are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI, with the osteoporosis risk phenotype, hip bone mineral density (BMD, scanning approximately 380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6 gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82x10(-7 and 1.47x10(-6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the approximately 380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS cohort containing 3,355 Caucasians (1,370 males and 1,985 females from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

Science.gov (United States)

Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249

SU-F-I-19: MRI Positive Contrast Visualization of Prostate Brachytherapy Seeds Using An Integrated Laplacian-Based Phase Processing

Energy Technology Data Exchange (ETDEWEB)

Soliman, A; Safigholi, H [Sunnybrook Research Institute, Toronto, ON (Canada); Sunnybrook Health Sciences Center, Toronto, ON (Canada); Nosrati, R [Sunnybrook Health Sciences Center, Toronto, ON (Canada); Ryerson University, Toronto, ON (Canada); Owrangi, A; Morton, G [Sunnybrook Health Sciences Center, Toronto, ON (Canada); University of Toronto, Toronto, ON (Canada); Song, W [Sunnybrook Research Institute, Toronto, ON (Canada); Sunnybrook Health Sciences Center, Toronto, ON (Canada); Ryerson University, Toronto, ON (Canada); University of Toronto, Toronto, ON (Canada)

2016-06-15

Purpose: To propose a new method that provides a positive contrast visualization of the prostate brachytherapy seeds using the phase information from MR images. Additionally, the feasibility of using the processed phase information to distinguish seeds from calcifications is explored. Methods: A gel phantom was constructed using 2% agar dissolved in 1 L of distilled water. Contrast agents were added to adjust the relaxation times. Four iodine-125 (Eckert & Ziegler SML86999) dummy seeds were placed at different orientations with respect to the main magnetic field (B0). Calcifications were obtained from a sheep femur cortical bone due to its close similarity to human bone tissue composition. Five samples of calcifications were shaped into different dimensions with lengths ranging between 1.2 – 6.1 mm.MR imaging was performed on a 3T Philips Achieva using an 8-channel head coil. Eight images were acquired at eight echo-times using a multi-gradient echo sequence. Spatial resolution was 0.7 × 0.7 × 2 mm, TR/TE/dTE = 20.0/2.3/2.3 ms and BW = 541 Hz/pixel. Complex images were acquired and fed into a two-step processing pipeline: the first includes phase unwrapping and background phase removal using Laplacian operator (Wei et al. 2013). The second step applies a specific phase mask on the resulting tissue phase from the first step to provide the desired positive contrast of the seeds and to, potentially, differentiate them from the calcifications. Results: The phase-processing was performed in less than 30 seconds. The proposed method has successfully resulted in a positive contrast of the brachytherapy seeds. Additionally, the final processed phase image showed difference between the appearance of seeds and calcifications. However, the shape of the seeds was slightly distorted compared to the original dimensions. Conclusion: It is feasible to provide a positive contrast of the seeds from MR images using Laplacian operator-based phase processing.

SNPMClust: Bivariate Gaussian Genotype Clustering and Calling for Illumina Microarrays

Directory of Open Access Journals (Sweden)

Stephen W. Erickson

2016-07-01

Full Text Available SNPMClust is an R package for genotype clustering and calling with Illumina microarrays. It was originally developed for studies using the GoldenGate custom genotyping platform but can be used with other Illumina platforms, including Infinium BeadChip. The algorithm first rescales the fluorescent signal intensity data, adds empirically derived pseudo-data to minor allele genotype clusters, then uses the package mclust for bivariate Gaussian model fitting. We compared the accuracy and sensitivity of SNPMClust to that of GenCall, Illumina's proprietary algorithm, on a data set of 94 whole-genome amplified buccal (cheek swab DNA samples. These samples were genotyped on a custom panel which included 1064 SNPs for which the true genotype was known with high confidence. SNPMClust produced uniformly lower false call rates over a wide range of overall call rates.

Attention deficit hyperactivity disorder in cocaine-dependent adults: a psychiatric comorbidity analysis.

Science.gov (United States)

Daigre, Constanza; Roncero, Carlos; Grau-López, Lara; Martínez-Luna, Nieves; Prat, Gemma; Valero, Sergi; Tejedor, Rosa; Ramos-Quiroga, Josep A; Casas, Miguel

2013-01-01

Attention deficit hyperactivity disorder (ADHD) is highly prevalent among drug abusers. We studied the psychiatric comorbidity and characteristics of cocaine use in relation to the presence of ADHD among patients with cocaine dependence. A total of 200 cocaine-dependent patients attending an Outpatient Drug Clinic participated in the study. A systematic evaluation of ADHD (CAADID-II), the severity of addiction (EuropASI) and other axes I and II psychiatric disorders was made (SCID-I and SCID-II). A descriptive, bivariate, and multivariate analysis of the data was performed. In the multivariate analysis, the identified risk factors for the development of ADHD were a history of behavioral disorder in childhood (OR: 3.04), a lifetime history of cannabis dependence in the course of life (OR: 2.68), and age at the start of treatment (OR: 1.08). The bivariate analysis showed ADHD to be associated with other factors such as male gender, age at start of cocaine use and dependence, the amount of cocaine consumed weekly, increased occupational alteration, alcohol consumption, general psychological discomfort, depressive disorder, and antisocial personality disorder. We conclude that ADHD is associated with increased psychiatric comorbidity and greater severity of addiction. Copyright © American Academy of Addiction Psychiatry.

Time-varying extreme value dependence with application to leading European stock markets

KAUST Repository

Castro-Camilo, Daniela; de Carvalho, Miguel; Wadsworth, Jennifer

2018-01-01

Extremal dependence between international stock markets is of particular interest in today’s global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.

Time-varying extreme value dependence with application to leading European stock markets

KAUST Repository

Castro-Camilo, Daniela

2018-03-09

Extremal dependence between international stock markets is of particular interest in today’s global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.

Detection of anomaly in human retina using Laplacian Eigenmaps and vectorized matched filtering

Science.gov (United States)

Yacoubou Djima, Karamatou A.; Simonelli, Lucia D.; Cunningham, Denise; Czaja, Wojciech

2015-03-01

We present a novel method for automated anomaly detection on auto fluorescent data provided by the National Institute of Health (NIH). This is motivated by the need for new tools to improve the capability of diagnosing macular degeneration in its early stages, track the progression over time, and test the effectiveness of new treatment methods. In previous work, macular anomalies have been detected automatically through multiscale analysis procedures such as wavelet analysis or dimensionality reduction algorithms followed by a classification algorithm, e.g., Support Vector Machine. The method that we propose is a Vectorized Matched Filtering (VMF) algorithm combined with Laplacian Eigenmaps (LE), a nonlinear dimensionality reduction algorithm with locality preserving properties. By applying LE, we are able to represent the data in the form of eigenimages, some of which accentuate the visibility of anomalies. We pick significant eigenimages and proceed with the VMF algorithm that classifies anomalies across all of these eigenimages simultaneously. To evaluate our performance, we compare our method to two other schemes: a matched filtering algorithm based on anomaly detection on single images and a combination of PCA and VMF. LE combined with VMF algorithm performs best, yielding a high rate of accurate anomaly detection. This shows the advantage of using a nonlinear approach to represent the data and the effectiveness of VMF, which operates on the images as a data cube rather than individual images.

Antiperiodic Solutions for a Generalized High-Order (p,q-Laplacian Neutral Differential System with Delays in the Critical Case

Directory of Open Access Journals (Sweden)

Yongzhi Liao

2013-01-01

Full Text Available By applying the method of coincidence degree, some criteria are established for the existence of antiperiodic solutions for a generalized high-order (p,q-Laplacian neutral differential system with delays (φp((x(t-cx(t-τ(k(m-k=F(t,xθ0(t,xθ1(t′,…,xθk(t(k,yϑ0(t,yϑ1(t′,…,yϑl(t(l, (φq((y(t-dy(t-σ(l(n-l=G(t,yμ0(t,yμ1(t′,…,yμl(t(l,xν0(t,xν1(t′,…,xνk(t(k in the critical case |c|=|d|=1. The results of this paper are completely new. Finally, an example is employed to illustrate our results.

Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

Science.gov (United States)

Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

2018-05-01

The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

A bivariate measurement error model for semicontinuous and continuous variables: Application to nutritional epidemiology.

Science.gov (United States)

Kipnis, Victor; Freedman, Laurence S; Carroll, Raymond J; Midthune, Douglas

2016-03-01

Semicontinuous data in the form of a mixture of a large portion of zero values and continuously distributed positive values frequently arise in many areas of biostatistics. This article is motivated by the analysis of relationships between disease outcomes and intakes of episodically consumed dietary components. An important aspect of studies in nutritional epidemiology is that true diet is unobservable and commonly evaluated by food frequency questionnaires with substantial measurement error. Following the regression calibration approach for measurement error correction, unknown individual intakes in the risk model are replaced by their conditional expectations given mismeasured intakes and other model covariates. Those regression calibration predictors are estimated using short-term unbiased reference measurements in a calibration substudy. Since dietary intakes are often "energy-adjusted," e.g., by using ratios of the intake of interest to total energy intake, the correct estimation of the regression calibration predictor for each energy-adjusted episodically consumed dietary component requires modeling short-term reference measurements of the component (a semicontinuous variable), and energy (a continuous variable) simultaneously in a bivariate model. In this article, we develop such a bivariate model, together with its application to regression calibration. We illustrate the new methodology using data from the NIH-AARP Diet and Health Study (Schatzkin et al., 2001, American Journal of Epidemiology 154, 1119-1125), and also evaluate its performance in a simulation study. © 2015, The International Biometric Society.

Goodness-of-fit tests with dependent observations

International Nuclear Information System (INIS)

Chicheportiche, Rémy; Bouchaud, Jean-Philippe

2011-01-01

We revisit the Kolmogorov–Smirnov and Cramér–von Mises goodness-of-fit (GoF) tests and propose a generalization to identically distributed, but dependent univariate random variables. We show that the dependence leads to a reduction of the 'effective' number of independent observations. The generalized GoF tests are not distribution-free but rather depend on all the lagged bivariate copulas. These objects, that we call 'self-copulas', encode all the non-linear temporal dependences. We introduce a specific, log-normal model for these self-copulas, for which a number of analytical results are derived. An application to financial time series is provided. As is well known, the dependence is to be long-ranged in this case, a finding that we confirm using self-copulas. As a consequence, the acceptance rates for GoF tests are substantially higher than if the returns were iid random variables

Exact Symbol Error Probability of Square M-QAM Signaling over Generalized Fading Channels subject to Additive Generalized Gaussian Noise

KAUST Repository

Soury, Hamza

2013-07-01

This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.

Error Rates of M-PAM and M-QAM in Generalized Fading and Generalized Gaussian Noise Environments

KAUST Repository

Soury, Hamza

2013-07-01

This letter investigates the average symbol error probability (ASEP) of pulse amplitude modulation and quadrature amplitude modulation coherent signaling over flat fading channels subject to additive white generalized Gaussian noise. The new ASEP results are derived in a generic closed-form in terms of the Fox H function and the bivariate Fox H function for the extended generalized-K fading case. The utility of this new general closed-form is that it includes some special fading distributions, like the Generalized-K, Nakagami-m, and Rayleigh fading and special noise distributions such as Gaussian and Laplacian. Some of these special cases are also treated and are shown to yield simplified results.

Ancestral informative marker selection and population structure visualization using sparse Laplacian eigenfunctions.

Directory of Open Access Journals (Sweden)

Jun Zhang

Full Text Available Identification of a small panel of population structure informative markers can reduce genotyping cost and is useful in various applications, such as ancestry inference in association mapping, forensics and evolutionary theory in population genetics. Traditional methods to ascertain ancestral informative markers usually require the prior knowledge of individual ancestry and have difficulty for admixed populations. Recently Principal Components Analysis (PCA has been employed with success to select SNPs which are highly correlated with top significant principal components (PCs without use of individual ancestral information. The approach is also applicable to admixed populations. Here we propose a novel approach based on our recent result on summarizing population structure by graph laplacian eigenfunctions, which differs from PCA in that it is geometric and robust to outliers. Our approach also takes advantage of the priori sparseness of informative markers in the genome. Through simulation of a ring population and the real global population sample HGDP of 650K SNPs genotyped in 940 unrelated individuals, we validate the proposed algorithm at selecting most informative markers, a small fraction of which can recover the similar underlying population structure efficiently. Employing a standard Support Vector Machine (SVM to predict individuals' continental memberships on HGDP dataset of seven continents, we demonstrate that the selected SNPs by our method are more informative but less redundant than those selected by PCA. Our algorithm is a promising tool in genome-wide association studies and population genetics, facilitating the selection of structure informative markers, efficient detection of population substructure and ancestral inference.

Preparation and bivariate analysis of suspensions of human chromosomes

Energy Technology Data Exchange (ETDEWEB)

van den Engh, G.J.; Trask, B.J.; Gray, J.W.; Langlois, R.G.; Yu, L.C.

1985-01-01

Chromosomes were isolated from a variety of human cell types using a HEPES-buffered hypotonic solution (pH 8.0) containing KCl, MgSO/sub 4/ dithioerythritol, and RNase. The chromosomes isolated by this procedure could be stained with a variety of fluorescent stains including propidium iodide, chromomycin A3, and Hoeschst 33258. Addition of sodium citrate to the stained chromosomes was found to improve the total fluorescence resolution. High-quality bivariate Hoeschst vs. chromomycin fluorescence distributions were obtained for chromosomes isolated from a human fibroblast cell strain, a human colon carcinoma cell line, and human peripheral blood lymphocyte cultures. Good flow karyotypes were also obtained from primary amniotic cell cultures. The Hoeschst vs. chromomycin flow karyotypes of a given cell line, made at different times and at dye concentrations varying over fourfold ranges, show little variation in the relative peak positions of the chromosomes. The size of the DNA in chromosomes isolated using this procedure ranges from 20 to 50 kilobases. The described isolation procedure is simple, it yields high-quality flow karyotypes, and it can be used to prepare chromosomes from clinical samples. 22 references, 7 figures, 1 table.

An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

Science.gov (United States)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

2014-10-01

Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

Science.gov (United States)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

2015-03-01

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

Extraction and prediction of indices for monsoon intraseasonal oscillations: an approach based on nonlinear Laplacian spectral analysis

Science.gov (United States)

Sabeerali, C. T.; Ajayamohan, R. S.; Giannakis, Dimitrios; Majda, Andrew J.

2017-11-01

An improved index for real-time monitoring and forecast verification of monsoon intraseasonal oscillations (MISOs) is introduced using the recently developed nonlinear Laplacian spectral analysis (NLSA) technique. Using NLSA, a hierarchy of Laplace-Beltrami (LB) eigenfunctions are extracted from unfiltered daily rainfall data from the Global Precipitation Climatology Project over the south Asian monsoon region. Two modes representing the full life cycle of the northeastward-propagating boreal summer MISO are identified from the hierarchy of LB eigenfunctions. These modes have a number of advantages over MISO modes extracted via extended empirical orthogonal function analysis including higher memory and predictability, stronger amplitude and higher fractional explained variance over the western Pacific, Western Ghats, and adjoining Arabian Sea regions, and more realistic representation of the regional heat sources over the Indian and Pacific Oceans. Real-time prediction of NLSA-derived MISO indices is demonstrated via extended-range hindcasts based on NCEP Coupled Forecast System version 2 operational output. It is shown that in these hindcasts the NLSA MISO indices remain predictable out to ˜3 weeks.

Effect of catchment properties and flood generation regime on copula selection for bivariate flood frequency analysis

Science.gov (United States)

Filipova, Valeriya; Lawrence, Deborah; Klempe, Harald

2018-02-01

Applying copula-based bivariate flood frequency analysis is advantageous because the results provide information on both the flood peak and volume. More data are, however, required for such an analysis, and it is often the case that only data series with a limited record length are available. To overcome this issue of limited record length, data regarding climatic and geomorphological properties can be used to complement statistical methods. In this paper, we present a study of 27 catchments located throughout Norway, in which we assess whether catchment properties, flood generation processes and flood regime have an effect on the correlation between flood peak and volume and, in turn, on the selection of copulas. To achieve this, the annual maximum flood events were first classified into events generated primarily by rainfall, snowmelt or a combination of these. The catchments were then classified into flood regime, depending on the predominant flood generation process producing the annual maximum flood events. A contingency table and Fisher's exact test were used to determine the factors that affect the selection of copulas in the study area. The results show that the two-parameter copulas BB1 and BB7 are more commonly selected in catchments with high steepness, high mean annual runoff and rainfall flood regime. These findings suggest that in these types of catchments, the dependence structure between flood peak and volume is more complex and cannot be modeled effectively using a one-parameter copula. The results illustrate that by relating copula types to flood regime and catchment properties, additional information can be supplied for selecting copulas in catchments with limited data.

BIVARIATE SYMMETRICAL STATISTICS OF LONG-RANGE DEPENDENT OBSERVATIONS

NARCIS (Netherlands)

DEHLING, H; TAQQU, MS

Let (X(j))j infinity = 1 be a stationary, mean-zero Gaussian sequence with covariances r(k) = EX(k+1)X1 satisfying r(0) = 1 and r(k) = k-D L(k) where D is small and L is slowly varying at infinity. Consider the sequence Y(j) = G(X(j)), j = 1,2,..., where G is any measurable function. We obtain the

Computation of Surface Laplacian for tri-polar ring electrodes on high-density realistic geometry head model.

Science.gov (United States)

Junwei Ma; Han Yuan; Sunderam, Sridhar; Besio, Walter; Lei Ding

2017-07-01

Neural activity inside the human brain generate electrical signals that can be detected on the scalp. Electroencephalograph (EEG) is one of the most widely utilized techniques helping physicians and researchers to diagnose and understand various brain diseases. Due to its nature, EEG signals have very high temporal resolution but poor spatial resolution. To achieve higher spatial resolution, a novel tri-polar concentric ring electrode (TCRE) has been developed to directly measure Surface Laplacian (SL). The objective of the present study is to accurately calculate SL for TCRE based on a realistic geometry head model. A locally dense mesh was proposed to represent the head surface, where the local dense parts were to match the small structural components in TCRE. Other areas without dense mesh were used for the purpose of reducing computational load. We conducted computer simulations to evaluate the performance of the proposed mesh and evaluated possible numerical errors as compared with a low-density model. Finally, with achieved accuracy, we presented the computed forward lead field of SL for TCRE for the first time in a realistic geometry head model and demonstrated that it has better spatial resolution than computed SL from classic EEG recordings.

A view on coupled cluster perturbation theory using a bivariational Lagrangian formulation.

Science.gov (United States)

Kristensen, Kasper; Eriksen, Janus J; Matthews, Devin A; Olsen, Jeppe; Jørgensen, Poul

2016-02-14

We consider two distinct coupled cluster (CC) perturbation series that both expand the difference between the energies of the CCSD (CC with single and double excitations) and CCSDT (CC with single, double, and triple excitations) models in orders of the Møller-Plesset fluctuation potential. We initially introduce the E-CCSD(T-n) series, in which the CCSD amplitude equations are satisfied at the expansion point, and compare it to the recently developed CCSD(T-n) series [J. J. Eriksen et al., J. Chem. Phys. 140, 064108 (2014)], in which not only the CCSD amplitude, but also the CCSD multiplier equations are satisfied at the expansion point. The computational scaling is similar for the two series, and both are term-wise size extensive with a formal convergence towards the CCSDT target energy. However, the two series are different, and the CCSD(T-n) series is found to exhibit a more rapid convergence up through the series, which we trace back to the fact that more information at the expansion point is utilized than for the E-CCSD(T-n) series. The present analysis can be generalized to any perturbation expansion representing the difference between a parent CC model and a higher-level target CC model. In general, we demonstrate that, whenever the parent parameters depend upon the perturbation operator, a perturbation expansion of the CC energy (where only parent amplitudes are used) differs from a perturbation expansion of the CC Lagrangian (where both parent amplitudes and parent multipliers are used). For the latter case, the bivariational Lagrangian formulation becomes more than a convenient mathematical tool, since it facilitates a different and faster convergent perturbation series than the simpler energy-based expansion.

Using bivariate latent basis growth curve analysis to better understand treatment outcome in youth with anorexia nervosa.

Science.gov (United States)

Byrne, Catherine E; Wonderlich, Joseph A; Curby, Timothy; Fischer, Sarah; Lock, James; Le Grange, Daniel

2018-04-25

This study explored the relation between eating-related obsessionality and weight restoration utilizing bivariate latent basis growth curve modelling. Eating-related obsessionality is a moderator of treatment outcome for adolescents with anorexia nervosa (AN). This study examined the degree to which the rate of change in eating-related obsessionality was associated with the rate of change in weight over time in family-based treatment (FBT) and individual therapy for AN. Data were drawn from a 2-site randomized controlled trial that compared FBT and adolescent focused therapy for AN. Bivariate latent basis growth curves were used to examine the differences of the relations between trajectories of body weight and symptoms associated with eating and weight obsessionality. In the FBT group, the slope of eating-related obsessionality scores and the slope of weight were significantly (negatively) correlated. This finding indicates that a decrease in overall eating-relating obsessionality is significantly associated with an increase in weight for individuals who received FBT. However, there was no relation between change in obsessionality scores and change in weight in the adolescent focused therapy group. Results suggest that FBT has a specific impact on both weight gain and obsessive compulsive behaviour that is distinct from individual therapy. Copyright © 2018 John Wiley & Sons, Ltd and Eating Disorders Association.

Pair copula constructions to determine the dependence structure of Treasury bond yields

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Marcelo Brutti Righi

2015-12-01

Full Text Available We estimated the dependence structure of US Treasury bonds through a pair copula construction. As a result, we verified that the variability of the yields decreases with a longer time of maturity of the bond. The yields presented strong dependence with past values, strongly positive bivariate associations between the daily variations, and prevalence of the Student's t copula in the relationships between the bonds. Furthermore, in tail associations, we identified relevant values in most of the relationships, which highlights the importance of risk management in the context of bonds diversification.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

Science.gov (United States)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Bivariate Cointegration Analysis of Energy-Economy Interactions in Iran

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Ismail Oladimeji Soile

2015-12-01

Full Text Available Fixing the prices of energy products below their opportunity cost for welfare and redistribution purposes is common with governments of many oil producing developing countries. This has often resulted in huge energy consumption in developing countries and the question that emerge is whether this increased energy consumption results in higher economic activities. Available statistics show that Iran’s economy growth shrunk for the first time in two decades from 2011 amidst the introduction of pricing reform in 2010 and 2014 suggesting a relationship between energy use and economic growth. Accordingly, the study examined the causality and the likelihood of a long term relationship between energy and economic growth in Iran. Unlike previous studies which have focused on the effects and effectiveness of the reform, the paper investigates the rationale for the reform. The study applied a bivariate cointegration time series econometric approach. The results reveals a one-way causality running from economic growth to energy with no feedback with evidence of long run connection. The implication of this is that energy conservation policy is not inimical to economic growth. This evidence lend further support for the ongoing subsidy reforms in Iran as a measure to check excessive and inefficient use of energy.

Generalization of binary tensor product schemes depends upon four parameters

International Nuclear Information System (INIS)

Bashir, R.; Bari, M.; Mustafa, G.

2018-01-01

This article deals with general formulae of parametric and non parametric bivariate subdivision scheme with four parameters. By assigning specific values to those parameters we get some special cases of existing tensor product schemes as well as a new proposed scheme. The behavior of schemes produced by the general formulae is interpolating, approximating and relaxed. Approximating bivariate subdivision schemes produce some other surfaces as compared to interpolating bivariate subdivision schemes. Polynomial reproduction and polynomial generation are desirable properties of subdivision schemes. Capability of polynomial reproduction and polynomial generation is strongly connected with smoothness, sum rules, convergence and approximation order. We also calculate the polynomial generation and polynomial reproduction of 9-point bivariate approximating subdivision scheme. Comparison of polynomial reproduction, polynomial generation and continuity of existing and proposed schemes has also been established. Some numerical examples are also presented to show the behavior of bivariate schemes. (author)

Probabilistic modeling using bivariate normal distributions for identification of flow and displacement intervals in longwall overburden

Energy Technology Data Exchange (ETDEWEB)

Karacan, C.O.; Goodman, G.V.R. [NIOSH, Pittsburgh, PA (United States). Off Mine Safety & Health Research

2011-01-15

Gob gas ventholes (GGV) are used to control methane emissions in longwall mines by capturing it within the overlying fractured strata before it enters the work environment. In order for GGVs to effectively capture more methane and less mine air, the length of the slotted sections and their proximity to top of the coal bed should be designed based on the potential gas sources and their locations, as well as the displacements in the overburden that will create potential flow paths for the gas. In this paper, an approach to determine the conditional probabilities of depth-displacement, depth-flow percentage, depth-formation and depth-gas content of the formations was developed using bivariate normal distributions. The flow percentage, displacement and formation data as a function of distance from coal bed used in this study were obtained from a series of borehole experiments contracted by the former US Bureau of Mines as part of a research project. Each of these parameters was tested for normality and was modeled using bivariate normal distributions to determine all tail probabilities. In addition, the probability of coal bed gas content as a function of depth was determined using the same techniques. The tail probabilities at various depths were used to calculate conditional probabilities for each of the parameters. The conditional probabilities predicted for various values of the critical parameters can be used with the measurements of flow and methane percentage at gob gas ventholes to optimize their performance.

Xp21 contiguous gene syndromes: Deletion quantitation with bivariate flow karyotyping allows mapping of patient breakpoints

Energy Technology Data Exchange (ETDEWEB)

McCabe, E.R.B.; Towbin, J.A. (Baylor College of Medicine, Houston, TX (United States)); Engh, G. van den; Trask, B.J. (Lawrence Livermore National Lab., CA (United States))

1992-12-01

Bivariate flow karyotyping was used to estimate the deletion sizes for a series of patients with Xp21 contiguous gene syndromes. The deletion estimates were used to develop an approximate scale for the genomic map in Xp21. The bivariate flow karyotype results were compared with clinical and molecular genetic information on the extent of the patients' deletions, and these various types of data were consistent. The resulting map spans >15 Mb, from the telomeric interval between DXS41 (99-6) and DXS68 (1-4) to a position centromeric to the ornithine transcarbamylase locus. The deletion sizing was considered to be accurate to [plus minus]1 Mb. The map provides information on the relative localization of genes and markers within this region. For example, the map suggests that the adrenal hypoplasia congenita and glycerol kinase genes are physically close to each other, are within 1-2 Mb of the telomeric end of the Duchenne muscular dystrophy (DMD) gene, and are nearer to the DMD locus than to the more distal marker DXS28 (C7). Information of this type is useful in developing genomic strategies for positional cloning in Xp21. These investigations demonstrate that the DNA from patients with Xp21 contiguous gene syndromes can be valuable reagents, not only for ordering loci and markers but also for providing an approximate scale to the map of the Xp21 region surrounding DMD. 44 refs., 3 figs.

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

Science.gov (United States)

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

A comparison of the effect of 5-bromodeoxyuridine substitution on 33258 Hoechst- and DAPI-fluorescence of isolated chromosomes by bivariate flow karyotyping

NARCIS (Netherlands)

Buys, C. H.; Mesa, J.; van der Veen, A. Y.; Aten, J. A.

1986-01-01

Application of the fluorescent DNA-intercalator propidium iodide for stabilization of the mitotic chromosome structure during isolation of chromosomes from V79 Chinese hamster cells and subsequent staining with the fluorochromes 33258 Hoechst or DAPI allowed bivariate flow karyotyping of isolated

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

Science.gov (United States)

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics

Classification of Knee Joint Vibration Signals Using Bivariate Feature Distribution Estimation and Maximal Posterior Probability Decision Criterion

Directory of Open Access Journals (Sweden)

Fang Zheng

2013-04-01

Full Text Available Analysis of knee joint vibration or vibroarthrographic (VAG signals using signal processing and machine learning algorithms possesses high potential for the noninvasive detection of articular cartilage degeneration, which may reduce unnecessary exploratory surgery. Feature representation of knee joint VAG signals helps characterize the pathological condition of degenerative articular cartilages in the knee. This paper used the kernel-based probability density estimation method to model the distributions of the VAG signals recorded from healthy subjects and patients with knee joint disorders. The estimated densities of the VAG signals showed explicit distributions of the normal and abnormal signal groups, along with the corresponding contours in the bivariate feature space. The signal classifications were performed by using the Fisher’s linear discriminant analysis, support vector machine with polynomial kernels, and the maximal posterior probability decision criterion. The maximal posterior probability decision criterion was able to provide the total classification accuracy of 86.67% and the area (Az of 0.9096 under the receiver operating characteristics curve, which were superior to the results obtained by either the Fisher’s linear discriminant analysis (accuracy: 81.33%, Az: 0.8564 or the support vector machine with polynomial kernels (accuracy: 81.33%, Az: 0.8533. Such results demonstrated the merits of the bivariate feature distribution estimation and the superiority of the maximal posterior probability decision criterion for analysis of knee joint VAG signals.

A bivariate Chebyshev spectral collocation quasilinearization method for nonlinear evolution parabolic equations.

Science.gov (United States)

Motsa, S S; Magagula, V M; Sibanda, P

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

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S. S. Motsa

2014-01-01

Full Text Available This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs. The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

Science.gov (United States)

Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

2013-04-01

The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

Which global stock indices trigger stronger contagion risk in the Vietnamese stock market? Evidence using a bivariate analysis

OpenAIRE

Wang Kuan-Min; Lai Hung-Cheng

2013-01-01

This paper extends recent investigations into risk contagion effects on stock markets to the Vietnamese stock market. Daily data spanning October 9, 2006 to May 3, 2012 are sourced to empirically validate the contagion effects between stock markets in Vietnam, and China, Japan, Singapore, and the US. To facilitate the validation of contagion effects with market-related coefficients, this paper constructs a bivariate EGARCH model of dynamic conditional correlation coefficients. Using the...

Applying Emax model and bivariate thin plate splines to assess drug interactions.

Science.gov (United States)

Kong, Maiying; Lee, J Jack

2010-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95 per cent point-wise confidence interval as well as its 95 per cent simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies.

Asymptotics of bivariate generating functions with algebraic singularities

Science.gov (United States)

Greenwood, Torin

Flajolet and Odlyzko (1990) derived asymptotic formulae the coefficients of a class of uni- variate generating functions with algebraic singularities. Gao and Richmond (1992) and Hwang (1996, 1998) extended these results to classes of multivariate generating functions, in both cases by reducing to the univariate case. Pemantle and Wilson (2013) outlined new multivariate ana- lytic techniques and used them to analyze the coefficients of rational generating functions. After overviewing these methods, we use them to find asymptotic formulae for the coefficients of a broad class of bivariate generating functions with algebraic singularities. Beginning with the Cauchy integral formula, we explicity deform the contour of integration so that it hugs a set of critical points. The asymptotic contribution to the integral comes from analyzing the integrand near these points, leading to explicit asymptotic formulae. Next, we use this formula to analyze an example from current research. In the following chapter, we apply multivariate analytic techniques to quan- tum walks. Bressler and Pemantle (2007) found a (d + 1)-dimensional rational generating function whose coefficients described the amplitude of a particle at a position in the integer lattice after n steps. Here, the minimal critical points form a curve on the (d + 1)-dimensional unit torus. We find asymptotic formulae for the amplitude of a particle in a given position, normalized by the number of steps n, as n approaches infinity. Each critical point contributes to the asymptotics for a specific normalized position. Using Groebner bases in Maple again, we compute the explicit locations of peak amplitudes. In a scaling window of size the square root of n near the peaks, each amplitude is asymptotic to an Airy function.

The use of bivariate spatial modeling of questionnaire and parasitology data to predict the distribution of Schistosoma haematobium in Coastal Kenya.

Directory of Open Access Journals (Sweden)

Hugh J W Sturrock

Full Text Available Questionnaires of reported blood in urine (BIU distributed through the existing school system provide a rapid and reliable method to classify schools according to the prevalence of Schistosoma haematobium, thereby helping in the targeting of schistosomiasis control. However, not all schools return questionnaires and it is unclear whether treatment is warranted in such schools. This study investigates the use of bivariate spatial modelling of available and multiple data sources to predict the prevalence of S. haematobium at every school along the Kenyan coast.Data from a questionnaire survey conducted by the Kenya Ministry of Education in Coast Province in 2009 were combined with available parasitological and environmental data in a Bayesian bivariate spatial model. This modeled the relationship between BIU data and environmental covariates, as well as the relationship between BIU and S. haematobium infection prevalence, to predict S. haematobium infection prevalence at all schools in the study region. Validation procedures were implemented to assess the predictive accuracy of endemicity classification.The prevalence of BIU was negatively correlated with distance to nearest river and there was considerable residual spatial correlation at small (~15 km spatial scales. There was a predictable relationship between the prevalence of reported BIU and S. haematobium infection. The final model exhibited excellent sensitivity (0.94 but moderate specificity (0.69 in identifying low (<10% prevalence schools, and had poor performance in differentiating between moderate and high prevalence schools (sensitivity 0.5, specificity 1.Schistosomiasis is highly focal and there is a need to target treatment on a school-by-school basis. The use of bivariate spatial modelling can supplement questionnaire data to identify schools requiring mass treatment, but is unable to distinguish between moderate and high prevalence schools.

Epileptic seizure prediction based on a bivariate spectral power methodology.

Science.gov (United States)

Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

2012-01-01

The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

Obtaining DDF Curves of Extreme Rainfall Data Using Bivariate Copula and Frequency Analysis

DEFF Research Database (Denmark)

Sadri, Sara; Madsen, Henrik; Mikkelsen, Peter Steen

2009-01-01

, situated near Copenhagen in Denmark. For rainfall extracted using method 2, the marginal distribution of depth was found to fit the Generalized Pareto distribution while duration was found to fit the Gamma distribution, using the method of L-moments. The volume was fit with a generalized Pareto...... with duration for a given return period and name them DDF (depth-duration-frequency) curves. The copula approach does not assume the rainfall variables are independent or jointly normally distributed. Rainfall series are extracted in three ways: (1) by maximum mean intensity; (2) by depth and duration...... distribution and the duration was fit with a Pearson type III distribution for rainfall extracted using method 3. The Clayton copula was found to be appropriate for bivariate analysis of rainfall depth and duration for both methods 2 and 3. DDF curves derived using the Clayton copula for depth and duration...

A Basic Bivariate Structure of Personality Attributes Evident Across Nine Languages.

Science.gov (United States)

Saucier, Gerard; Thalmayer, Amber Gayle; Payne, Doris L; Carlson, Robert; Sanogo, Lamine; Ole-Kotikash, Leonard; Church, A Timothy; Katigbak, Marcia S; Somer, Oya; Szarota, Piotr; Szirmák, Zsofia; Zhou, Xinyue

2014-02-01

Here, two studies seek to characterize a parsimonious common-denominator personality structure with optimal cross-cultural replicability. Personality differences are observed in all human populations and cultures, but lexicons for personality attributes contain so many distinctions that parsimony is lacking. Models stipulating the most important attributes have been formulated by experts or by empirical studies drawing on experience in a very limited range of cultures. Factor analyses of personality lexicons of nine languages of diverse provenance (Chinese, Korean, Filipino, Turkish, Greek, Polish, Hungarian, Maasai, and Senoufo) were examined, and their common structure was compared to that of several prominent models in psychology. A parsimonious bivariate model showed evidence of substantial convergence and ubiquity across cultures. Analyses involving key markers of these dimensions in English indicate that they are broad dimensions involving the overlapping content of the interpersonal circumplex, models of communion and agency, and morality/warmth and competence. These "Big Two" dimensions-Social Self-Regulation and Dynamism-provide a common-denominator model involving the two most crucial axes of personality variation, ubiquitous across cultures. The Big Two might serve as an umbrella model serving to link diverse theoretical models and associated research literatures. © 2013 Wiley Periodicals, Inc.

Local fluctuations of the signed traded volumes and the dependencies of demands: a copula analysis

Science.gov (United States)

Wang, Shanshan; Guhr, Thomas

2018-03-01

We investigate how the local fluctuations of the signed traded volumes affect the dependence of demands between stocks. We analyze the empirical dependence of demands using copulas and show that they are well described by a bivariate K copula density function. We find that large local fluctuations strongly increase the positive dependence but lower slightly the negative one in the copula density. This interesting feature is due to cross-correlations of volume imbalances between stocks. Also, we explore the asymmetries of tail dependencies of the copula density, which are moderate for the negative dependencies but strong for the positive ones. For the latter, we reveal that large local fluctuations of the signed traded volumes trigger stronger dependencies of demands than of supplies, probably indicating a bull market with persistent raising of prices.

Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

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Jaewon Kwak

2016-03-01

Full Text Available Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF per year in the Sacramento River basin could be considered a critical level of drought for water shortages.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

OpenAIRE

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D.

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture th...

Aquaculture in artificially developed wetlands in urban areas: an application of the bivariate relationship between soil and surface water in landscape ecology.

Science.gov (United States)

Paul, Abhijit

2011-01-01

Wetlands show a strong bivariate relationship between soil and surface water. Artificially developed wetlands help to build landscape ecology and make built environments sustainable. The bheries, wetlands of eastern Calcutta (India), utilize the city sewage to develop urban aquaculture that supports the local fish industries and opens a new frontier in sustainable environmental planning research.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

Science.gov (United States)

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

A bivariate optimal replacement policy for a multistate repairable system

International Nuclear Information System (INIS)

Zhang Yuanlin; Yam, Richard C.M.; Zuo, Ming J.

2007-01-01

In this paper, a deteriorating simple repairable system with k+1 states, including k failure states and one working state, is studied. It is assumed that the system after repair is not 'as good as new' and the deterioration of the system is stochastic. We consider a bivariate replacement policy, denoted by (T,N), in which the system is replaced when its working age has reached T or the number of failures it has experienced has reached N, whichever occurs first. The objective is to determine the optimal replacement policy (T,N)* such that the long-run expected profit per unit time is maximized. The explicit expression of the long-run expected profit per unit time is derived and the corresponding optimal replacement policy can be determined analytically or numerically. We prove that the optimal policy (T,N)* is better than the optimal policy N* for a multistate simple repairable system. We also show that a general monotone process model for a multistate simple repairable system is equivalent to a geometric process model for a two-state simple repairable system in the sense that they have the same structure for the long-run expected profit (or cost) per unit time and the same optimal policy. Finally, a numerical example is given to illustrate the theoretical results

An improved method for bivariate meta-analysis when within-study correlations are unknown.

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Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the

Automated nodule location and size estimation using a multi-scale Laplacian of Gaussian filtering approach.

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Jirapatnakul, Artit C; Fotin, Sergei V; Reeves, Anthony P; Biancardi, Alberto M; Yankelevitz, David F; Henschke, Claudia I

2009-01-01

Estimation of nodule location and size is an important pre-processing step in some nodule segmentation algorithms to determine the size and location of the region of interest. Ideally, such estimation methods will consistently find the same nodule location regardless of where the the seed point (provided either manually or by a nodule detection algorithm) is placed relative to the "true" center of the nodule, and the size should be a reasonable estimate of the true nodule size. We developed a method that estimates nodule location and size using multi-scale Laplacian of Gaussian (LoG) filtering. Nodule candidates near a given seed point are found by searching for blob-like regions with high filter response. The candidates are then pruned according to filter response and location, and the remaining candidates are sorted by size and the largest candidate selected. This method was compared to a previously published template-based method. The methods were evaluated on the basis of stability of the estimated nodule location to changes in the initial seed point and how well the size estimates agreed with volumes determined by a semi-automated nodule segmentation method. The LoG method exhibited better stability to changes in the seed point, with 93% of nodules having the same estimated location even when the seed point was altered, compared to only 52% of nodules for the template-based method. Both methods also showed good agreement with sizes determined by a nodule segmentation method, with an average relative size difference of 5% and -5% for the LoG and template-based methods respectively.

A Bivariate Mixture Model for Natural Antibody Levels to Human Papillomavirus Types 16 and 18: Baseline Estimates for Monitoring the Herd Effects of Immunization.

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Margaretha A Vink

Full Text Available Post-vaccine monitoring programs for human papillomavirus (HPV have been introduced in many countries, but HPV serology is still an underutilized tool, partly owing to the weak antibody response to HPV infection. Changes in antibody levels among non-vaccinated individuals could be employed to monitor herd effects of immunization against HPV vaccine types 16 and 18, but inference requires an appropriate statistical model. The authors developed a four-component bivariate mixture model for jointly estimating vaccine-type seroprevalence from correlated antibody responses against HPV16 and -18 infections. This model takes account of the correlation between HPV16 and -18 antibody concentrations within subjects, caused e.g. by heterogeneity in exposure level and immune response. The model was fitted to HPV16 and -18 antibody concentrations as measured by a multiplex immunoassay in a large serological survey (3,875 females carried out in the Netherlands in 2006/2007, before the introduction of mass immunization. Parameters were estimated by Bayesian analysis. We used the deviance information criterion for model selection; performance of the preferred model was assessed through simulation. Our analysis uncovered elevated antibody concentrations in doubly as compared to singly seropositive individuals, and a strong clustering of HPV16 and -18 seropositivity, particularly around the age of sexual debut. The bivariate model resulted in a more reliable classification of singly and doubly seropositive individuals than achieved by a combination of two univariate models, and suggested a higher pre-vaccine HPV16 seroprevalence than previously estimated. The bivariate mixture model provides valuable baseline estimates of vaccine-type seroprevalence and may prove useful in seroepidemiologic assessment of the herd effects of HPV vaccination.

Preserving differential privacy under finite-precision semantics.

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Ivan Gazeau

2013-06-01

Full Text Available The approximation introduced by finite-precision representation of continuous data can induce arbitrarily large information leaks even when the computation using exact semantics is secure. Such leakage can thus undermine design efforts aimed at protecting sensitive information. We focus here on differential privacy, an approach to privacy that emerged from the area of statistical databases and is now widely applied also in other domains. In this approach, privacy is protected by the addition of noise to a true (private value. To date, this approach to privacy has been proved correct only in the ideal case in which computations are made using an idealized, infinite-precision semantics. In this paper, we analyze the situation at the implementation level, where the semantics is necessarily finite-precision, i.e. the representation of real numbers and the operations on them, are rounded according to some level of precision. We show that in general there are violations of the differential privacy property, and we study the conditions under which we can still guarantee a limited (but, arguably, totally acceptable variant of the property, under only a minor degradation of the privacy level. Finally, we illustrate our results on two cases of noise-generating distributions: the standard Laplacian mechanism commonly used in differential privacy, and a bivariate version of the Laplacian recently introduced in the setting of privacy-aware geolocation.

Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

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Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

2017-10-01

This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

THE BIVARIATE SIZE-LUMINOSITY RELATIONS FOR LYMAN BREAK GALAXIES AT z {approx} 4-5

Energy Technology Data Exchange (ETDEWEB)

Huang, Kuang-Han; Su, Jian [Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Ferguson, Henry C. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Ravindranath, Swara, E-mail: kuanghan@pha.jhu.edu [The Inter-University Center for Astronomy and Astrophysics, Pune University Campus, Pune 411007, Maharashtra (India)

2013-03-01

We study the bivariate size-luminosity distribution of Lyman break galaxies (LBGs) selected at redshifts around 4 and 5 in GOODS and the HUDF fields. We model the size-luminosity distribution as a combination of log-normal distribution (in size) and Schechter function (in luminosity), therefore it enables a more detailed study of the selection effects. We perform extensive simulations to quantify the dropout-selection completenesses and measurement biases and uncertainties in two-dimensional size and magnitude bins, and transform the theoretical size-luminosity distribution to the expected distribution for the observed data. Using maximum-likelihood estimator, we find that the Schechter function parameters for B {sub 435}-dropouts and are consistent with the values in the literature, but the size distributions are wider than expected from the angular momentum distribution of the underlying dark matter halos. The slope of the size-luminosity (RL) relation is similar to those found for local disk galaxies, but considerably shallower than local early-type galaxies.

THE BIVARIATE SIZE-LUMINOSITY RELATIONS FOR LYMAN BREAK GALAXIES AT z ∼ 4-5

International Nuclear Information System (INIS)

Huang, Kuang-Han; Su, Jian; Ferguson, Henry C.; Ravindranath, Swara

2013-01-01

We study the bivariate size-luminosity distribution of Lyman break galaxies (LBGs) selected at redshifts around 4 and 5 in GOODS and the HUDF fields. We model the size-luminosity distribution as a combination of log-normal distribution (in size) and Schechter function (in luminosity), therefore it enables a more detailed study of the selection effects. We perform extensive simulations to quantify the dropout-selection completenesses and measurement biases and uncertainties in two-dimensional size and magnitude bins, and transform the theoretical size-luminosity distribution to the expected distribution for the observed data. Using maximum-likelihood estimator, we find that the Schechter function parameters for B 435 -dropouts and are consistent with the values in the literature, but the size distributions are wider than expected from the angular momentum distribution of the underlying dark matter halos. The slope of the size-luminosity (RL) relation is similar to those found for local disk galaxies, but considerably shallower than local early-type galaxies.

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

Science.gov (United States)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

Science.gov (United States)

Kranstauber, Bart; Safi, Kamran; Bartumeus, Frederic

2014-01-01

In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.

IDF relationships using bivariate copula for storm events in Peninsular Malaysia

Science.gov (United States)

Ariff, N. M.; Jemain, A. A.; Ibrahim, K.; Wan Zin, W. Z.

2012-11-01

SummaryIntensity-duration-frequency (IDF) curves are used in many hydrologic designs for the purpose of water managements and flood preventions. The IDF curves available in Malaysia are those obtained from univariate analysis approach which only considers the intensity of rainfalls at fixed time intervals. As several rainfall variables are correlated with each other such as intensity and duration, this paper aims to derive IDF points for storm events in Peninsular Malaysia by means of bivariate frequency analysis. This is achieved through utilizing the relationship between storm intensities and durations using the copula method. Four types of copulas; namely the Ali-Mikhail-Haq (AMH), Frank, Gaussian and Farlie-Gumbel-Morgenstern (FGM) copulas are considered because the correlation between storm intensity, I, and duration, D, are negative and these copulas are appropriate when the relationship between the variables are negative. The correlations are attained by means of Kendall's τ estimation. The analysis was performed on twenty rainfall stations with hourly data across Peninsular Malaysia. Using Akaike's Information Criteria (AIC) for testing goodness-of-fit, both Frank and Gaussian copulas are found to be suitable to represent the relationship between I and D. The IDF points found by the copula method are compared to the IDF curves yielded based on the typical IDF empirical formula of the univariate approach. This study indicates that storm intensities obtained from both methods are in agreement with each other for any given storm duration and for various return periods.

GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

Science.gov (United States)

Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

2017-12-01

Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

Strong source heat transfer simulations based on a GalerKin/Gradient - least - squares method

International Nuclear Information System (INIS)

Franca, L.P.; Carmo, E.G.D. do.

1989-05-01

Heat conduction problems with temperature-dependent strong sources are modeled by an equation with a laplacian term, a linear term and a given source distribution term. When the linear-temperature-dependent source term is much larger than the laplacian term, we have a singular perturbation problem. In this case, boundary layers are formed to satisfy the Dirichlet boundary conditions. Although this is an elliptic equation, the standard Galerkin method solution is contaminated by spurious oscillations in the neighborhood of the boundary layers. Herein we employ a Galerkin/Gradient-least-squares method which eliminates all pathological phenomena of the Galerkin method. The method is constructed by adding to the Galerkin method a mesh-dependent term obtained by the least-squares form of the gradient of the Euler-Lagrange equation. Error estimates, numerical simulations in one-and multi-dimensions are given that attest the good stability and accuracy properties of the method [pt

Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

Science.gov (United States)

Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both

Smooth time-dependent receiver operating characteristic curve estimators.

Science.gov (United States)

Martínez-Camblor, Pablo; Pardo-Fernández, Juan Carlos

2018-03-01

The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article.

Efficient anisotropic quasi-P wavefield extrapolation using an isotropic low-rank approximation

KAUST Repository

Zhang, Zhendong; Liu, Yike; Alkhalifah, Tariq Ali; Wu, Zedong

2017-01-01

efficient. A dynamic implementation of this approach decomposes the original pseudo-differential operator into a Laplacian, handled using the low-rank approximation of the spectral operator, plus an angular dependent correction factor applied in the space

The Role of Wealth and Health in Insurance Choice: Bivariate Probit Analysis in China

Directory of Open Access Journals (Sweden)

Yiding Yue

2014-01-01

Full Text Available This paper captures the correlation between the choices of health insurance and pension insurance using the bivariate probit model and then studies the effect of wealth and health on insurance choice. Our empirical evidence shows that people who participate in a health care program are more likely to participate in a pension plan at the same time, while wealth and health have different effects on the choices of the health care program and the pension program. Generally, the higher an individual’s wealth level is, the more likelihood he will participate in a health care program; but wealth has no effect on the participation of pension. Health status has opposite effects on choices of health care programs and pension plans; the poorer an individual’s health is, the more likely he is to participate in health care programs, while the better health he enjoys, the more likely he is to participate in pension plans. When the investigation scope narrows down to commercial insurance, there is only a significant effect of health status on commercial health insurance. The commercial insurance choice and the insurance choice of the agricultural population are more complicated.

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

Science.gov (United States)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

On the level order for Dirac operators

International Nuclear Information System (INIS)

Grosse, H.

1987-01-01

We start from the Dirac operator for the Coulomb potential and prove within first order perturbation theory that degenerate levels split in a definite way depending on the sign of the Laplacian of the perturbing potential. 9 refs. (Author)

A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price

Directory of Open Access Journals (Sweden)

Zhilong Wang

2014-01-01

Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.

Inference for the Bivariate and Multivariate Hidden Truncated Pareto(type II) and Pareto(type IV) Distribution and Some Measures of Divergence Related to Incompatibility of Probability Distribution

Science.gov (United States)

Ghosh, Indranil

2011-01-01

Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…

Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

Science.gov (United States)

Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

2012-01-01

Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method

Science.gov (United States)

Shaw, Stephen B.; Walter, M. Todd

2009-03-01

The Soil Conservation Service curve number (SCS-CN) method is widely used to predict storm runoff for hydraulic design purposes, such as sizing culverts and detention basins. As traditionally used, the probability of calculated runoff is equated to the probability of the causative rainfall event, an assumption that fails to account for the influence of variations in soil moisture on runoff generation. We propose a modification to the SCS-CN method that explicitly incorporates rainfall return periods and the frequency of different soil moisture states to quantify storm runoff risks. Soil moisture status is assumed to be correlated to stream base flow. Fundamentally, this approach treats runoff as the outcome of a bivariate process instead of dictating a 1:1 relationship between causative rainfall and resulting runoff volumes. Using data from the Fall Creek watershed in western New York and the headwaters of the French Broad River in the mountains of North Carolina, we show that our modified SCS-CN method improves frequency discharge predictions in medium-sized watersheds in the eastern United States in comparison to the traditional application of the method.

Modeling both of the number of pausibacillary and multibacillary leprosy patients by using bivariate poisson regression

Science.gov (United States)

Winahju, W. S.; Mukarromah, A.; Putri, S.

2015-03-01

Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.

Estimating twin concordance for bivariate competing risks twin data

DEFF Research Database (Denmark)

Scheike, Thomas; Holst, Klaus K.; Hjelmborg, Jacob B.

2014-01-01

For twin time-to-event data, we consider different concordance probabilities, such as the casewise concordance that are routinely computed as a measure of the lifetime dependence/correlation for specific diseases. The concordance probability here is the probability that both twins have experience...... events with the competing risk death. We thus aim to quantify the degree of dependence through the casewise concordance function and show a significant genetic component...... the event of interest. Under the assumption that both twins are censored at the same time, we show how to estimate this probability in the presence of right censoring, and as a consequence, we can then estimate the casewise twin concordance. In addition, we can model the magnitude of within pair dependence...... over time, and covariates may be further influential on the marginal risk and dependence structure. We establish the estimators large sample properties and suggest various tests, for example, for inferring familial influence. The method is demonstrated and motivated by specific twin data on cancer...

Assessing nicotine dependence in adolescent E-cigarette users: The 4-item Patient-Reported Outcomes Measurement Information System (PROMIS) Nicotine Dependence Item Bank for electronic cigarettes.

Science.gov (United States)

Morean, Meghan E; Krishnan-Sarin, Suchitra; S O'Malley, Stephanie

2018-04-26

Adolescent e-cigarette use (i.e., "vaping") likely confers risk for developing nicotine dependence. However, there have been no studies assessing e-cigarette nicotine dependence in youth. We evaluated the psychometric properties of the 4-item Patient-Reported Outcomes Measurement Information System Nicotine Dependence Item Bank for E-cigarettes (PROMIS-E) for assessing youth e-cigarette nicotine dependence and examined risk factors for experiencing stronger dependence symptoms. In 2017, 520 adolescent past-month e-cigarette users completed the PROMIS-E during a school-based survey (50.5% female, 84.8% White, 16.22[1.19] years old). Adolescents also reported on sex, grade, race, age at e-cigarette use onset, vaping frequency, nicotine e-liquid use, and past-month cigarette smoking. Analyses included conducting confirmatory factor analysis and examining the internal consistency of the PROMIS-E. Bivariate correlations and independent-samples t-tests were used to examine unadjusted relationships between e-cigarette nicotine dependence and the proposed risk factors. Regression models were run in which all potential risk factors were entered as simultaneous predictors of PROMIS-E scores. The single-factor structure of the PROMIS-E was confirmed and evidenced good internal consistency. Across models, larger PROMIS-E scores were associated with being in a higher grade, initiating e-cigarette use at an earlier age, vaping more frequently, using nicotine e-liquid (and higher nicotine concentrations), and smoking cigarettes. Adolescent e-cigarette users reported experiencing nicotine dependence, which was assessed using the psychometrically sound PROMIS-E. Experiencing stronger nicotine dependence symptoms was associated with characteristics that previously have been shown to confer risk for frequent vaping and tobacco cigarette dependence. Copyright © 2018 Elsevier B.V. All rights reserved.

Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors – Exploratory empirical analysis using a bivariate ordered probit model

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Behram Wali

2017-06-01

Full Text Available The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver's drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focused on investigating the simultaneous impact of socioeconomic factors, fatalities, vehicle ownership, health services and highway agency road safety policies on enforcement levels of speed limit and drink driving laws. The effectiveness of enforcement levels of speed limit and drink driving laws has been investigated through development of bivariate ordered probit model using data extricated from WHO's global status report on road safety in 2013. The consistent and intuitive parameter estimates along with statistically significant correlation between response outcomes validates the statistical supremacy of bivariate ordered probit model. The results revealed that fatalities per thousand registered vehicles, hospital beds per hundred thousand population and road safety policies are associated with a likely medium or high effectiveness of enforcement levels of speed limit and drink driving laws, respectively. Also, the model encapsulates the effect of several other agency related variables and socio-economic status on the response outcomes. Marginal effects are reported for analyzing the impact of such factors on intermediate categories of response outcomes. The results of this study are expected to provide necessary insights to elemental enforcement programs. Also, marginal effects of explanatory variables may provide useful directions for formulating effective policy countermeasures for overcoming driver's speeding and drink driving behavior.

Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

KAUST Repository

Philbin, R.

2015-05-22

This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields\\' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

KAUST Repository

Philbin, R.; Jun, M.

2015-01-01

This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

Social anxiety symptoms in alcohol-dependent outpatients: prevalence, severity and predictors

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Nicoli Tamie Yoshimi

2016-06-01

Full Text Available ABSTRACT Objectives High rates of comorbidity between social anxiety disorder (SAD and alcohol use disorders have been reported, but the predictors of this comorbidity are poorly known and most studies involve primary SAD samples. The aims were to estimate the prevalence and severity of SAD symptoms among alcohol-dependent patients and to investigate sociodemographic and clinical factors associated with SAD comorbidity, including suicidal behaviors. Methods A cross-sectional study with 53 adults who were in treatment for alcohol dependence at a Brazilian public university outpatient service. Assessment instruments Social Phobia Inventory (SPIN, Short Alcohol Dependence Data and Beck Depression Inventory. Bivariate analyses between the categorical outcome (Probable SAD: SPIN ≥ 19 and explanatory variables were conducted. Correlates of SPIN total and subscales scores (dimensional outcomes were also investigated. Results The diagnosis and treatment of alcohol dependence occurred, on average, 30 years after the onset of alcohol use and 39.6% of the 53 patients (37 men and 16 women reported alleviation of social anxiety symptoms with alcohol use. Twenty-four (45.3% patients presented probable SAD. These patients differed from non-SAD alcohol-dependent individuals by having lower income and higher frequency of depression, suicidal ideation, suicide plans and attempts. The SPIN subscales mostly associated with suicidal behaviors were social inadequacy and social inferiority. Conclusions SAD symptoms are common among help-seeking alcohol-dependent individuals and should be directly investigated and treated, since depression and suicidality are associated with this comorbidity. Prospective studies are needed to assess the impact of SAD treatment on the clinical course of alcohol dependence.

Evaluation of the Momentum Closure Schemes in MPAS-Ocean

Science.gov (United States)

Zhao, Shimei; Liu, Yudi; Liu, Wei

2018-04-01

In order to compare and evaluate the performances of the Laplacian viscosity closure, the biharmonic viscosity closure, and the Leith closure momentum schemes in the MPAS-Ocean model, a variety of physical quantities, such as the relative reference potential energy (RPE) change, the RPE time change rate (RPETCR), the grid Reynolds number, the root mean square (RMS) of kinetic energy, and the spectra of kinetic energy and enstrophy, are calculated on the basis of results of a 3D baroclinic periodic channel. Results indicate that: 1) The RPETCR demonstrates a saturation phenomenon in baroclinic eddy tests. The critical grid Reynolds number corresponding to RPETCR saturation differs between the three closures: the largest value is in the biharmonic viscosity closure, followed by that in the Laplacian viscosity closure, and that in the Leith closure is the smallest. 2) All three closures can effectively suppress spurious dianeutral mixing by reducing the grid Reynolds number under sub-saturation conditions of the RPETCR, but they can also damage certain physical processes. Generally, the damage to the rotation process is greater than that to the advection process. 3) The dissipation in the biharmonic viscosity closure is strongly dependent on scales. Most dissipation concentrates on small scales, and the energy of small-scale eddies is often transferred to large-scale kinetic energy. The viscous dissipation in the Laplacian viscosity closure is the strongest on various scales, followed by that in the Leith closure. Note that part of the small-scale kinetic energy is also transferred to large-scale kinetic energy in the Leith closure. 4) The characteristic length scale L and the dimensionless parameter D in the Leith closure are inherently coupled. The RPETCR is inversely proportional to the product of D and L. When the product of D and L is constant, both the simulated RPETCR and the inhibition of spurious dianeutral mixing are the same in all tests using the Leith

Improving risk estimates of runoff producing areas: formulating variable source areas as a bivariate process.

Science.gov (United States)

Cheng, Xiaoya; Shaw, Stephen B; Marjerison, Rebecca D; Yearick, Christopher D; DeGloria, Stephen D; Walter, M Todd

2014-05-01

Predicting runoff producing areas and their corresponding risks of generating storm runoff is important for developing watershed management strategies to mitigate non-point source pollution. However, few methods for making these predictions have been proposed, especially operational approaches that would be useful in areas where variable source area (VSA) hydrology dominates storm runoff. The objective of this study is to develop a simple approach to estimate spatially-distributed risks of runoff production. By considering the development of overland flow as a bivariate process, we incorporated both rainfall and antecedent soil moisture conditions into a method for predicting VSAs based on the Natural Resource Conservation Service-Curve Number equation. We used base-flow immediately preceding storm events as an index of antecedent soil wetness status. Using nine sub-basins of the Upper Susquehanna River Basin, we demonstrated that our estimated runoff volumes and extent of VSAs agreed with observations. We further demonstrated a method for mapping these areas in a Geographic Information System using a Soil Topographic Index. The proposed methodology provides a new tool for watershed planners for quantifying runoff risks across watersheds, which can be used to target water quality protection strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Which global stock indices trigger stronger contagion risk in the Vietnamese stock market? Evidence using a bivariate analysis

Directory of Open Access Journals (Sweden)

Wang Kuan-Min

2013-01-01

Full Text Available This paper extends recent investigations into risk contagion effects on stock markets to the Vietnamese stock market. Daily data spanning October 9, 2006 to May 3, 2012 are sourced to empirically validate the contagion effects between stock markets in Vietnam, and China, Japan, Singapore, and the US. To facilitate the validation of contagion effects with market-related coefficients, this paper constructs a bivariate EGARCH model of dynamic conditional correlation coefficients. Using the correlation contagion test and Dungey et al.’s (2005 contagion test, we find contagion effects between the Vietnamese and four other stock markets, namely Japan, Singapore, China, and the US. Second, we show that the Japanese stock market causes stronger contagion risk in the Vietnamese stock market compared to the stock markets of China, Singapore, and the US. Finally, we show that the Chinese and US stock markets cause weaker contagion effects in the Vietnamese stock market because of stronger interdependence effects between the former two markets.

Queue Length and Server Content Distribution in an Infinite-Buffer Batch-Service Queue with Batch-Size-Dependent Service

Directory of Open Access Journals (Sweden)

U. C. Gupta

2015-01-01

Full Text Available We analyze an infinite-buffer batch-size-dependent batch-service queue with Poisson arrival and arbitrarily distributed service time. Using supplementary variable technique, we derive a bivariate probability generating function from which the joint distribution of queue and server content at departure epoch of a batch is extracted and presented in terms of roots of the characteristic equation. We also obtain the joint distribution of queue and server content at arbitrary epoch. Finally, the utility of analytical results is demonstrated by the inclusion of some numerical examples which also includes the investigation of multiple zeros.

Modified Fourth-Order Kinetic Energy Gradient Expansion with Hartree Potential-Dependent Coefficients.

Science.gov (United States)

Constantin, Lucian A; Fabiano, Eduardo; Della Sala, Fabio

2017-09-12

Using the semiclassical neutral atom theory, we developed a modified fourth-order kinetic energy (KE) gradient expansion (GE4m) that keeps unchanged all the linear-response terms of the uniform electron gas and gives a significant improvement with respect to the known semilocal functionals for both large atoms and jellium surfaces. On the other hand, GE4m is not accurate for light atoms; thus, we modified the GE4m coefficients making them dependent on a novel ingredient, the reduced Hartree potential, recently introduced in the Journal of Chemical Physics 2016, 145, 084110, in the context of exchange functionals. The resulting KE gradient expansion functional, named uGE4m, belongs to the novel class of u-meta-generalized-gradient-approximations (uMGGA) whose members depend on the conventional ingredients (i.e., the reduced gradient and Laplacian of the density) as well as on the reduced Hartree potential. To test uGE4m, we defined an appropriate benchmark (including total KE and KE differences for atoms, molecules and jellium clusters) for gradient expansion functionals, that is, including only those systems which are mainly described by a slowly varying density regime. While most of the GGA and meta-GGA KE functionals (we tested 18 of them) are accurate for some properties and inaccurate for others, uGE4m shows a consistently good performance for all the properties considered. This represents a qualitative boost in the KE functional development and highlights the importance of the reduced Hartree potential for the construction of next-generation KE functionals.

Stability of Nonlinear Dirichlet BVPs Governed by Fractional Laplacian

Directory of Open Access Journals (Sweden)

Dorota Bors

2014-01-01

Dirichlet boundary data. Some sufficient condition under which the solutions of the equations considered depend continuously on parameters is stated. The application of the results to some optimal control problem is presented. The methods applied in the paper make use of the variational structure of the problem.

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

Science.gov (United States)

Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

2014-06-01

The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

Science.gov (United States)

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear

Study of the SEMG probability distribution of the paretic tibialis anterior muscle

Energy Technology Data Exchange (ETDEWEB)

Cherniz, AnalIa S; Bonell, Claudia E; Tabernig, Carolina B [Laboratorio de Ingenieria de Rehabilitacion e Investigaciones Neuromusculares y Sensoriales, Facultad de Ingenieria, UNER, Oro Verde (Argentina)

2007-11-15

The surface electromyographic signal is a stochastic signal that has been modeled as a Gaussian process, with a zero mean. It has been experimentally proved that this probability distribution can be adjusted with less error to a Laplacian type distribution. The selection of estimators for the detection of changes in the amplitude of the muscular signal depends, among other things, on the type of distribution. In the case of subjects with lesions to the superior motor neuron, the lack of central control affects the muscular tone, the force and the patterns of muscular movement involved in activities such as the gait cycle. In this work, the distribution types of the SEMG signal amplitudes of the tibialis anterior muscle are evaluated during gait, both in two healthy subjects and in two hemiparetic ones in order to select the estimators that best characterize them. It was observed that the Laplacian distribution function would be the one that best adjusts to the experimental data in the studied subjects, although this largely depends on the subject and on the data segment analyzed.

Study of the SEMG probability distribution of the paretic tibialis anterior muscle

International Nuclear Information System (INIS)

Cherniz, AnalIa S; Bonell, Claudia E; Tabernig, Carolina B

2007-01-01

The surface electromyographic signal is a stochastic signal that has been modeled as a Gaussian process, with a zero mean. It has been experimentally proved that this probability distribution can be adjusted with less error to a Laplacian type distribution. The selection of estimators for the detection of changes in the amplitude of the muscular signal depends, among other things, on the type of distribution. In the case of subjects with lesions to the superior motor neuron, the lack of central control affects the muscular tone, the force and the patterns of muscular movement involved in activities such as the gait cycle. In this work, the distribution types of the SEMG signal amplitudes of the tibialis anterior muscle are evaluated during gait, both in two healthy subjects and in two hemiparetic ones in order to select the estimators that best characterize them. It was observed that the Laplacian distribution function would be the one that best adjusts to the experimental data in the studied subjects, although this largely depends on the subject and on the data segment analyzed

Chaotic, informational and synchronous behaviour of multiplex networks

Science.gov (United States)

Baptista, M. S.; Szmoski, R. M.; Pereira, R. F.; Pinto, S. E. De Souza

2016-03-01

The understanding of the relationship between topology and behaviour in interconnected networks would allow to charac- terise and predict behaviour in many real complex networks since both are usually not simultaneously known. Most previous studies have focused on the relationship between topology and synchronisation. In this work, we provide analytical formulas that shows how topology drives complex behaviour: chaos, information, and weak or strong synchronisation; in multiplex net- works with constant Jacobian. We also study this relationship numerically in multiplex networks of Hindmarsh-Rose neurons. Whereas behaviour in the analytically tractable network is a direct but not trivial consequence of the spectra of eigenvalues of the Laplacian matrix, where behaviour may strongly depend on the break of symmetry in the topology of interconnections, in Hindmarsh-Rose neural networks the nonlinear nature of the chemical synapses breaks the elegant mathematical connec- tion between the spectra of eigenvalues of the Laplacian matrix and the behaviour of the network, creating networks whose behaviour strongly depends on the nature (chemical or electrical) of the inter synapses.

Generator localization by current source density (CSD): Implications of volume conduction and field closure at intracranial and scalp resolutions

Science.gov (United States)

Tenke, Craig E.; Kayser, Jürgen

2012-01-01

The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm’s Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson’s source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the “cortical dipole” into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings. PMID:22796039

Scale-dependent bias from the reconstruction of non-Gaussian distributions

International Nuclear Information System (INIS)

Chongchitnan, Sirichai; Silk, Joseph

2011-01-01

Primordial non-Gaussianity introduces a scale-dependent variation in the clustering of density peaks corresponding to rare objects. This variation, parametrized by the bias, is investigated on scales where a linear perturbation theory is sufficiently accurate. The bias is obtained directly in real space by comparing the one- and two-point probability distributions of density fluctuations. We show that these distributions can be reconstructed using a bivariate Edgeworth series, presented here up to an arbitrarily high order. The Edgeworth formalism is shown to be well-suited for ''local'' cubic-order non-Gaussianity parametrized by g NL . We show that a strong scale dependence in the bias can be produced by g NL of order 10 5 , consistent with cosmic microwave background constraints. On a separation length of ∼100 Mpc, current constraints on g NL still allow the bias for the most massive clusters to be enhanced by 20-30% of the Gaussian value. We further examine the bias as a function of mass scale, and also explore the relationship between the clustering and the abundance of massive clusters in the presence of g NL . We explain why the Edgeworth formalism, though technically challenging, is a very powerful technique for constraining high-order non-Gaussianity with large-scale structures.

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Science.gov (United States)

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K; Schad, Lothar R; Zöllner, Frank Gerrit

2015-01-01

Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

Bivariate quadratic method in quantifying the differential capacitance and energy capacity of supercapacitors under high current operation

Science.gov (United States)

Goh, Chin-Teng; Cruden, Andrew

2014-11-01

Capacitance and resistance are the fundamental electrical parameters used to evaluate the electrical characteristics of a supercapacitor, namely the dynamic voltage response, energy capacity, state of charge and health condition. In the British Standards EN62391 and EN62576, the constant capacitance method can be further improved with a differential capacitance that more accurately describes the dynamic voltage response of supercapacitors. This paper presents a novel bivariate quadratic based method to model the dynamic voltage response of supercapacitors under high current charge-discharge cycling, and to enable the derivation of the differential capacitance and energy capacity directly from terminal measurements, i.e. voltage and current, rather than from multiple pulsed-current or excitation signal tests across different bias levels. The estimation results the author achieves are in close agreement with experimental measurements, within a relative error of 0.2%, at various high current levels (25-200 A), more accurate than the constant capacitance method (4-7%). The archival value of this paper is the introduction of an improved quantification method for the electrical characteristics of supercapacitors, and the disclosure of the distinct properties of supercapacitors: the nonlinear capacitance-voltage characteristic, capacitance variation between charging and discharging, and distribution of energy capacity across the operating voltage window.

Relating zeta functions of discrete and quantum graphs

Science.gov (United States)

Harrison, Jonathan; Weyand, Tracy

2018-02-01

We write the spectral zeta function of the Laplace operator on an equilateral metric graph in terms of the spectral zeta function of the normalized Laplace operator on the corresponding discrete graph. To do this, we apply a relation between the spectrum of the Laplacian on a discrete graph and that of the Laplacian on an equilateral metric graph. As a by-product, we determine how the multiplicity of eigenvalues of the quantum graph, that are also in the spectrum of the graph with Dirichlet conditions at the vertices, depends on the graph geometry. Finally we apply the result to calculate the vacuum energy and spectral determinant of a complete bipartite graph and compare our results with those for a star graph, a graph in which all vertices are connected to a central vertex by a single edge.

Idealized models of the joint probability distribution of wind speeds

Science.gov (United States)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

ALCOHOL DEPENDENCE IN GASTROENTEROLOG YOUTPATIENT ON A PUBLIC HOSPITAL

Directory of Open Access Journals (Sweden)

Mariana de Andrade PRANKE

2017-09-01

Full Text Available ABSTRACT BACKGROUND: Alcoholism and alcoholic liver disease are both considered worldwide health problems. OBJECTIVE: The prevalence of alcohol dependence, the associated risk factors and the concordance between the prevalence found and the data collected during the medical visit were evaluated. METHODS: A prospective study evaluating gastroenterology outpatients at a public tertiary hospital was conducted. Two specific questionnaires to assess alcohol dependence were applied: Cut down, Annoyed by criticism, Guilty, Eye-opener (CAGE and The Alcohol Use Disorder Identification Test (AUDIT. Data on comorbidities, clinical diagnosis and assessment of alcohol consumption by the attending physician were collected through medical records. RESULTS: One hundred and seventy eight patients were interviewed, of which 119 (66.9% were women and 59 (33.1% were men, with mean age of 57 years. Thirty-three (18.5% of the 178 patients were considered alcohol-dependent by the CAGE questionnaire. Thirteen (7.3% patients scored 8 points or more on the AUDIT questionnaire. The agreement (kappa between these questionnaires was 0.37 (P<0.001. The most consumed drink was beer. The median daily consumption of dependent patients was 64 g. None of the patients were undergoing treatment in a specific treatment center, and 14/33 (42.4% patients considered themselves alcoholics. Only in 17/33 (51.5% there was information about alcoholism in their respective medical records. In the bivariate analysis, male gender (P<0.001, onset of alcohol consumption before the age of 15 (P=0.003, daily alcohol consumption in the last 12 months (P<0.001 and smoking (P<0.001 were identified as risk factors. After multivariate analysis, only male gender (P=0.009 and smoking (P=0.001 were associated with alcoholism. CONCLUSION: The present study demonstrated a high prevalence of alcohol dependence in the gastroenterology outpatient clinic, being predominantly associated with male gender and

The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution.

Science.gov (United States)

Li, Ning; Liu, Xueqin; Xie, Wei; Wu, Jidong; Zhang, Peng

2013-01-01

New features of natural disasters have been observed over the last several years. The factors that influence the disasters' formation mechanisms, regularity of occurrence and main characteristics have been revealed to be more complicated and diverse in nature than previously thought. As the uncertainty involved increases, the variables need to be examined further. This article discusses the importance and the shortage of multivariate analysis of natural disasters and presents a method to estimate the joint probability of the return periods and perform a risk analysis. Severe dust storms from 1990 to 2008 in Inner Mongolia were used as a case study to test this new methodology, as they are normal and recurring climatic phenomena on Earth. Based on the 79 investigated events and according to the dust storm definition with bivariate, the joint probability distribution of severe dust storms was established using the observed data of maximum wind speed and duration. The joint return periods of severe dust storms were calculated, and the relevant risk was analyzed according to the joint probability. The copula function is able to simulate severe dust storm disasters accurately. The joint return periods generated are closer to those observed in reality than the univariate return periods and thus have more value in severe dust storm disaster mitigation, strategy making, program design, and improvement of risk management. This research may prove useful in risk-based decision making. The exploration of multivariate analysis methods can also lay the foundation for further applications in natural disaster risk analysis. © 2012 Society for Risk Analysis.

Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

Energy Technology Data Exchange (ETDEWEB)

Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

Quasi-bivariate variational mode decomposition as a tool of scale analysis in wall-bounded turbulence

Science.gov (United States)

Wang, Wenkang; Pan, Chong; Wang, Jinjun

2018-01-01

The identification and separation of multi-scale coherent structures is a critical task for the study of scale interaction in wall-bounded turbulence. Here, we propose a quasi-bivariate variational mode decomposition (QB-VMD) method to extract structures with various scales from instantaneous two-dimensional (2D) velocity field which has only one primary dimension. This method is developed from the one-dimensional VMD algorithm proposed by Dragomiretskiy and Zosso (IEEE Trans Signal Process 62:531-544, 2014) to cope with a quasi-2D scenario. It poses the feature of length-scale bandwidth constraint along the decomposed dimension, together with the central frequency re-balancing along the non-decomposed dimension. The feasibility of this method is tested on both a synthetic flow field and a turbulent boundary layer at moderate Reynolds number (Re_{τ } = 3458) measured by 2D particle image velocimetry (PIV). Some other popular scale separation tools, including pseudo-bi-dimensional empirical mode decomposition (PB-EMD), bi-dimensional EMD (B-EMD) and proper orthogonal decomposition (POD), are also tested for comparison. Among all these methods, QB-VMD shows advantages in both scale characterization and energy recovery. More importantly, the mode mixing problem, which degrades the performance of EMD-based methods, is avoided or minimized in QB-VMD. Finally, QB-VMD analysis of the wall-parallel plane in the log layer (at y/δ = 0.12) of the studied turbulent boundary layer shows the coexistence of large- or very large-scale motions (LSMs or VLSMs) and inner-scaled structures, which can be fully decomposed in both physical and spectral domains.

Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

International Nuclear Information System (INIS)

Costa, Valter Magalhaes; Pereira, Iraci Martinez

2011-01-01

The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Directory of Open Access Journals (Sweden)

Jakob Nikolas Kather

Full Text Available Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions.In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images.To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images.Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

Examination of the causes of covariation between conduct disorder symptoms and vulnerability to drug dependence.

Science.gov (United States)

Button, Tanya M M; Hewitt, John K; Rhee, Soo Hyun; Young, Susan E; Corley, Robin P; Stallings, Michael C

2006-02-01

Conduct disorder (CD) symptoms and substance dependence commonly co-occur. Both phenotypes are highly heritable and a common genetic influence on the covariation has been suggested. The aim of this study was to determine the extent to which genes and environment contribute to the covariance between CD and drug dependence using twins from the Colorado Longitudinal Twin Sample and the Colorado Twin Registry. A total of 880 twin pairs (237 monozygotic [MZ] female, 195 MZ male, 116 dizygotic [DZ] female, 118 DZ male and 214 DZ opposite-sex) aged 13 to 18 (mean = 15.65) were included in the analysis. CD was assessed by lifetime Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) symptom count and a polysubstance dependence vulnerability index was developed from responses to the Composite International Diagnostic Interview--Substance Abuse Module. A bivariate Cholesky Decomposition model was used to partition the cause of variation and covariation of the two phenotypes. No sex-limitation was observed in our data, and male and female parameter estimates were constrained to be equal. Both CD symptoms and dependence vulnerability were significantly heritable, and genes, shared environment and nonshared environment all contributed to the covariation between them. Genes contributed 35% of the phenotypic covariance, shared environment contributed 46%, and nonshared environmental influences contributed the remaining 19% to the phenotypic covariance. Therefore, there appears to be pleiotropic genetic influence on CD symptoms and dependence vulnerability.

Stochastic Levy Divergence and Maxwell's Equations

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B. O. Volkov

2015-01-01

Full Text Available One of the main reasons for interest in the Levy Laplacian and its analogues such as Levy d'Alembertian is a connection of these operators with gauge fields. The theorem proved by Accardi, Gibillisco and Volovich stated that a connection in a bundle over a Euclidean space or over a Minkowski space is a solution of the Yang-Mills equations if and only if the corresponding parallel transport to the connection is a solution of the Laplace equation for the Levy Laplacian or of the d'Alembert equation for the Levy d'Alembertian respectively (see [5, 6]. There are two approaches to define Levy type operators, both of which date back to the original works of Levy [7]. The first is that the Levy Laplacian (or Levy d'Alembertian is defined as an integral functional generated by a special form of the second derivative. This approach is used in the works [5, 6], as well as in the paper [8] of Leandre and Volovich, where stochastic Levy-Laplacian is discussed. Another approach to the Levy Laplacian is defining it as the Cesaro mean of second order derivatives along the family of vectors, which is an orthonormal basis in the Hilbert space. This definition of the Levy Laplacian is used for the description of solutions of the Yang-Mills equations in the paper [10].The present work shows that the definitions of the Levy Laplacian and the Levy d'Alembertian based on Cesaro averaging of the second order directional derivatives can be transferred to the stochastic case. In the article the values of these operators on a stochastic parallel transport associated with a connection (vector potential are found. In this case, unlike the deterministic case and the stochastic case of Levy Laplacian from [8], these values are not equal to zero if the vector potential corresponding to the stochastic parallel transport is a solution of the Maxwell's equations. As a result, two approaches to definition of the Levy Laplacian in the stochastic case give different operators. This

Direct extraction of boundaries from computed tomography scans

International Nuclear Information System (INIS)

Thirion, J.P.

1994-01-01

This paper presents a method, based on the Filtered Backprojection technique (FBP), to extract directly the boundaries of X-ray images, without previous image reconstruction. The authors preprocess the raw data in order to compute directly the reconstructed values of the gradient or of the Laplacian at any location in the plane (defined with real coordinates). The reconstructed value of the gradient and of the Laplacian correspond to the exact mathematical definition of the differentials of the image. For noisy data, the authors propose also to use an extension of existing FBP techniques, adapted to the computation of the gradient and of the Laplacian. Finally, the authors show how to use the corresponding operators to perform the segmentation of a slice, without image reconstruction. Images of the reconstructed gradient, Laplacian, and segmented objects are presented

A Spectral Algorithm for Envelope Reduction of Sparse Matrices

Science.gov (United States)

Barnard, Stephen T.; Pothen, Alex; Simon, Horst D.

1993-01-01

The problem of reordering a sparse symmetric matrix to reduce its envelope size is considered. A new spectral algorithm for computing an envelope-reducing reordering is obtained by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. This Laplacian eigenvector solves a continuous relaxation of a discrete problem related to envelope minimization called the minimum 2-sum problem. The permutation vector computed by the spectral algorithm is a closest permutation vector to the specified Laplacian eigenvector. Numerical results show that the new reordering algorithm usually computes smaller envelope sizes than those obtained from the current standard algorithms such as Gibbs-Poole-Stockmeyer (GPS) or SPARSPAK reverse Cuthill-McKee (RCM), in some cases reducing the envelope by more than a factor of two.

A regularized, model-based approach to phase-based conductivity mapping using MRI.

Science.gov (United States)

Ropella, Kathleen M; Noll, Douglas C

2017-11-01

To develop a novel regularized, model-based approach to phase-based conductivity mapping that uses structural information to improve the accuracy of conductivity maps. The inverse of the three-dimensional Laplacian operator is used to model the relationship between measured phase maps and the object conductivity in a penalized weighted least-squares optimization problem. Spatial masks based on structural information are incorporated into the problem to preserve data near boundaries. The proposed Inverse Laplacian method was compared against a restricted Gaussian filter in simulation, phantom, and human experiments. The Inverse Laplacian method resulted in lower reconstruction bias and error due to noise in simulations than the Gaussian filter. The Inverse Laplacian method also produced conductivity maps closer to the measured values in a phantom and with reduced noise in the human brain, as compared to the Gaussian filter. The Inverse Laplacian method calculates conductivity maps with less noise and more accurate values near boundaries. Improving the accuracy of conductivity maps is integral for advancing the applications of conductivity mapping. Magn Reson Med 78:2011-2021, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

DBH Prediction Using Allometry Described by Bivariate Copula Distribution

Science.gov (United States)

Xu, Q.; Hou, Z.; Li, B.; Greenberg, J. A.

2017-12-01

Forest biomass mapping based on single tree detection from the airborne laser scanning (ALS) usually depends on an allometric equation that relates diameter at breast height (DBH) with per-tree aboveground biomass. The incapability of the ALS technology in directly measuring DBH leads to the need to predict DBH with other ALS-measured tree-level structural parameters. A copula-based method is proposed in the study to predict DBH with the ALS-measured tree height and crown diameter using a dataset measured in the Lassen National Forest in California. Instead of exploring an explicit mathematical equation that explains the underlying relationship between DBH and other structural parameters, the copula-based prediction method utilizes the dependency between cumulative distributions of these variables, and solves the DBH based on an assumption that for a single tree, the cumulative probability of each structural parameter is identical. Results show that compared with the bench-marking least-square linear regression and the k-MSN imputation, the copula-based method obtains better accuracy in the DBH for the Lassen National Forest. To assess the generalization of the proposed method, prediction uncertainty is quantified using bootstrapping techniques that examine the variability of the RMSE of the predicted DBH. We find that the copula distribution is reliable in describing the allometric relationship between tree-level structural parameters, and it contributes to the reduction of prediction uncertainty.

Interaction between diffusion and chemical stresses

International Nuclear Information System (INIS)

Yang Fuqian

2005-01-01

The present work studies the interaction between chemical stresses and diffusion. A new relation between hydrostatic stress and concentration of solute atoms is established. For a solid free of action of body force, the Laplacian of the hydrostatic stress is proportional to the Laplacian of the concentration of solute atoms, that is, deviation of the hydrostatic stress from its local average is proportional to deviation of the local concentration of solute atoms. A general relationship among surface concentration of solute atoms, normal stress and surface deformation of a solid is then derived, in which the normal stress is dependent on the mean curvature of the undeformed surface and tangential components of the surface displacement. A closed-form solution of the steady state concentration of solute atoms in a thin plate is obtained. It turns out that linear distribution of solute atoms in the plate is non-existent due to the interaction between chemical stresses and diffusion

Manifolds with cusps of rank one spectral theory and L2-index theorem

CERN Document Server

Müller, Werner

1987-01-01

The manifolds investigated in this monograph are generalizations of (Mathematical Physics and Mathematics)-rank one locally symmetric spaces. In the first part of the book the author develops spectral theory for the differential Laplacian operator associated to the so-called generalized Dirac operators on manifolds with cusps of rank one. This includes the case of spinor Laplacians on (Mathematical Physics and Mathematics)-rank one locally symmetric spaces. The time-dependent approach to scattering theory is taken to derive the main results about the spectral resolution of these operators. The second part of the book deals with the derivation of an index formula for generalized Dirac operators on manifolds with cusps of rank one. This index formula is used to prove a conjecture of Hirzebruch concerning the relation of signature defects of cusps of Hilbert modular varieties and special values of L-series. This book is intended for readers working in the field of automorphic forms and analysis on non-compact Ri...

A state-dependent model for inflation forecasting

OpenAIRE

Andrea Stella; James H. Stock

2012-01-01

We develop a parsimonious bivariate model of inflation and unemployment that allows for persistent variation in trend inflation and the NAIRU. The model, which consists of five unobserved components (including the trends) with stochastic volatility, implies a time-varying VAR for changes in the rates of inflation and unemployment. The implied backwards-looking Phillips curve has a time-varying slope that is steeper in the 1970s than in the 1990s. Pseudo out-of-sample forecasting experiments i...

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis.

Science.gov (United States)

Moran, Valerie; Jacobs, Rowena

2018-06-01

Provider payment systems for mental health care that incentivize cost control and quality improvement have been a policy focus in a number of countries. In England, a new prospective provider payment system is being introduced to mental health that should encourage providers to control costs and improve outcomes. The aim of this research is to investigate the relationship between costs and outcomes to ascertain whether there is a trade-off between controlling costs and improving outcomes. The main data source is the Mental Health Minimum Data Set (MHMDS) for the years 2011/12 and 2012/13. Costs are calculated using NHS reference cost data while outcomes are measured using the Health of the Nation Outcome Scales (HoNOS). We estimate a bivariate multi-level model with costs and outcomes simultaneously. We calculate the correlation and plot the pairwise relationship between residual costs and outcomes at the provider level. After controlling for a range of demographic, need, social, and treatment variables, residual variation in costs and outcomes remains at the provider level. The correlation between residual costs and outcomes is negative, but very small, suggesting that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment system.

On the origins and foundations of Laplacian determinism.

Science.gov (United States)

van Strien, Marij

2014-03-01

In this paper I examine the foundations of Laplace's famous statement of determinism in 1814, and argue that rather than derived from his mechanics, this statement is based on general philosophical principles, namely the principle of sufficient reason and the law of continuity. It is usually supposed that Laplace's statement is based on the fact that each system in classical mechanics has an equation of motion which has a unique solution. But Laplace never proved this result, and in fact he could not have proven it, since it depends on a theorem about uniqueness of solutions to differential equations that was only developed later on. I show that the idea that is at the basis of Laplace's determinism was in fact widespread in enlightenment France, and is ultimately based on a re-interpretation of Leibnizian metaphysics, specifically the principle of sufficient reason and the law of continuity. Since the law of continuity also lies at the basis of the application of differential calculus in physics, one can say that Laplace's determinism and the idea that systems in physics can be described by differential equations with unique solutions have a common foundation.

Extensão bivariada do índice de confiabilidade univariado para avaliação da estabilidade fenotípica Bivariate extension of univariate reliability index for evaluating phenotypic stability

Directory of Open Access Journals (Sweden)

Suzankelly Cunha Arruda de Abreu

2004-10-01

Full Text Available Com o presente trabalho, objetiva-se realizar a derivação teórica da extensão bivariada dos métodos de Annicchiarico (1992 e Annicchiarico et al. (1995 para estudar a estabilidade fenotípica. A partir dos ensaios com genótipos em ambientes e mensurações de duas variáveis, cada genótipo teve seu valor padronizado com relação a cada variável k = 1, 2. Essa padronização foi realizada em função da média do ambiente, da seguinte forma: Wijk = Yijk/×100 ; em que Wijk representa o valor padronizado do genótipo i, no ambiente j para a variável k; representa a média observada do genótipo , no ambiente para a variável k e , a média de todos genótipos para o ambiente e variável k. Com os valores padronizados foram estimados o vetor média e a matriz de variância e covariância de cada genótipo. Foi obtida a derivação teórica da extensão bivariada do índice de risco (Ii de Annicchiarico com sucesso e foi proposto um segundo índice de risco baseado nas probabilidades bivariada (Prb i; os dois índices apresentaram grande concordância nos resultados obtidos em um exemplo ilustrativo com genótipos de melões.The objective of this work was to obtain the theoretical derivation of the bivariate extension to the methods proposed by Annicchiarico (1992 and Annicchiarico et al. (1995 for studing phenotypic stability. Considering assays with genotypes in environments and two variates, every genotype had the response of each variate (k = 1, 2 standardized. This standardization has been made using the environment means as follows: Wijk = Yijk/×100 ; where Wijk represents the ith genotype standard value in the jth environment for the kth variate; represents the observed mean of the ith genotype, in jth environment for the kth variate e the overall genotypes means for jth environment to kth variate. Considering the standardized values, the genotypes mean vector and covariance matrix were estimated. The theoretical derivation of the

Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics.

Science.gov (United States)

Alberola-Rubio, J; Prats-Boluda, G; Ye-Lin, Y; Valero, J; Perales, A; Garcia-Casado, J

2013-12-01

Non-invasive recording of uterine myoelectric activity (electrohysterogram, EHG) could provide an alternative to monitoring uterine dynamics by systems based on tocodynamometers (TOCO). Laplacian recording of bioelectric signals has been shown to give better spatial resolution and less interference than mono- and bipolar surface recordings. The aim of this work was to study the signal quality obtained from monopolar, bipolar and Laplacian techniques in EHG recordings, as well as to assess their ability to detect uterine contractions. Twenty-two recording sessions were carried out on singleton pregnant women during the active phase of labour. In each session the following simultaneous recordings were obtained: internal uterine pressure (IUP), external tension of abdominal wall (TOCO) and EHG signals (5 monopolar and 4 bipolar recordings, 1 discrete approximation to the Laplacian of the potential and 2 estimates of the Laplacian from two active annular electrodes). The results obtained show that EHG is able to detect a higher number of uterine contractions than TOCO. Laplacian recordings give improved signal quality over monopolar and bipolar techniques, reduce maternal cardiac interference and improve the signal-to-noise ratio. The optimal position for recording EHG was found to be the uterine median axis and the lower centre-right umbilical zone. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Predictors of attrition with buprenorphine/naloxone treatment in opioid dependent youth☆

Science.gov (United States)

Warden, Diane; Subramaniam, Geetha A.; Carmody, Thomas; Woody, George E.; Minhajuddin, Abu; Poole, Sabrina A.; Potter, Jennifer; Fishman, Marc; Bogenschutz, Michael; Patkar, Ashwin; Trivedi, Madhukar H.

2012-01-01

Background In opioid dependent youth there is substantial attrition from medication-assisted treatment. If youth at risk for attrition can be identified at treatment entry or early in treatment, they can be targeted for interventions to help retain them in treatment. Methods Opioid dependent adolescents and young adults (n=152), aged 15–21, were randomized to 12 weeks (BUP, n=74) or 2 weeks of detoxification (DETOX, n=78) with buprenorphine/naloxone (Bup/Nal), both in combination with 12 weeks of psychosocial treatment. Baseline and early treatment related predictors of treatment attrition were identified in each group using bivariate and multivariate logistic regression. Results In the DETOX group 36% left between weeks 2 and 4, at the end of the dose taper, while in the BUP group only 8% left by week 4. In the BUP group, early adherence to Bup/Nal, early opioid negative urines, use of any medications in the month prior to treatment entry, and lifetime non-heroin opioid use were associated with retention while prior 30-day hallucinogen use was associated with attrition. In the DETOX group, only use of sleep medications was associated with retention although not an independent predictor. A broad range of other pre-treatment characteristics was unrelated to attrition. Conclusions Prompt attention to those with early non-adherence to medication or an early opioid positive urine, markers available in the first 2 weeks of treatment, may improve treatment retention. Extended Bup/ Nal treatment appeared effective in improving treatment retention for youth with opioid dependence across a wide range of demographics, and pre-treatment clinical characteristics. PMID:22626890

Predictors of attrition with buprenorphine/naloxone treatment in opioid dependent youth.

Science.gov (United States)

Warden, Diane; Subramaniam, Geetha A; Carmody, Thomas; Woody, George E; Minhajuddin, Abu; Poole, Sabrina A; Potter, Jennifer; Fishman, Marc; Bogenschutz, Michael; Patkar, Ashwin; Trivedi, Madhukar H

2012-09-01

In opioid dependent youth there is substantial attrition from medication-assisted treatment. If youth at risk for attrition can be identified at treatment entry or early in treatment, they can be targeted for interventions to help retain them in treatment. Opioid dependent adolescents and young adults (n=152), aged 15-21, were randomized to 12 weeks (BUP, n=74) or 2 weeks of detoxification (DETOX, n=78) with buprenorphine/naloxone (Bup/Nal), both in combination with 12 weeks of psychosocial treatment. Baseline and early treatment related predictors of treatment attrition were identified in each group using bivariate and multivariate logistic regression. In the DETOX group 36% left between weeks 2 and 4, at the end of the dose taper, while in the BUP group only 8% left by week 4. In the BUP group, early adherence to Bup/Nal, early opioid negative urines, use of any medications in the month prior to treatment entry, and lifetime non-heroin opioid use were associated with retention while prior 30-day hallucinogen use was associated with attrition. In the DETOX group, only use of sleep medications was associated with retention although not an independent predictor. A broad range of other pre-treatment characteristics was unrelated to attrition. Prompt attention to those with early non-adherence to medication or an early opioid positive urine, markers available in the first 2 weeks of treatment, may improve treatment retention. Extended Bup/Nal treatment appeared effective in improving treatment retention for youth with opioid dependence across a wide range of demographics, and pre-treatment clinical characteristics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mosco convergence of integral functionals and its applications

International Nuclear Information System (INIS)

Tolstonogov, Aleksandr A

2009-01-01

Questions relating to the Mosco convergence of integral functionals defined on the space of square integrable functions taking values in a Hilbert space are investigated. The integrands of these functionals are time-dependent proper, convex, lower semicontinuous functions on the Hilbert space. The results obtained are applied to the analysis of the dependence on the parameter of solutions of evolution equations involving time-dependent subdifferential operators. For example a parabolic inclusion is considered, where the right-hand side contains a sum of the p-Laplacian and the subdifferential of the indicator function of a time-dependent closed convex set. The convergence as p→+∞ of solutions of this inclusion is investigated. Bibliography: 20 titles.

Spectral Results on Some Hamiltonian Properties of Graphs

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Rao Li

2014-10-01

Full Text Available Using Lotker’s interlacing theorem on the Laplacian eigenvalues of a graph in [5] and Wang and Belardo’s interlacing theorem on the signless Laplacian eigenvalues of a graph in [6], we in this note obtain spectral conditions for some Hamiltonian properties of graphs

Symmetric co-movement between Malaysia and Japan stock markets

Science.gov (United States)

Razak, Ruzanna Ab; Ismail, Noriszura

2017-04-01

The copula approach is a flexible tool known to capture linear, nonlinear, symmetric and asymmetric dependence between two or more random variables. It is often used as a co-movement measure between stock market returns. The information obtained from copulas such as the level of association of financial market during normal and bullish and bearish markets phases are useful for investment strategies and risk management. However, the study of co-movement between Malaysia and Japan markets are limited, especially using copulas. Hence, we aim to investigate the dependence structure between Malaysia and Japan capital markets for the period spanning from 2000 to 2012. In this study, we showed that the bivariate normal distribution is not suitable as the bivariate distribution or to present the dependence between Malaysia and Japan markets. Instead, Gaussian or normal copula was found a good fit to represent the dependence. From our findings, it can be concluded that simple distribution fitting such as bivariate normal distribution does not suit financial time series data, whose characteristics are often leptokurtic. The nature of the data is treated by ARMA-GARCH with heavy tail distributions and these can be associated with copula functions. Regarding the dependence structure between Malaysia and Japan markets, the findings suggest that both markets co-move concurrently during normal periods.

On the Curvature and Heat Flow on Hamiltonian Systems

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Ohta Shin-ichi

2014-01-01

Full Text Available We develop the differential geometric and geometric analytic studies of Hamiltonian systems. Key ingredients are the curvature operator, the weighted Laplacian, and the associated Riccati equation.We prove appropriate generalizations of the Bochner-Weitzenböck formula and Laplacian comparison theorem, and study the heat flow.

Modeling of MAI in UWB System Using MGGD

KAUST Repository

Ahmed, Qasim Zeeshan

2014-01-06

Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to Gaussian, Laplacian and Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. Finally, a receiver based on the principles of minimum bit error rate is designed for the MGGD pdf.

Tobacco dependence among people with mental illness: a facility-based cross sectional study from Southwest Ethiopia.

Science.gov (United States)

Molla, Zemenay; Dube, Lamesa; Krahl, Wolfgang; Soboka, Matiwos

2017-07-17

Tobacco smoking is a health care issue in developed as well as in developing countries. Tobacco smoking among people with mental illness is significantly higher than in the general population. Tobacco smoking has negative effects on physical, mental and financial well-being of people with mental illness but little is known about tobacco dependence among mental health service users in sub-Saharan African countries, including Ethiopia. Therefore, this study attempted to assess the prevalence of tobacco dependence and associated factors among mental health service users at Jimma University teaching hospital. A cross-sectional study was conducted among 305 male and 117 female mental health service users at Jimma University teaching Hospital in 2014. The Fagerstrom Test for Nicotine Dependence (FTND) was used to assess tobacco dependence. Logistic regression analysis was used for bivariate and multivariate analysis. Variables with a P value of service users with tobacco dependence were males. There was a significant association between tobacco dependence and high school education (AOR 3.02, 95% CI 1.07, 8. 48), alcohol use disorder (AOR 4.14, 95% CI = 1.54, 11.11), daily khat chewing (AOR 13.51, 95% CI = 4.27, 42.74), chewing khat 2-3 times per week (AOR 5.09, 95% CI = 1.37,18.95), chewing khat once a week (AOR 4.31, 95%CI = 1.04,17.78), having friends who smoke tobacco (AOR 4.88, 95% CI = 2.12, 11.25) and being diagnosed with schizophrenia compared to a diagnosis of major depression (AOR 5.26, 95% CI = 2.07, 13.37). However, daily attendance at a place of worship (AOR 0.46, 95% CI = 0.22, 0.95) was associated negatively with tobacco dependence. In this study, there was a high prevalence of tobacco dependence among mental health services users. There is a pressing need to increase availability of psychological and pharmacological interventions to reduce tobacco dependence and tobacco-related medical illness in this vulnerable group.

Bivariate copulas on the exponentially weighted moving average control chart

Directory of Open Access Journals (Sweden)

Sasigarn Kuvattana

2016-10-01

Full Text Available This paper proposes four types of copulas on the Exponentially Weighted Moving Average (EWMA control chart when observations are from an exponential distribution using a Monte Carlo simulation approach. The performance of the control chart is based on the Average Run Length (ARL which is compared for each copula. Copula functions for specifying dependence between random variables are used and measured by Kendall’s tau. The results show that the Normal copula can be used for almost all shifts.

Strong diamagnetism for general domains and applications

DEFF Research Database (Denmark)

Fournais, Søren; Helffer, Bernard

2007-01-01

We consider the Neumann Laplacian with constant magnetic field on a regular domain. Let $B$ be the strength of the magnetic field, and let $\\lambda_1(B)$ be the first eigenvalue of the magnetic Neumann Laplacian on the domain. It is proved that $B \\mapsto \\lambda_1(B)$ is monotone increasing for ...

Stable Formation Control of Multi-Robot System with Communication Delay

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Limei Jiang

2012-03-01

Full Text Available In this paper, a distributed formation control algorithm with delayed information exchange is discussed. The algorithm, which is derived from the flocking behaviour of birds and consensus theory, enables robots to move in formation at a desired velocity. After a series of orthogonal transformations to the original formation system, the upper bound tolerable delay is obtained by using matrix theory and the Nyquist criterion. According to the results, the upper bound tolerable delay depends on the control parameters and eigenvalues of the Laplacian matrix. Therefore, the effect of the parameters on the maximum tolerable delay is analysed, obtaining the following conclusions: the upper bound tolerable delay is proportional to the parameters associated with the velocity, inversely proportional to the parameters associated with the position, and inversely proportional to the difference between the eigenvalue of Laplacian matrix and 1. The simulation results of a four-robot formation system with different communication delays verify the effectiveness of the formation control algorithm and the correctness of the theoretical analysis.

Modeling of pseudoacoustic P-waves in orthorhombic media with a low-rank approximation

KAUST Repository

Song, Xiaolei

2013-06-04

Wavefield extrapolation in pseudoacoustic orthorhombic anisotropic media suffers from wave-mode coupling and stability limitations in the parameter range. We use the dispersion relation for scalar wave propagation in pseudoacoustic orthorhombic media to model acoustic wavefields. The wavenumber-domain application of the Laplacian operator allows us to propagate the P-waves exclusively, without imposing any conditions on the parameter range of stability. It also allows us to avoid dispersion artifacts commonly associated with evaluating the Laplacian operator in space domain using practical finite-difference stencils. To handle the corresponding space-wavenumber mixed-domain operator, we apply the low-rank approximation approach. Considering the number of parameters necessary to describe orthorhombic anisotropy, the low-rank approach yields space-wavenumber decomposition of the extrapolator operator that is dependent on space location regardless of the parameters, a feature necessary for orthorhombic anisotropy. Numerical experiments that the proposed wavefield extrapolator is accurate and practically free of dispersion. Furthermore, there is no coupling of qSv and qP waves because we use the analytical dispersion solution corresponding to the P-wave.

Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

Directory of Open Access Journals (Sweden)

Yanyong Guo

2017-01-01

Full Text Available The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use.

Numerical modeling of positive streamer in air in nonuniform fields: Efficiency of radicals production

International Nuclear Information System (INIS)

Kulikovsky, A.A.

2001-01-01

The efficiency of streamer corona depends on a number of factors such as geometry of electrodes, voltage pulse parameters, gas pressure etc. In a past 5 years a two-dimensional models of streamer in nonuniform fields in air have been developed. These models allow to simulate streamer dynamics and generation of species and to investigate the influence of external parameters on species production. In this work the influence of Laplacian field on efficiency of radicals generation is investigated

C2H5OH

Indian Academy of Sciences (India)

gen bonding interactions, it is now well established that ... molecules.11 The results of this work were found to be .... (Y is acceptor atom). Table 2 presents electron den- sity values ρ(r) and Laplacian of electron density values. Table 2. Electron densities (ρ(r)) and the Laplacian (∇2ρ(r)) values at the intermolecular BCP for ...

Nutrition education intervention for dependent patients: protocol of a randomized controlled trial.

Science.gov (United States)

Arija, Victoria; Martín, Núria; Canela, Teresa; Anguera, Carme; Castelao, Ana I; García-Barco, Montserrat; García-Campo, Antoni; González-Bravo, Ana I; Lucena, Carme; Martínez, Teresa; Fernández-Barrés, Silvia; Pedret, Roser; Badia, Waleska; Basora, Josep

2012-05-24

Malnutrition in dependent patients has a high prevalence and can influence the prognosis associated with diverse pathologic processes, decrease quality of life, and increase morbidity-mortality and hospital admissions.The aim of the study is to assess the effect of an educational intervention for caregivers on the nutritional status of dependent patients at risk of malnutrition. Intervention study with control group, randomly allocated, of 200 patients of the Home Care Program carried out in 8 Primary Care Centers (Spain). These patients are dependent and at risk of malnutrition, older than 65, and have caregivers. The socioeconomic and educational characteristics of the patient and the caregiver are recorded. On a schedule of 0-6-12 months, patients are evaluated as follows: Mini Nutritional Assessment (MNA), food intake, dentures, degree of dependency (Barthel test), cognitive state (Pfeiffer test), mood status (Yesavage test), and anthropometric and serum parameters of nutritional status: albumin, prealbumin, transferrin, haemoglobin, lymphocyte count, iron, and ferritin.Prior to the intervention, the educational procedure and the design of educational material are standardized among nurses. The nurses conduct an initial session for caregivers and then monitor the education impact at home every month (4 visits) up to 6 months. The North American Nursing Diagnosis Association (NANDA) methodology will be used. The investigators will study the effect of the intervention with caregivers on the patient's nutritional status using the MNA test, diet, anthropometry, and biochemical parameters.Bivariate normal test statistics and multivariate models will be created to adjust the effect of the intervention.The SPSS/PC program will be used for statistical analysis. The nutritional status of dependent patients has been little studied. This study allows us to know nutritional risk from different points of view: diet, anthropometry and biochemistry in dependent patients at

Nutrition education intervention for dependent patients: protocol of a randomized controlled trial

Directory of Open Access Journals (Sweden)

Arija Victoria

2012-05-01

Full Text Available Abstract Background Malnutrition in dependent patients has a high prevalence and can influence the prognosis associated with diverse pathologic processes, decrease quality of life, and increase morbidity-mortality and hospital admissions. The aim of the study is to assess the effect of an educational intervention for caregivers on the nutritional status of dependent patients at risk of malnutrition. Methods/Design Intervention study with control group, randomly allocated, of 200 patients of the Home Care Program carried out in 8 Primary Care Centers (Spain. These patients are dependent and at risk of malnutrition, older than 65, and have caregivers. The socioeconomic and educational characteristics of the patient and the caregiver are recorded. On a schedule of 0–6–12 months, patients are evaluated as follows: Mini Nutritional Assessment (MNA, food intake, dentures, degree of dependency (Barthel test, cognitive state (Pfeiffer test, mood status (Yesavage test, and anthropometric and serum parameters of nutritional status: albumin, prealbumin, transferrin, haemoglobin, lymphocyte count, iron, and ferritin. Prior to the intervention, the educational procedure and the design of educational material are standardized among nurses. The nurses conduct an initial session for caregivers and then monitor the education impact at home every month (4 visits up to 6 months. The North American Nursing Diagnosis Association (NANDA methodology will be used. The investigators will study the effect of the intervention with caregivers on the patient’s nutritional status using the MNA test, diet, anthropometry, and biochemical parameters. Bivariate normal test statistics and multivariate models will be created to adjust the effect of the intervention. The SPSS/PC program will be used for statistical analysis. Discussion The nutritional status of dependent patients has been little studied. This study allows us to know nutritional risk from different points of

PENERAPAN REGRESI PROBIT BIVARIAT UNTUK MENDUGA FAKTOR-FAKTOR YANG MEMENGARUHI KELULUSAN MAHASISWA (Studi Kasus: Mahasiswa Fakultas MIPA Unversitas Udayana

Directory of Open Access Journals (Sweden)

NI GUSTI KETUT TRISNA PRADNYANTARI

2015-06-01

Full Text Available The aim of this research to estimate the factors that affect students graduation using bivariate probit regression. Bivariate probit regression is a statistical method that involves two response variables which are qualitative and the independent variables are qualitative, quantitative, or a combination of both. In bivariate probit regression model, the result obtained is the probability of the response variable. The result of this research are the factors that affect significantly for students graduation based on study period are majors, sex, and duration of the thesis, while the factors that significantly for students graduation based on GPA are the entry system, duration of the thesis and the number of parents’ dependents.

Modelling the vicious circle between obesity and physical activity in children and adolescents using a bivariate probit model with endogenous regressors.

Science.gov (United States)

Yeh, C-Y; Chen, L-J; Ku, P-W; Chen, C-M

2015-01-01

The increasing prevalence of obesity in children and adolescents has become one of the most important public health issues around the world. Lack of physical activity is a risk factor for obesity, while being obese could reduce the likelihood of participating in physical activity. Failing to account for the endogeneity between obesity and physical activity would result in biased estimation. This study investigates the relationship between overweight and physical activity by taking endogeneity into consideration. It develops an endogenous bivariate probit model estimated by the maximum likelihood method. The data included 4008 boys and 4197 girls in the 5th-9th grades in Taiwan in 2007-2008. The relationship between overweight and physical activity is significantly negative in the endogenous model, but insignificant in the comparative exogenous model. This endogenous relationship presents a vicious circle in which lower levels of physical activity lead to overweight, while those who are already overweight engage in less physical activity. The results not only reveal the importance of endogenous treatment, but also demonstrate the robust negative relationship between these two factors. An emphasis should be put on overweight and obese children and adolescents in order to break the vicious circle. Promotion of physical activity by appropriate counselling programmes and peer support could be effective in reducing the prevalence of obesity in children and adolescents.

The self-similar field and its application to a diffusion problem

International Nuclear Information System (INIS)

Michelitsch, Thomas M

2011-01-01

We introduce a continuum approach which accounts for self-similarity as a symmetry property of an infinite medium. A self-similar Laplacian operator is introduced which is the source of self-similar continuous fields. In this way ‘self-similar symmetry’ appears in an analogous manner as transverse isotropy or cubic symmetry of a medium. As a consequence of the self-similarity the Laplacian is a non-local fractional operator obtained as the continuum limit of the discrete self-similar Laplacian introduced recently by Michelitsch et al (2009 Phys. Rev. E 80 011135). The dispersion relation of the Laplacian and its Green’s function is deduced in closed forms. As a physical application of the approach we analyze a self-similar diffusion problem. The statistical distributions, which constitute the solutions of this problem, turn out to be Lévi-stable distributions with infinite variances characterizing the statistics of one-dimensional Lévi flights. The self-similar continuum approach introduced in this paper has the potential to be applied on a variety of scale invariant and fractal problems in physics such as in continuum mechanics, electrodynamics and in other fields. (paper)

Harmonic maps of V-manifolds

International Nuclear Information System (INIS)

Chiang, Yuan-Jen.

1989-01-01

Harmonic maps between manifolds are described as the critical maps of their associated energy functionals. By using Sampson's method [Sam1], the author constructs a Sobolev's chain on a compact V-manifold and obtain Rellich's Theorem (Theorem 3.1), Sobolev's Theorem (Theorem 3.2), the regularity theorem (Theorem 3.3), the property of the eigenspaces for the Laplacian (Theorem 3.5) and the solvability of Laplacian (Theorem 3.6). Then, with these results, he constructs the Green's functions for the Laplacian on a compact V-manifold M in Proposition 4.1; and obtain an orthonormal basis for L 2 (M) formed by the eigenfunctions of the Laplacian corresponding to the eigenvalues in Proposition 4.2. He also estimates the eigenvalues and eigenfunctions of the Laplacian in Theorem 4.3, which is used to construct the heat kernel on a compact V-manifold in Proposition 5.1. Afterwards, he compares the G-invariant heat kernel functions with the G-invariant fundamental solutions of heat equations in the finite V-charts of a compact V-manifold in Theorem 6.1, and then study two integral operators associated to the heat kernel on a compact V-manifold in section 7. With all the preceding results established, in Theorem 8.3 he uses successive approximations to prove the existence of the solutions of parabolic equations on V-manifolds. Finally, he uses Theorem 8.3 to show the existence of harmonic maps from compact V-manifolds into compact Riemannian manifolds in Theorem 9.1 which extends Eells-Sampson's results [E-S

A general framework for regularized, similarity-based image restoration.

Science.gov (United States)

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

Zeta functions and regularized determinants related to the Selberg trace formula

DEFF Research Database (Denmark)

Momeni, Arash; Venkov, Alexei

determinants of one dimensional Schroedinger operator for harmonic oscillator. We decompose the determinant of the automorphic Laplacian into a product of the determinants where each factor is a determinant representation of a zeta function related to Selberg's trace formula. Then we derive an identity...... connecting the determinants of the automorphic Laplacians on different Riemannian surfaces related to the arithmetical groups. Finally, by using the Jacquet-Langlands correspondence we connect the determinant of the automorphic Laplacian for the unit group of quaternions to the product of the determinants......For a general Fuchsian group of the first kind with an arbitrary unitary representation we define the zeta functions related to the contributions of the identity, hyperbolic, elliptic and parabolic conjugacy classes in Selberg's trace formula. We present Selberg's zeta function in terms...

Dependence of US hurricane economic loss on maximum wind speed and storm size

International Nuclear Information System (INIS)

Zhai, Alice R; Jiang, Jonathan H

2014-01-01

Many empirical hurricane economic loss models consider only wind speed and neglect storm size. These models may be inadequate in accurately predicting the losses of super-sized storms, such as Hurricane Sandy in 2012. In this study, we examined the dependences of normalized US hurricane loss on both wind speed and storm size for 73 tropical cyclones that made landfall in the US from 1988 through 2012. A multi-variate least squares regression is used to construct a hurricane loss model using both wind speed and size as predictors. Using maximum wind speed and size together captures more variance of losses than using wind speed or size alone. It is found that normalized hurricane loss (L) approximately follows a power law relation with maximum wind speed (V max ) and size (R), L = 10 c V max a R b , with c determining an overall scaling factor and the exponents a and b generally ranging between 4–12 and 2–4 respectively. Both a and b tend to increase with stronger wind speed. Hurricane Sandy’s size was about three times of the average size of all hurricanes analyzed. Based on the bi-variate regression model that explains the most variance for hurricanes, Hurricane Sandy’s loss would be approximately 20 times smaller if its size were of the average size with maximum wind speed unchanged. It is important to revise conventional empirical hurricane loss models that are only dependent on maximum wind speed to include both maximum wind speed and size as predictors. (letters)

Investigations of grain size dependent sediment transport phenomena on multiple scales

Science.gov (United States)

Thaxton, Christopher S.

Sediment transport processes in coastal and fluvial environments resulting from disturbances such as urbanization, mining, agriculture, military operations, and climatic change have significant impact on local, regional, and global environments. Primarily, these impacts include the erosion and deposition of sediment, channel network modification, reduction in downstream water quality, and the delivery of chemical contaminants. The scale and spatial distribution of these effects are largely attributable to the size distribution of the sediment grains that become eligible for transport. An improved understanding of advective and diffusive grain-size dependent sediment transport phenomena will lead to the development of more accurate predictive models and more effective control measures. To this end, three studies were performed that investigated grain-size dependent sediment transport on three different scales. Discrete particle computer simulations of sheet flow bedload transport on the scale of 0.1--100 millimeters were performed on a heterogeneous population of grains of various grain sizes. The relative transport rates and diffusivities of grains under both oscillatory and uniform, steady flow conditions were quantified. These findings suggest that boundary layer formalisms should describe surface roughness through a representative grain size that is functionally dependent on the applied flow parameters. On the scale of 1--10m, experiments were performed to quantify the hydrodynamics and sediment capture efficiency of various baffles installed in a sediment retention pond, a commonly used sedimentation control measure in watershed applications. Analysis indicates that an optimum sediment capture effectiveness may be achieved based on baffle permeability, pond geometry and flow rate. Finally, on the scale of 10--1,000m, a distributed, bivariate watershed terain evolution module was developed within GRASS GIS. Simulation results for variable grain sizes and for

Analisis Faktor Permintaan Non Fungsional Kelompok Non-Member Terhadap Permintaan (Seri 2

Directory of Open Access Journals (Sweden)

Iskandar Putong

2011-11-01

Full Text Available Factor analysis of non functional Demand Non-Member On to Demand aimed to discover whether there is significant influence of non-functional variable on demand. Three independent variables (the effect, ie, X1 for Snob Effect (Mode, X2 for the Bandwagon effect (Prestige and X3 for the Veblen Effect (Show-off and 1 dependent variable Y for Demand. The number of respondents of 50 and 22 indicators is statistically valid. Analysis tool using the Model Correlation and simple Regression (Simple/Bivariate, Correlation and Regression Simultaneously (Multiple Regression and Partial Correlation. The results of analysis proved statistically with LOC of 95%, indicating that the bivariate, partial unison and Simultaneously there is positive and significant correlation between variables X to Y, except for variable X2 (Prestige on Bivariate correlation. 

Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.

Science.gov (United States)

Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil

2017-01-19

Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.

Dynamics-based centrality for directed networks.

Science.gov (United States)

Masuda, Naoki; Kori, Hiroshi

2010-11-01

Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

Abandonment of nicotine dependence treatment: A cohort study

Directory of Open Access Journals (Sweden)

Maritza Muzzi Cardozo Pawlina

Full Text Available CONTEXT AND OBJECTIVE: Non-adherence to treatment is one of the hindering factors in the process of smoking cessation. This study aimed to compare sociodemographic characteristics, smoking status and motivation among smokers who maintained or abandoned treatment to stop smoking, and to analyze associations between sociodemographic factors and smoking. DESIGN AND SETTING: Cohort study on 216 smokers who were attended at healthcare units in Cuiabá, Mato Grosso. METHODS: The instruments used were the Fagerström, URICA and CAGE questionnaires. Data from the initial evaluation was analyzed using the two-proportion test (α < 0.05. The patients were monitored for six months and those who abandoned treatment were accounted for. Bivariate analysis was conducted, using crude prevalence ratios and 5% significance level (P < 0.05, with abandonment of treatment as the outcome variable. Associations with P < 0.20 were selected for multiple robust Poisson regression (RPa. RESULTS: The abandonment rate was 34.26%. Males and individuals in the 20-39 age group, in employment, with low motivation, with shorter time smoking and lower tobacco intake predominated in the dropout group. In the final model, gender (RPa 1.47; 95% CI: 1.03-2.10 and age group (RPa 3.77; 95% CI: 1.47-9.67 remained associated with abandonment. CONCLUSION: Males and individuals in the 20-39 age group, in employment, with low motivation, with shorter time smoking and lower tobacco intake more frequently abandoned the treatment. Male gender and younger age group were associated with abandonment of nicotine dependence treatment.

Analysis of multi-species point patterns using multivariate log Gaussian Cox processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah

Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...

Determinantal spanning forests on planar graphs

OpenAIRE

Kenyon, Richard

2017-01-01

We generalize the uniform spanning tree to construct a family of determinantal measures on essential spanning forests on periodic planar graphs in which every component tree is bi-infinite. Like the uniform spanning tree, these measures arise naturally from the laplacian on the graph. More generally these results hold for the "massive" laplacian determinant which counts rooted spanning forests with weight $M$ per finite component. These measures typically have a form of conformal invariance, ...

Conjugate gradient coupled with multigrid for an indefinite problem

Science.gov (United States)

Gozani, J.; Nachshon, A.; Turkel, E.

1984-01-01

An iterative algorithm for the Helmholtz equation is presented. This scheme was based on the preconditioned conjugate gradient method for the normal equations. The preconditioning is one cycle of a multigrid method for the discrete Laplacian. The smoothing algorithm is red-black Gauss-Seidel and is constructed so it is a symmetric operator. The total number of iterations needed by the algorithm is independent of h. By varying the number of grids, the number of iterations depends only weakly on k when k(3)h(2) is constant. Comparisons with a SSOR preconditioner are presented.

A simplified method of estimating noise power spectra

International Nuclear Information System (INIS)

Hanson, K.M.

1998-01-01

A technique to estimate the radial dependence of the noise power spectrum of images is proposed in which the calculations are conducted solely in the spatial domain of the noise image. The noise power spectrum averaged over a radial spatial-frequency interval is obtained form the variance of a noise image that has been convolved with a small kernel that approximates a Laplacian operator. Recursive consolidation of the image by factors of two in each dimension yields estimates of the noise power spectrum over that full range of spatial frequencies

Review on mathematical basis for thermal conduction equation

Energy Technology Data Exchange (ETDEWEB)

Park, D. G.; Kim, H. M

2007-10-15

In the view point of thermal conductivity measurement technology, It is very useful to understand mathematical theory of thermal conduction equation in order to evaluation of measurement data and to solve diverse technical problem in measurement. To approach this mathematical theory, thermal conduction equation is derived by Fourier thermal conduction law. Since thermal conduction equation depends on the Lapacian operator basically, mathematical meaning of Lapalacian and various diffusion equation including Laplacian have been studied. Stum-Liouville problem and Bessel function were studied in this report to understand analytical solution of various diffusion equation.

Review on mathematical basis for thermal conduction equation

International Nuclear Information System (INIS)

Park, D. G.; Kim, H. M.

2007-10-01

In the view point of thermal conductivity measurement technology, It is very useful to understand mathematical theory of thermal conduction equation in order to evaluation of measurement data and to solve diverse technical problem in measurement. To approach this mathematical theory, thermal conduction equation is derived by Fourier thermal conduction law. Since thermal conduction equation depends on the Lapacian operator basically, mathematical meaning of Lapalacian and various diffusion equation including Laplacian have been studied. Stum-Liouville problem and Bessel function were studied in this report to understand analytical solution of various diffusion equation

Regional Analysis of Precipitation by Means of Bivariate Distribution Adjusted by Maximum Entropy; Analisis regional de precipitacion con base en una distribucion bivariada ajustada por maxima entropia

Energy Technology Data Exchange (ETDEWEB)

Escalante Sandoval, Carlos A.; Dominguez Esquivel, Jose Y. [Universidad Nacional Autonoma de Mexico (Mexico)

2001-09-01

The principle of maximum entropy (POME) is used to derive an alternative method of parameter estimation for the bivariate Gumbel distribution. A simple algorithm for this parameter estimation technique is presented. This method is applied to analyze the precipitation in a region of Mexico. Design events are compered with those obtained by the maximum likelihood procedure. According to the results, the proposed technique is a suitable option to be considered when performing frequency analysis of precipitation with small samples. [Spanish] El principio de maxima entropia, conocido como POME, es utilizado para derivar un procedimiento alternativo de estimacion de parametros de la distribucion bivariada de valores extremos con marginales Gumbel. El modelo se aplica al analisis de la precipitacion maxima en 24 horas en una region de Mexico y los eventos de diseno obtenidos son comparados con los proporcionados por la tecnica de maxima verosimilitud. De acuerdo con los resultados obtenidos, se concluye que la tecnica propuesta representa una buena opcion, sobre todo para el caso de muestras pequenas.

Association of Supply Type with Fecal Contamination of Source Water and Household Stored Drinking Water in Developing Countries: A Bivariate Meta-analysis.

Science.gov (United States)

Shields, Katherine F; Bain, Robert E S; Cronk, Ryan; Wright, Jim A; Bartram, Jamie

2015-12-01

Access to safe drinking water is essential for health. Monitoring access to drinking water focuses on water supply type at the source, but there is limited evidence on whether quality differences at the source persist in water stored in the household. We assessed the extent of fecal contamination at the source and in household stored water (HSW) and explored the relationship between contamination at each sampling point and water supply type. We performed a bivariate random-effects meta-analysis of 45 studies, identified through a systematic review, that reported either the proportion of samples free of fecal indicator bacteria and/or individual sample bacteria counts for source and HSW, disaggregated by supply type. Water quality deteriorated substantially between source and stored water. The mean percentage of contaminated samples (noncompliance) at the source was 46% (95% CI: 33, 60%), whereas mean noncompliance in HSW was 75% (95% CI: 64, 84%). Water supply type was significantly associated with noncompliance at the source (p water (OR = 0.2; 95% CI: 0.1, 0.5) and HSW (OR = 0.3; 95% CI: 0.2, 0.8) from piped supplies had significantly lower odds of contamination compared with non-piped water, potentially due to residual chlorine. Piped water is less likely to be contaminated compared with other water supply types at both the source and in HSW. A focus on upgrading water services to piped supplies may help improve safety, including for those drinking stored water.

Calculus of bivariant function

OpenAIRE

PTÁČNÍK, Jan

2011-01-01

This thesis deals with the introduction of function of two variables and differential calculus of this function. This work should serve as a textbook for students of elementary school's teacher. Each chapter contains a summary of basic concepts and explanations of relationships, then solved model exercises of the topic and finally the exercises, which should solve the student himself. Thesis have transmit to students basic knowledges of differential calculus of functions of two variables, inc...

Socioeconomic status and health : A new approach to the measurement of bivariate inequality

NARCIS (Netherlands)

Erreygers, G.; Kessels, R.

2017-01-01

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health

Layer potentials, Green's formulae, Kac's problem, and refined Hardy inequality on homogeneous Carnot groups

OpenAIRE

Ruzhansky, Michael; Suragan, Durvudkhan

2015-01-01

We propose the analogues of boundary layer potentials for the sub-Laplacian on homogeneous Carnot groups/stratified Lie groups and prove continuity results for them. In particular, we show continuity of the single layer potential and establish the Plemelj type jump relations for the double layer potential. We prove sub-Laplacian adapted versions of the Stokes theorem as well as of Green's first and second formulae on homogeneous Carnot groups. Several applications to boundary value problems a...

Layer potentials, Kac's problem, and refined Hardy inequality on homogeneous Carnot groups

OpenAIRE

Ruzhansky, Michael; Suragan, Durvudkhan

2017-01-01

We propose the analogues of boundary layer potentials for the sub-Laplacian on homogeneous Carnot groups/stratified Lie groups and prove continuity results for them. In particular, we show continuity of the single layer potential and establish the Plemelj type jump relations for the double layer potential. We prove sub-Laplacian adapted versions of the Stokes theorem as well as of Green's first and second formulae on homogeneous Carnot groups. Several applications to boundary value problems a...

Ultrawide Bandwidth Receiver Based on a Multivariate Generalized Gaussian Distribution

KAUST Repository

Ahmed, Qasim Zeeshan

2015-04-01

Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively. © 2002-2012 IEEE.

Improved integrability of the gradients of solutions of elliptic equations with variable nonlinearity exponent

International Nuclear Information System (INIS)

Zhikov, Vasilii V; Pastukhova, Svetlana E

2008-01-01

Elliptic equations of p(x)-Laplacian type are investigated. There is a well-known logarithmic condition on the modulus of continuity of the nonlinearity exponent p(x), which ensures that a Laplacian with variable order of nonlinearity inherits many properties of the usual p-Laplacian of constant order. One of these is the so-called improved integrability of the gradient of the solution. It is proved in this paper that this property holds also under a slightly more general condition on the exponent p(x), although then the improvement of integrability is logarithmic rather than power-like. The method put forward is based on a new generalization of Gehring's lemma, which relies upon the reverse Hoelder inequality 'with increased support and exponent on the right-hand side'. A counterexample is constructed that reveals the extent to which the condition on the modulus of continuity obtained is sharp. Bibliography: 28 titles.

Scattering theory for Riemannian Laplacians

DEFF Research Database (Denmark)

Ito, Kenichi; Skibsted, Erik

In this paper we introduce a notion of scattering theory for the Laplace-Beltrami operator on non-compact, connected and complete Riemannian manifolds. A principal condition is given by a certain positive lower bound of the second fundamental form of angular submanifolds at infinity. Another...... condition is certain bounds of derivatives up to order one of the trace of this quantity. These conditions are shown to be optimal for existence and completeness of a wave operator. Our theory does not involve prescribed asymptotic behaviour of the metric at infinity (like asymptotic Euclidean or hyperbolic...

Analysing risk factors of co-occurrence of schistosomiasis haematobium and hookworm using bivariate regression models: Case study of Chikwawa, Malawi

Directory of Open Access Journals (Sweden)

Bruce B.W. Phiri

2016-06-01

Full Text Available Schistosomiasis and soil-transmitted helminth (STH infections constitute a major public health problem in many parts of sub-Saharan Africa. In areas where prevalence of geo-helminths and schistosomes is high, co-infection with multiple parasite species is common, resulting in disproportionately elevated burden compared with single infections. Determining risk factors of co-infection intensity is important for better design of targeted interventions. In this paper, we examined risk factors of hookworm and S. haematobium co-infection intensity, in Chikwawa district, southern Malawi in 2005, using bivariate count models. Results show that hookworm and S. haematobium infections were much localised with small proportion of individuals harbouring more parasites especially among school-aged children. The risk of co-intensity with both hookworm and S. haematobium was high for all ages, although this diminished with increasing age, increased with fishing (hookworm: coefficient. = 12.29; 95% CI = 11.50–13.09; S. haematobium: 0.040; 95% CI = 0.0037, 3.832. Both infections were abundant in those with primary education (hookworm: coef. = 0.072; 95% CI = 0.056, 0.401 and S. haematobium: coef. = 0.286; 95% CI = 0.034, 0.538. However, much lower risk was observed for those who were farmers (hookworm: coef. = −0.349, 95% CI = −0.547,−0.150; S. haematobium: coef. −0.239, 95% CI = −0.406, −0.072. In conclusion, our findings suggest that efforts to control helminths infection should be co-integrated and health promotion campaigns should be aimed at school-going children and adults who are in constant contact with water.

Gender differences in prevalence and correlates of antisocial personality disorder among heroin dependent users in compulsory isolation treatment in China.

Science.gov (United States)

Yang, Mei; Mamy, Jules; Zhou, Liang; Liao, Yan-Hui; Wang, Qiang; Seewoobudul, Vasish; Xiao, Shui-Yuan; Hao, Wei

2014-03-01

Little is known about gender difference in correlates of antisocial personality disorder (ASPD) among drug users. To detect gender difference in correlates of ASPD in a Chinese heroin dependent sample. Structured interviews were conducted among 882 heroin dependent users in two compulsory isolation settings in Changsha, China. Descriptive statistics were employed to report sample characteristics by gender. Bivariate relationships were examined between co-occurring ASPD and variables measuring demographic, drug use, and psychiatric co-morbidities. Multivariate logistic regressions with stepwise forward method were conducted to determine independent predictors for co-occurring ASPD. All analyses examining correlates of co-occurring ASPD were conducted for the total, the male and the female participants respectively to detect both the common and the unique correlates of ASPD by gender. Of the total participants, 41.4% (54.2% of males and 15.4% of females) met the DSM-IV criteria of ASPD. For male participants, lower educational level, unemployment, unmarried, younger age at first heroin use, previous history of compulsory treatment, larger amounts of heroin used per day and poly-drug abuse during past month before admission, as well as psychiatric co-morbidities of lifetime major depressive disorder and borderline personality disorder were independent predictors for co-occurring ASPD; while for female participants, only three variables: younger age at first heroin use, paranoid personality disorder and borderline personality disorder were independent predictors for co-occurring ASPD. Gender differences in prevalence and correlates of ASPD among heroin dependent users were detected. The findings highlight a need for gender-specific interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Model-based VQ for image data archival, retrieval and distribution

Science.gov (United States)

Manohar, Mareboyana; Tilton, James C.

1995-01-01

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Trace formulae and spectral statistics for discrete Laplacians on regular graphs (I)

Energy Technology Data Exchange (ETDEWEB)

Oren, Idan; Godel, Amit; Smilansky, Uzy [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel)], E-mail: idan.oren@weizmann.ac.il, E-mail: amit.godel@weizmann.ac.il, E-mail: uzy.smilansky@weizmann.ac.il

2009-10-16

Trace formulae for d-regular graphs are derived and used to express the spectral density in terms of the periodic walks on the graphs under consideration. The trace formulae depend on a parameter w which can be tuned continuously to assign different weights to different periodic orbit contributions. At the special value w = 1, the only periodic orbits which contribute are the non-back-scattering orbits, and the smooth part in the trace formula coincides with the Kesten-McKay expression. As w deviates from unity, non-vanishing weights are assigned to the periodic walks with backscatter, and the smooth part is modified in a consistent way. The trace formulae presented here are the tools to be used in the second paper in this sequence, for showing the connection between the spectral properties of d-regular graphs and the theory of random matrices.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows.

Science.gov (United States)

Welderufael, B G; Janss, L L G; de Koning, D J; Sørensen, L P; Løvendahl, P; Fikse, W F

2017-06-01

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under

Independent component analysis of edge information for face recognition

CERN Document Server

Karande, Kailash Jagannath

2013-01-01

The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also propos

The analysis of dependence between extreme rainfall and storm surge in the coastal zone

Science.gov (United States)

Zheng, F.; Westra, S.

2012-12-01

Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as

Harnack's Inequality for Degenerate and Singular Parabolic Equations

CERN Document Server

DiBenedetto, Emmanuele; Vespri, Vincenzo

2012-01-01

Degenerate and singular parabolic equations have been the subject of extensive research for the last 25 years. Despite important achievements, the issue of the Harnack inequality for non-negative solutions to these equations, both of p-Laplacian and porous medium type, while raised by several authors, has remained basically open. Recently considerable progress has been made on this issue, to the point that, except for the singular sub-critical range, both for the p-laplacian and the porous medium equations, the theory is reasonably complete. It seemed therefore timely to trace a comprehensive

Diagnostic value of sTREM-1 in bronchoalveolar lavage fluid in ICU patients with bacterial lung infections: a bivariate meta-analysis.

Science.gov (United States)

Shi, Jia-Xin; Li, Jia-Shu; Hu, Rong; Li, Chun-Hua; Wen, Yan; Zheng, Hong; Zhang, Feng; Li, Qin

2013-01-01

The serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is a useful biomarker in differentiating bacterial infections from others. However, the diagnostic value of sTREM-1 in bronchoalveolar lavage fluid (BALF) in lung infections has not been well established. We performed a meta-analysis to assess the accuracy of sTREM-1 in BALF for diagnosis of bacterial lung infections in intensive care unit (ICU) patients. We searched PUBMED, EMBASE and Web of Knowledge (from January 1966 to October 2012) databases for relevant studies that reported diagnostic accuracy data of BALF sTREM-1 in the diagnosis of bacterial lung infections in ICU patients. Pooled sensitivity, specificity, and positive and negative likelihood ratios were calculated by a bivariate regression analysis. Measures of accuracy and Q point value (Q*) were calculated using summary receiver operating characteristic (SROC) curve. The potential between-studies heterogeneity was explored by subgroup analysis. Nine studies were included in the present meta-analysis. Overall, the prevalence was 50.6%; the sensitivity was 0.87 (95% confidence interval (CI), 0.72-0.95); the specificity was 0.79 (95% CI, 0.56-0.92); the positive likelihood ratio (PLR) was 4.18 (95% CI, 1.78-9.86); the negative likelihood ratio (NLR) was 0.16 (95% CI, 0.07-0.36), and the diagnostic odds ratio (DOR) was 25.60 (95% CI, 7.28-89.93). The area under the SROC curve was 0.91 (95% CI, 0.88-0.93), with a Q* of 0.83. Subgroup analysis showed that the assay method and cutoff value influenced the diagnostic accuracy of sTREM-1. BALF sTREM-1 is a useful biomarker of bacterial lung infections in ICU patients. Further studies are needed to confirm the optimized cutoff value.

Socioeconomic Status and Health: A New Approach to the Measurement of Bivariate Inequality

OpenAIRE

Erreygers, Guido; Kessels, Roselinde

2017-01-01

Abstract: We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to ineq...

Subsystem density functional theory with meta-generalized gradient approximation exchange-correlation functionals.

Science.gov (United States)

Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio

2015-04-21

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.

Thermal rectification based on phonon hydrodynamics and thermomass theory

Directory of Open Access Journals (Sweden)

Dong Yuan

2016-06-01

Full Text Available The thermal diode is the fundamental device for phononics. There are various mechanisms for thermal rectification, e.g. different temperature dependent thermal conductivity of two ends, asymmetric interfacial resistance, and nonlocal behavior of phonon transport in asymmetric structures. The phonon hydrodynamics and thermomass theory treat the heat conduction in a fluidic viewpoint. The phonon gas flowing through the media is characterized by the balance equation of momentum, like the Navier-Stokes equation for fluid mechanics. Generalized heat conduction law thereby contains the spatial acceleration (convection term and the viscous (Laplacian term. The viscous term predicts the size dependent thermal conductivity. Rectification appears due to the MFP supersession of phonons. The convection term also predicts rectification because of the inertia effect, like a gas passing through a nozzle or diffuser.

On two energy-like invariants of line graphs and related graph operations

Directory of Open Access Journals (Sweden)

Xiaodan Chen

2016-02-01

Full Text Available Abstract For a simple graph G of order n, let μ 1 ≥ μ 2 ≥ ⋯ ≥ μ n = 0 $\\mu_{1}\\geq\\mu_{2}\\geq\\cdots\\geq\\mu_{n}=0$ be its Laplacian eigenvalues, and let q 1 ≥ q 2 ≥ ⋯ ≥ q n ≥ 0 $q_{1}\\geq q_{2}\\geq\\cdots\\geq q_{n}\\geq0$ be its signless Laplacian eigenvalues. The Laplacian-energy-like invariant and incidence energy of G are defined as, respectively, LEL ( G = ∑ i = 1 n − 1 μ i and IE ( G = ∑ i = 1 n q i . $$\\mathit{LEL}(G=\\sum_{i=1}^{n-1}\\sqrt{ \\mu_{i}} \\quad\\mbox{and}\\quad \\mathit {IE}(G=\\sum_{i=1}^{n} \\sqrt{q_{i}}. $$ In this paper, we present some new upper and lower bounds on LEL and IE of line graph, subdivision graph, para-line graph and total graph of a regular graph, some of which improve previously known results. The main tools we use here are the Cauchy-Schwarz inequality and the Ozeki inequality.

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

International Nuclear Information System (INIS)

DeVries, Nicole A.; Gassman, Esther E.; Kallemeyn, Nicole A.; Shivanna, Kiran H.; Magnotta, Vincent A.; Grosland, Nicole M.

2008-01-01

To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans. Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen. The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing. This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques. (orig.)

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

Energy Technology Data Exchange (ETDEWEB)

DeVries, Nicole A.; Gassman, Esther E.; Kallemeyn, Nicole A. [The University of Iowa, Department of Biomedical Engineering, Center for Computer Aided Design, Iowa City, IA (United States); Shivanna, Kiran H. [The University of Iowa, Center for Computer Aided Design, Iowa City, IA (United States); Magnotta, Vincent A. [The University of Iowa, Department of Biomedical Engineering, Department of Radiology, Center for Computer Aided Design, Iowa City, IA (United States); Grosland, Nicole M. [The University of Iowa, Department of Biomedical Engineering, Department of Orthopaedics and Rehabilitation, Center for Computer Aided Design, Iowa City, IA (United States)

2008-01-15

To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans. Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen. The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing. This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques. (orig.)

Inter-dependence not Over-dependence: Reducing Urban Transport Energy Dependence

Energy Technology Data Exchange (ETDEWEB)

Saunders, Michael James; Rodrigues da Silva, Antonio Nelson

2007-07-01

A major issue of concern in today's world is urban transport energy dependence and energy supply security. In an energy inter-dependent world, energy over-dependence brings risks to urban transport systems. Many urban areas are over-dependent on finite petroleum resources for transport. New technology and the development and integration of renewable resources into transport energy systems may reduce some of the current transport energy dependence of urban areas. However, the most effective means of reducing energy dependence is to first design urban areas for this condition. An urban policy framework is proposed that requires transport energy dependence to be measured and controlled in the urban development process. A new tool has been created for this purpose, the Transport Energy Specification (TES), which measures transport energy dependence of urban areas. This creates the possibility for cities to regulate urban development with respect to energy dependence. Trial assessments were performed in Germany, New Zealand and Brazil; initial analysis by transport and government professionals shows promise of this tool being included into urban policy. The TES combined with a regulatory framework has the potential to significantly reduce transport energy consumption and dependence in urban areas in the future. (auth)

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African Journals Online (AJOL)

abp

2016-05-13

May 13, 2016 ... Descriptive and inferential statistical analysis was carried out depending on the nature of variables. .... Sampling technique .... Bivariate and multivariate binary logistic regression regressions were applied when the variables are normally .... through the traditional maternal and child health care programs.

Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)

Science.gov (United States)

Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.

2013-12-01

We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.

Assessment of Schrodinger Eigenmaps for target detection

Science.gov (United States)

Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek

2014-06-01

Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.

Development of a 3D-Multigroup program to simulate anomalous diffusion phenomena in the nuclear reactors

International Nuclear Information System (INIS)

Maleki Moghaddam, Nader; Afarideh, Hossein; Espinosa-Paredes, Gilberto

2015-01-01

Highlights: • The new version of neutron diffusion equation for simulating anomalous diffusion is presented. • Application of fractional calculus in the nuclear reactor is revealed. • A 3D-Multigroup program is developed based on the fractional operators. • The super-diffusion and sub-diffusion phenomena are modeled in the nuclear reactors core. - Abstract: The diffusion process is categorized in three parts, normal diffusion, super-diffusion and sub-diffusion. The classical neutron diffusion equation is used to model normal diffusion. A new scheme of derivatives is required to model anomalous diffusion phenomena. The fractional space derivatives are employed to model anomalous diffusion processes where a plume of particles spreads at an inconsistent rate with the classical Brownian motion model. In the fractional diffusion equation, the fractional Laplacians are used; therefore the statistical jump length of neutrons is unrestricted. It is clear that the fractional Laplacians are capable to model the anomalous phenomena in nuclear reactors. We have developed a NFDE-3D (neutron fractional diffusion equation) as a core calculation code to model normal and anomalous diffusion phenomena. The NFDE-3D is validated against the LMW-LWR reactor. The results demonstrate that reactors exhibit complex behavior versus order of the fractional derivatives which depends on the competition between neutron absorption and super-diffusion phenomenon

Prediction of partial synchronization in delay-coupled nonlinear oscillators, with application to Hindmarsh–Rose neurons

International Nuclear Information System (INIS)

Ünal, Hakkı Ulaş; Michiels, Wim

2013-01-01

The full synchronization of coupled nonlinear oscillators has been widely studied. In this paper we investigate conditions for which partial synchronization of time-delayed diffusively coupled systems arises. The coupling configuration of the systems is described by a directed graph. As a novel quantitative result we first give necessary and sufficient conditions for the presence of forward invariant sets characterized by partially synchronous motion. These conditions can easily be checked from the eigenvalues and eigenvectors of the graph Laplacian. Second, we perform stability analysis of the synchronized equilibria in a (gain,delay) parameter space. For this analysis the coupled nonlinear systems are linearized around the synchronized equilibria and then the resulting characteristic function is factorized. By such a factorization, it is shown that the relation between the behaviour of different agents at the zero of the characteristic function depends on the structure of the eigenvectors of the weighted Laplacian matrix. By determining the structure of the solutions in the unstable manifold, combined with the characterization of invariant sets, we predict which partially synchronous regimes occur and estimate the corresponding coupling gain and delay values. We apply the obtained results to networks of coupled Hindmarsh–Rose neurons and verify the occurrence of the expected partially synchronous regimes by using a numerical simulation. We also make a comparison with an existing approach based on Lyapunov functionals. (paper)

Multiview Hessian regularization for image annotation.

Science.gov (United States)

Liu, Weifeng; Tao, Dacheng

2013-07-01

The rapid development of computer hardware and Internet technology makes large scale data dependent models computationally tractable, and opens a bright avenue for annotating images through innovative machine learning algorithms. Semisupervised learning (SSL) therefore received intensive attention in recent years and was successfully deployed in image annotation. One representative work in SSL is Laplacian regularization (LR), which smoothes the conditional distribution for classification along the manifold encoded in the graph Laplacian, however, it is observed that LR biases the classification function toward a constant function that possibly results in poor generalization. In addition, LR is developed to handle uniformly distributed data (or single-view data), although instances or objects, such as images and videos, are usually represented by multiview features, such as color, shape, and texture. In this paper, we present multiview Hessian regularization (mHR) to address the above two problems in LR-based image annotation. In particular, mHR optimally combines multiple HR, each of which is obtained from a particular view of instances, and steers the classification function that varies linearly along the data manifold. We apply mHR to kernel least squares and support vector machines as two examples for image annotation. Extensive experiments on the PASCAL VOC'07 dataset validate the effectiveness of mHR by comparing it with baseline algorithms, including LR and HR.

Consensus of second-order multi-agent dynamic systems with quantized data

Energy Technology Data Exchange (ETDEWEB)

Guan, Zhi-Hong, E-mail: zhguan@mail.hust.edu.cn [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074 (China); Meng, Cheng [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074 (China); Liao, Rui-Quan [Petroleum Engineering College,Yangtze University, Jingzhou, 420400 (China); Zhang, Ding-Xue, E-mail: zdx7773@163.com [Petroleum Engineering College,Yangtze University, Jingzhou, 420400 (China)

2012-01-09

The consensus problem of second-order multi-agent systems with quantized link is investigated in this Letter. Some conditions are derived for the quantized consensus of the second-order multi-agent systems by the stability theory. Moreover, a result characterizing the relationship between the eigenvalues of the Laplacians matrix and the quantized consensus is obtained. Examples are given to illustrate the theoretical analysis. -- Highlights: ► A second-order multi-agent model with quantized data is proposed. ► Two sufficient and necessary conditions are obtained. ► The relationship between the eigenvalues of the Laplacians matrix and the quantized consensus is discovered.

Brownian distance covariance

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.

2010-01-01

Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...

Multifractal Modeling of Turbulent Mixing

Science.gov (United States)

Samiee, Mehdi; Zayernouri, Mohsen; Meerschaert, Mark M.

2017-11-01

Stochastic processes in random media are emerging as interesting tools for modeling anomalous transport phenomena. Applications include intermittent passive scalar transport with background noise in turbulent flows, which are observed in atmospheric boundary layers, turbulent mixing in reactive flows, and long-range dependent flow fields in disordered/fractal environments. In this work, we propose a nonlocal scalar transport equation involving the fractional Laplacian, where the corresponding fractional index is linked to the multifractal structure of the nonlinear passive scalar power spectrum. This work was supported by the AFOSR Young Investigator Program (YIP) award (FA9550-17-1-0150) and partially by MURI/ARO (W911NF-15-1-0562).

Reliability of redundant ductile structures with uncertain system ...

Indian Academy of Sciences (India)

tance, applied loads and geometric parameters, and in some cases in the .... Statistical dependence among (i) girder strengths ... element reliability solution techniques; such formulation unfortunately remains ..... The spread of plasticity through a member after failure of a section .... The following form of the bivariate Gumbel.

Histogram Estimators of Bivariate Densities

National Research Council Canada - National Science Library

Husemann, Joyce A

1986-01-01

One-dimensional fixed-interval histogram estimators of univariate probability density functions are less efficient than the analogous variable-interval estimators which are constructed from intervals...

BIMOND3, Monotone Bivariate Interpolation

International Nuclear Information System (INIS)

Fritsch, F.N.; Carlson, R.E.

2001-01-01

1 - Description of program or function: BIMOND is a FORTRAN-77 subroutine for piecewise bi-cubic interpolation to data on a rectangular mesh, which reproduces the monotonousness of the data. A driver program, BIMOND1, is provided which reads data, computes the interpolating surface parameters, and evaluates the function on a mesh suitable for plotting. 2 - Method of solution: Monotonic piecewise bi-cubic Hermite interpolation is used. 3 - Restrictions on the complexity of the problem: The current version of the program can treat data which are monotone in only one of the independent variables, but cannot handle piecewise monotone data

STABILITY OF LINEAR MULTIAGENT SCALAR SYSTEMS AND ITS DEPENDENCE ON CONNECTIVITY GRAPH

Directory of Open Access Journals (Sweden)

S. I. Tomashevich

2014-03-01

Full Text Available Multiagent systems are now finding increasingly wide applications in various engineering fields such as energy, transportation, robotics, aviation and others. There are two main aspects to be focused on when organizing multiagent systems: the dynamics of the agents themselves and the ways of their interaction. This interaction is determined by the structure of information connections between agents. Thus, there are several key points of multiagent systems study: the dynamics of individual agents and shape of the information graph. Formation dynamics, in general, is determined by a set of properties of agents and connectivity graph. The paper deals with the relationship between dynamics of agents and Laplace matrix, which is used to set the graph connections. The present research is based on the results given in the known paper by A. Fax and R. Murray (IEEE Trans. AC, 2004. An illustrative example is given, and the application problem of studying the formation dynamics consisting of the group of quadrocopters is presented. Information exchange between agents is determined in the paper by means of the conventional set of graphs. The paper presents an interpretation of the stability conditions and the method of system performance improvement based on these conditions. Motion of quadrocopters group along the flight height is used as an example for methodology application. The simulation results demonstrate the basic dependencies between the information graph shape (and, consequently, the eigenvalues of the Laplacian, which describes this graph and formation stability. Simulation and consideration of Nyquist diagram connection with the key points give an indication of the system stability and take steps to change the control laws. Necessary conditions for the formation stability are obtained on the basis of this research method. Research result makes it possible to create local control laws for agents to ensure the stability of motion in the selected

Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes.

Science.gov (United States)

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Xu, Richard Yi Da; Luo, Xiangfeng

2018-05-01

Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

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Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

"Minesweeper" and spectrum of discrete Laplacians

OpenAIRE

German, Oleg; Lakshtanov, Evgeny

2008-01-01

The paper is devoted to a problem inspired by the "Minesweeper" computer game. It is shown that certain configurations of open cells guarantee the existence and the uniqueness of solution. Mathematically the problem is reduced to some spectral properties of discrete differential operators. It is shown how the uniqueness can be used to create a new game which preserves the spirit of "Minesweeper" but does not require a computer.

[Burden, empathy, and resilience in dependent people caregivers].

Science.gov (United States)

Navarro-Abal, Yolanda; López-López, María José; Climent-Rodríguez, José Antonio; Gómez-Salgado, Juan

2018-02-10

To analyse the differences in perceived burden between family caregivers who are users of patient associations and those who are not; to assess the relationship between burden, resilience, and empathy levels. Retrospective ex post facto study of two groups, one of them quasi control. The sample was composed of 155 informal caregivers (28 men and 155 women); 109 of them were users of patient relatives' associations and 46 were not. Both descriptive and bivariate comparative analyses were carried out. Caregivers who were members of patient associations showed lower burden and empathy levels than those who were not. This highlighted that the higher their level of perceived burden, the lower their level of resilience. Belonging to carers' associations results in a lower level of perceived burden and a lower risk of developing compassion fatigue syndrome. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

An efficient reconstruction algorithm for differential phase-contrast tomographic images from a limited number of views

International Nuclear Information System (INIS)

Sunaguchi, Naoki; Yuasa, Tetsuya; Gupta, Rajiv; Ando, Masami

2015-01-01

The main focus of this paper is reconstruction of tomographic phase-contrast image from a set of projections. We propose an efficient reconstruction algorithm for differential phase-contrast computed tomography that can considerably reduce the number of projections required for reconstruction. The key result underlying this research is a projection theorem that states that the second derivative of the projection set is linearly related to the Laplacian of the tomographic image. The proposed algorithm first reconstructs the Laplacian image of the phase-shift distribution from the second-derivative of the projections using total variation regularization. The second step is to obtain the phase-shift distribution by solving a Poisson equation whose source is the Laplacian image previously reconstructed under the Dirichlet condition. We demonstrate the efficacy of this algorithm using both synthetically generated simulation data and projection data acquired experimentally at a synchrotron. The experimental phase data were acquired from a human coronary artery specimen using dark-field-imaging optics pioneered by our group. Our results demonstrate that the proposed algorithm can reduce the number of projections to approximately 33% as compared with the conventional filtered backprojection method, without any detrimental effect on the image quality

Spectral methods for the detection of network community structure: a comparative analysis

International Nuclear Information System (INIS)

Shen, Hua-Wei; Cheng, Xue-Qi

2010-01-01

Spectral analysis has been successfully applied to the detection of community structure of networks, respectively being based on the adjacency matrix, the standard Laplacian matrix, the normalized Laplacian matrix, the modularity matrix, the correlation matrix and several other variants of these matrices. However, the comparison between these spectral methods is less reported. More importantly, it is still unclear which matrix is more appropriate for the detection of community structure. This paper answers the question by evaluating the effectiveness of these five matrices against benchmark networks with heterogeneous distributions of node degree and community size. Test results demonstrate that the normalized Laplacian matrix and the correlation matrix significantly outperform the other three matrices at identifying the community structure of networks. This indicates that it is crucial to take into account the heterogeneous distribution of node degree when using spectral analysis for the detection of community structure. In addition, to our surprise, the modularity matrix exhibits very similar performance to the adjacency matrix, which indicates that the modularity matrix does not gain benefits from using the configuration model as a reference network with the consideration of the node degree heterogeneity

The Designated Convergence Rate Problems of Consensus or Flocking of Double-Integrator Agents With General Nonequal Velocity and Position Couplings: Further Results and Patterns of Convergence Rate Contours.

Science.gov (United States)

Li, Wei

2017-05-01

This paper considers the designated convergence rate (DCR) (or the designated convergence margin) problems of consensus or flocking of coupled double-integrator agents. The DCR problems are more valuable for systems design than just convergence or stability conditions. The system setting in this paper is general, i.e., the velocity coupling and position coupling (VCPC) between agents, respectively, are set to be general and nonequal (up to rescaling), together with distinct damping and stiffness gains for the VCPC, respectively. This paper has two primary contributions on consensus: 1) further necessary and sufficient conditions are established to guarantee the DCR problems of the system, which have enriched the previous results and 2) the patterns of the convergence rate contours for the DCR are characterized, in terms of the damping and stiffness gains, which are closely related to the characteristics of the spectra of the two Laplacian matrices of the VCPC. Additionally, this paper has a contribution on matrix theory, i.e., the sufficient conditions for the simultaneous upper-triangularization of two independent Laplacian matrices, particularly from an easily verifiable topological perspective on the corresponding digraphs of these Laplacian matrices.

Denoising of B1+ field maps for noise-robust image reconstruction in electrical properties tomography

International Nuclear Information System (INIS)

Michel, Eric; Hernandez, Daniel; Cho, Min Hyoung; Lee, Soo Yeol

2014-01-01

Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B 1 + maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B 1 + maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B 1 + maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. Results: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. Conclusions: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T

Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.

Science.gov (United States)

Ma, Yuanyuan; Hu, Xiaohua; He, Tingting; Jiang, Xingpeng

2016-12-01

Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H T ) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering. Copyright © 2016. Published by Elsevier Inc.

Quantum mechanics on Laakso spaces

Science.gov (United States)

Kauffman, Christopher J.; Kesler, Robert M.; Parshall, Amanda G.; Stamey, Evelyn A.; Steinhurst, Benjamin A.

2012-04-01

We first review the spectrum of the Laplacian operator on a general Laakso space before considering modified Hamiltonians for the infinite square well, parabola, and Coulomb potentials. Additionally, we compute the spectrum for the Laplacian and its multiplicities when certain regions of a Laakso space are compressed or stretched and calculate the Casimir force experienced by two uncharged conducting plates by imposing physically relevant boundary conditions and then analytically regularizing the resulting zeta function. Lastly, we derive a general formula for the spectral zeta function and its derivative for Laakso spaces with strict self-similar structure before listing explicit spectral values for some special cases

Socioeconomic Status and Health: A New Approach to the Measurement of Bivariate Inequality.

Science.gov (United States)

Erreygers, Guido; Kessels, Roselinde

2017-06-23

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to inequality in the socioeconomic distribution and to inequality in the health distribution. As an empirical illustration, we make a comparative study of the relation between income and well-being in 16 European countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4.

Socioeconomic Status and Health: A New Approach to the Measurement of Bivariate Inequality

Science.gov (United States)

Kessels, Roselinde

2017-01-01

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to inequality in the socioeconomic distribution and to inequality in the health distribution. As an empirical illustration, we make a comparative study of the relation between income and well-being in 16 European countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4. PMID:28644405

Content and Method in the Teaching of Marketing Research Revisited

Science.gov (United States)

Wilson, Holt; Neeley, Concha; Niedzwiecki, Kelly

2009-01-01

This paper presents the findings from a survey of marketing research faculty. The study finds SPSS is the most used statistical software, that cross tabulation, single, independent, and dependent t-tests, and ANOVA are among the most important statistical tools according to respondents. Bivariate and multiple regression are also considered…

Comparison of different spatial transformations applied to EEG data: A case study of error processing.

Science.gov (United States)

Cohen, Michael X

2015-09-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.

Individualized Treatment for Tobacco Dependence in Addictions Treatment Settings: The Role of Current Depressive Symptoms on Outcomes at 3 and 6 Months.

Science.gov (United States)

Zawertailo, Laurie A; Baliunas, Dolly; Ivanova, Anna; Selby, Peter L

2015-08-01

Individuals with concurrent tobacco dependence and other addictions often report symptoms of low mood and depression and as such may have more difficulty quitting smoking. We hypothesized that current symptoms of depression would be a significant predictor of quit success among a group of smokers receiving individualized treatment for tobacco dependence within addiction treatment settings. Individuals in treatment for other addictions were enrolled in a smoking cessation program involving brief behavioral counseling and individualized dosing of nicotine replacement therapy. The baseline assessment included the Patient Health Questionnaire (PHQ9) for depression. Smoking cessation outcomes were measured at 3 and 6 months post-enrollment. Bivariate associations between cessation outcomes and PHQ9 score were analyzed. Of the 1,196 subjects enrolled to date, 1,171 (98%) completed the PHQ9. Moderate to severe depression (score >9) was reported by 28% of the sample, and another 29% reported mild depression (score between 5 and 9). Contrary to the extant literature and other findings by our own group, there was no association between current depression and cessation outcome at either 3 months (n = 1,171) (17.0% in those with PHQ9 > 9 vs. 19.8% in those with PHQ9 addictions treatment setting. These data indicate that patients in an addictions treatment setting can successfully quit smoking regardless of current depressive symptoms. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The application of Regge calculus to quantum gravity and quantum field theory in a curved background

International Nuclear Information System (INIS)

Warner, N.P.

1982-01-01

The application of Regge calculus to quantum gravity and quantum field theory in a curved background is discussed. A discrete form of exterior differential calculus is developed, and this is used to obtain Laplacians for p-forms on the Regge manifold. To assess the accuracy of these approximations, the eigenvalues of the discrete Laplacians were calculated for the regular tesselations of S 2 and S 3 . The results indicate that the methods obtained in this paper may be used in curved space-times with an accuracy comparing with that obtained in lattice gauge theories on a flat background. It also becomes evident that Regge calculus provides particularly suitable lattices for Monte-Carlo techniques. (author)

Density distortion within a rotating body

International Nuclear Information System (INIS)

Lanzano, P.

1975-01-01

This paper ascertains the distortion of the density distribution within a self-gravitating body in hydrostatic equilibrium under the influence of rotation. For this purpose, the Poisson equation has been solved by using the undistorted density profile within the Laplacian to obtain the distorted density. The Laplacian has been expressed in terms of a system of curvilinear coordinates for which the equipotential surfaces constitute a family of fundamental surfaces. In performing the requisite algebraic manipulations, the Clairaut and Radau equations developed in a previous paper (Lanzano,1974) were utilized to eliminate the derivatives of the elements pertaining to the equipotential surfaces. The density distortion has been obtained up to third-order terms in a small rotational parameter. (Auth.)

Stochastic Frontier Models with Dependent Errors based on Normal and Exponential Margins || Modelos de frontera estocástica con errores dependientes basados en márgenes normal y exponencial

Directory of Open Access Journals (Sweden)

Gómez-Déniz, Emilio

2017-06-01

Full Text Available Following the recent work of Gómez-Déniz and Pérez-Rodríguez (2014, this paper extends the results obtained there to the normal-exponential distribution with dependence. Accordingly, the main aim of the present paper is to enhance stochastic production frontier and stochastic cost frontier modelling by proposing a bivariate distribution for dependent errors which allows us to nest the classical models. Closed-form expressions for the error term and technical efficiency are provided. An illustration using real data from the econometric literature is provided to show the applicability of the model proposed. || Continuando el reciente trabajo de Gómez-Déniz y Pérez-Rodríguez (2014, el presente artículo extiende los resultados obtenidos a la distribución normal-exponencial con dependencia. En consecuencia, el principal propósito de este artículo es mejorar el modelado de la frontera estocástica tanto de producción como de coste proponiendo para ello una distribución bivariante para errores dependientes que nos permitan encajar los modelos clásicos. Se obtienen las expresiones en forma cerrada para el término de error y la eficiencia técnica. Se ilustra la aplicabilidad del modelo propouesto usando datos reales existentes en la literatura econométrica.

[Dependent patient and interpersonal dependency: psychotherapeutic strategies].

Science.gov (United States)

Versaevel, C

2012-04-01

This article is a review of psychotherapies for patients suffering from dependent personality and interpersonal dependency. We synthesized articles making reference to this question, notably those written by Bornstein, author who refers to the dependent personality. We highlighted the psychotherapies that have been the object of an evaluation. The research on the subject is sparse: only eight studies permitting assessment of psychotherapies in this indication in 2005. Besides these psychotherapies, we detailed other approaches which are used by practitioners in these indications. The therapy does not aim at autonomy "at all costs", but that the patient finds a dependence "adapted" to his/her environment. Before starting a therapy, an evaluation is useful to specify the type of dependence. First of all, is there a "pathological" dependence? Is the suffering of the patient secondary to his personality or not supportive enough? Does insight exist? What is the reaction of the patient if we suggest the hypothesis of a dependence on his/her part? Does he/she consider this idea or reject it? Finally, is the dependence primary or secondary? For that purpose, it is necessary to study the biography of the patient and the appearance of the comorbidity over time. The primary dependence is seen in childhood and precedes the other psychological disorders. The secondary dependence follows after the comorbidity and events of life that alter self-esteem (depression, for example). Various therapeutic strategies arise from various currents. The therapies of analytical inspiration recommend replaying the relationship of object and explicitly evoking the transfer. The behavioural and cognitive psychotherapies aim at making the patient identify the cognitions which underlie the dependence, then leading the patient to modify his/her cognition and to behave in a more autonomous way, using the theory of learning. The humanist therapies aim at a therapeutic relationship of acceptance and

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

Science.gov (United States)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

Advances in the analysis of energy commodities and of multivariate dependence structures

Energy Technology Data Exchange (ETDEWEB)

Schlueter, Stephan

2011-01-27

In the first chapter of the dissertation a new stochastic long-term/short-term model for short-term electricity prices is introduced and applied to four major European indices. Evidence is given that all time series contain certain periodic patterns, and it is shown how to use the wavelet transform for filtering purpose. The wavelet transform is also applied to separate the long-term trend from the short-term oscillation in the seasonal-adjusted log-prices. Moreover, dynamic volatility is found in all time series, which is incorporated by using a bivariate GARCH model with constant correlation. The residuals are modeled using the normal-inverse Gaussian distribution. In the second chapter an overview over different wavelet based time series forecasting methods is given. The methods are tested on four data sets, each with its own characteristics. Eventually, it can be seen that using wavelets does improve the forecasting quality, especially for longer time horizons than one day ahead. However, there is no single superior method; the performance depends on the data set and the forecasting time horizon. In the third chapter a new formula for extreme Student t quantiles is derived. The derivation is based on the proof for the Gaussian quantile and on the fact that the Student t distribution arises as the limit of a variance-mixture of normals. In the fourth chapter a theoretical framework and a solved example for valuing a European gas storage facility is presented. For modeling the gas price a mean reverting process with GARCH volatility is chosen. Based on this process dynamic programming methods are applied to derive partial differential equations for valuing the storage facility. As an example a storage site in Epe, Germany, is chosen. In this context the effects of multiple contract types for renting a storage site are investigated and a sensitivity analysis is performed. In the fifth chapter multivariate copula models are discussed. Using three different four

Ordinary matter, dark matter, and dark energy on normal Zeeman space-times

Science.gov (United States)

Imre Szabó, Zoltán

2017-01-01

Zeeman space-times are new, relativistic, and operator based Hamiltonian models representing multi-particle systems. They are established on Lorentzian pseudo Riemannian manifolds whose Laplacian immediately appears in the form of original quantum physical wave operators. In classical quantum theory they emerge, differently, from the Hamilton formalism and the correspondence principle. Nonetheless, this new model does not just reiterate the well known conceptions but holds the key to solving open problems of quantum theory. Most remarkably, it represents the dark matter, dark energy, and ordinary matter by the same ratios how they show up in experiments. Another remarkable agreement with reality is that the ordinary matter appears to be non-expanding and is described in consent with observations. The theory also explains gravitation, moreover, the Hamilton operators of all energy and matter formations, together with their physical properties, are solely derived from the Laplacian of the Zeeman space-time. By this reason, it is called Monistic Wave Laplacian which symbolizes an all-comprehensive unification of all matter and energy formations. This paper only outlines the normal case where the particles do not have proper spin but just angular momentum. The complete anomalous theory is detailed in [Sz2, Sz3, Sz4, Sz5, Sz6, Sz7].

Bounds of the Spectral Radius and the Nordhaus-Gaddum Type of the Graphs

Directory of Open Access Journals (Sweden)

Tianfei Wang

2013-01-01

Full Text Available The Laplacian spectra are the eigenvalues of Laplacian matrix L(G=D(G-A(G, where D(G and A(G are the diagonal matrix of vertex degrees and the adjacency matrix of a graph G, respectively, and the spectral radius of a graph G is the largest eigenvalue of A(G. The spectra of the graph and corresponding eigenvalues are closely linked to the molecular stability and related chemical properties. In quantum chemistry, spectral radius of a graph is the maximum energy level of molecules. Therefore, good upper bounds for the spectral radius are conducive to evaluate the energy of molecules. In this paper, we first give several sharp upper bounds on the adjacency spectral radius in terms of some invariants of graphs, such as the vertex degree, the average 2-degree, and the number of the triangles. Then, we give some numerical examples which indicate that the results are better than the mentioned upper bounds in some sense. Finally, an upper bound of the Nordhaus-Gaddum type is obtained for the sum of Laplacian spectral radius of a connected graph and its complement. Moreover, some examples are applied to illustrate that our result is valuable.

An equivalent body surface charge model representing three-dimensional bioelectrical activity

Science.gov (United States)

He, B.; Chernyak, Y. B.; Cohen, R. J.

1995-01-01

A new surface-source model has been developed to account for the bioelectrical potential on the body surface. A single-layer surface-charge model on the body surface has been developed to equivalently represent bioelectrical sources inside the body. The boundary conditions on the body surface are discussed in relation to the surface-charge in a half-space conductive medium. The equivalent body surface-charge is shown to be proportional to the normal component of the electric field on the body surface just outside the body. The spatial resolution of the equivalent surface-charge distribution appears intermediate between those of the body surface potential distribution and the body surface Laplacian distribution. An analytic relationship between the equivalent surface-charge and the surface Laplacian of the potential was found for a half-space conductive medium. The effects of finite spatial sampling and noise on the reconstruction of the equivalent surface-charge were evaluated by computer simulations. It was found through computer simulations that the reconstruction of the equivalent body surface-charge from the body surface Laplacian distribution is very stable against noise and finite spatial sampling. The present results suggest that the equivalent body surface-charge model may provide an additional insight to our understanding of bioelectric phenomena.

Least-Squares Linear Regression and Schrodinger's Cat: Perspectives on the Analysis of Regression Residuals.

Science.gov (United States)

Hecht, Jeffrey B.

The analysis of regression residuals and detection of outliers are discussed, with emphasis on determining how deviant an individual data point must be to be considered an outlier and the impact that multiple suspected outlier data points have on the process of outlier determination and treatment. Only bivariate (one dependent and one independent)…

On Geometric Variational Models for Inpainting Surface Holes (PREPRINT)

National Research Council Canada - National Science Library

Caselles, Vicent; Haro, Gloria; Sapiro, Guillermo; Verdera, Joan

2006-01-01

.... These equations include a system for the joint interpolation of scalar and vector fields, a Laplacian-based minimization, a mean curvature diffusion flow, and an absolutely minimizing Lipschitz extension...

A Vehicle for Bivariate Data Analysis

Science.gov (United States)

Roscoe, Matt B.

2016-01-01

Instead of reserving the study of probability and statistics for special fourth-year high school courses, the Common Core State Standards for Mathematics (CCSSM) takes a "statistics for all" approach. The standards recommend that students in grades 6-8 learn to summarize and describe data distributions, understand probability, draw…

Spectral density regression for bivariate extremes

KAUST Repository

Castro Camilo, Daniela; de Carvalho, Miguel

2016-01-01

can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts

Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM).

Science.gov (United States)

Poddar, Sunrita; Jacob, Mathews

2016-04-01

We introduce a novel algorithm to recover real time dynamic MR images from highly under-sampled k- t space measurements. The proposed scheme models the images in the dynamic dataset as points on a smooth, low dimensional manifold in high dimensional space. We propose to exploit the non-linear and non-local redundancies in the dataset by posing its recovery as a manifold smoothness regularized optimization problem. A navigator acquisition scheme is used to determine the structure of the manifold, or equivalently the associated graph Laplacian matrix. The estimated Laplacian matrix is used to recover the dataset from undersampled measurements. The utility of the proposed scheme is demonstrated by comparisons with state of the art methods in multi-slice real-time cardiac and speech imaging applications.

Realization of consensus of multi-agent systems with stochastically mixed interactions

Energy Technology Data Exchange (ETDEWEB)

Sun, Yongzheng, E-mail: yzsung@gmail.com; Li, Wang [School of Science, China University of Mining and Technology, Xuzhou 221008 (China); Zhao, Donghua [School of Mathematical Sciences, Fudan University, Shanghai 200433 (China)

2016-07-15

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of its graph Laplacian. The influence of network topologies on the consensus time is also investigated.

Consensus Analysis of Second-Order Multiagent Systems with General Topology and Time Delay

Directory of Open Access Journals (Sweden)

Bo Liu

2013-01-01

Full Text Available This paper addresses the consensus of second-order multiagent systems with general topology and time delay based on the nearest neighbor rule. By using the Laplace transform technique, it is proved that the second-order multi-agent system in the presence of time-delay can reach consensus if the network topology contains a globally reachable node and time delay is bounded. The bound of time-delay only depends on eigenvalues of the Laplacian matrix of the system. The main contribution of this paper is that the accurate state of the consensus center and the upper bound of the communication delay to make the agents reach consensus are given. Some numerical simulations are given to illustrate the theoretical results.

Spectral Bisection with Two Eigenvectors

Czech Academy of Sciences Publication Activity Database

Rocha, Israel

2017-01-01

Roč. 61, August (2017), s. 1019-1025 ISSN 1571-0653 Institutional support: RVO:67985807 Keywords : graph partitioning * Laplacian matrix * Fiedler vector Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics

Exercise Dependence

Directory of Open Access Journals (Sweden)

Erdal Vardar

2012-06-01

Full Text Available Exercise dependence define a condition in which a person performs excessive exercise resulting in deterioration of his or her physical and mental health wellness. Despite many clinical research studies on exercise dependence, exact diagnostic criteria has not been developed yet. Clinical evidences concerning etiology, epidemiology, underlying mechanisms and treatment of exercise dependence are still not sufficient. Moreover, evaluation of this clinical disorder within dependency perspective is a fairly new concept. Recent studies have shown that exercise dependence has similar features like chemical substance dependence with regards to withdrawal and tolerance symptoms. The aim of this review was to briefly evaluate diagnostic and clinical features of exercise dependence. [Archives Medical Review Journal 2012; 21(3.000: 163-173

Absence of embedded eigenvalues for Riemannian Laplacians

DEFF Research Database (Denmark)

Ito, Kenichi; Skibsted, Erik

Schrödinger operators on non-compact connected Riemannian manifolds. A principal example is given by a manifold with an end (possibly more than one) in which geodesic coordinates are naturally defined. In this case one of our geometric conditions is a positive lower bound of the second fundamenta...

The Schroedinger operator as a generalized Laplacian

International Nuclear Information System (INIS)

Grabowska, Katarzyna; Urbanski, Pawel; Grabowski, Janusz

2008-01-01

The Schroedinger operators on the Newtonian spacetime are defined in a way which make them independent of the class of inertial observers. In this picture the Schroedinger operators act not on functions on the spacetime but on sections of a certain one-dimensional complex vector bundle-the Schroedinger line bundle. This line bundle has trivializations indexed by inertial observers and is associated with an U(1)-principal bundle with an analogous list of trivializations-the Schroedinger principal bundle. If an inertial frame is fixed, the Schroedinger bundle can be identified with the trivial bundle over spacetime, but as there is no canonical trivialization (inertial frame), these sections interpreted as 'wavefunctions' cannot be viewed as actual functions on the spacetime. In this approach, the change of an observer results not only in the change of actual coordinates in the spacetime but also in a change of the phase of wavefunctions. For the Schroedinger principal bundle, a natural differential calculus for 'wave forms' is developed that leads to a natural generalization of the concept of the Laplace-Beltrami operator associated with a pseudo-Riemannian metric. The free Schroedinger operator turns out to be the Laplace-Beltrami operator associated with a naturally distinguished invariant pseudo-Riemannian metric on the Schroedinger principal bundle. The presented framework does not involve any ad hoc or axiomatically introduced geometrical structures. It is based on the traditional understanding of the Schroedinger operator in a given reference frame-which is supported by producing right physics predictions-and it is proven to be strictly related to the frame-independent formulation of analytical Newtonian mechanics and Hamilton-Jacobi equations that makes a bridge between the classical and quantum theory

A Concentration Phenomenon for p-Laplacian Equation

Directory of Open Access Journals (Sweden)

Yansheng Zhong

2014-01-01

Full Text Available It is proved that if the bounded function of coefficient Qn in the following equation  -div ⁡{|∇u|p-2∇u}+V(x|u|p-2u=Qn(x|u|q-2u,  u(x=0  as  x∈∂Ω.  u(x⟶0  as  |x|⟶∞ is positive in a region contained in Ω and negative outside the region, the sets {Qn>0} shrink to a point x0∈Ω as n→∞, and then the sequence un generated by the nontrivial solution of the same equation, corresponding to Qn, will concentrate at x0 with respect to W01,p(Ω and certain Ls(Ω-norms. In addition, if the sets {Qn>0} shrink to finite points, the corresponding ground states {un} only concentrate at one of these points. These conclusions extend the results proved in the work of Ackermann and Szulkin (2013 for case p=2.

Effect of short-term heart rate variability biofeedback on long-term abstinence in alcohol dependent patients - a one-year follow-up.

Science.gov (United States)

Penzlin, Ana Isabel; Barlinn, Kristian; Illigens, Ben Min-Woo; Weidner, Kerstin; Siepmann, Martin; Siepmann, Timo

2017-09-06

A randomized controlled study (RCT) recently showed that short-term heart rate variability (HRV) biofeedback in addition to standard rehabilitation care for alcohol dependence can reduce craving, anxiety and improve cardiovascular autonomic function. In this one-year follow-up study we aimed to explore whether completion of 2-week HRV-Biofeedback training is associated with long-term abstinence. Furthermore, we sought to identify potential predictors of post-treatment abstinence. We conducted a survey on abstinence in patients with alcohol dependence 1 year after completion of an RCT comparing HRV-biofeedback in addition to inpatient rehabilitation treatment alone (controls). Abstinence rates were compared and analysed for association with demographic data as well as psychometric and autonomic cardiac assessment before and after completion of the biofeedback training using bivariate and multivariate regression analyses. Out of 48 patients who participated in the RCT, 27 patients (9 females, ages 42.9 ± 8.6, mean ± SD) completed our one-year follow-up. When including in the analysis only patients who completed follow-up, the rate of abstinence tended to be higher in patients who underwent HRV-biofeedback 1 year earlier compared to those who received rehabilitative treatment alone (66.7% vs 50%, p = ns). This non-significant trend was also observed in the intention-to-treat analysis where patients who did not participate in the follow-up were assumed to have relapsed (46,7% biofeedback vs. 33.3% controls, p = ns). Neither cardiac autonomic function nor psychometric variables were associated with abstinence 1 year after HRV-biofeedback. Our follow-up study provide a first indication of possible increase in long-term abstinence after HRV-biofeedback for alcohol dependence in addition to rehabilitation. The original randomized controlled trial was registered in the German Clinical Trials Register ( DRKS00004618 ). This one-year follow-up survey has not been

Path Dependency

OpenAIRE

Mark Setterfield

2015-01-01

Path dependency is defined, and three different specific concepts of path dependency – cumulative causation, lock in, and hysteresis – are analyzed. The relationships between path dependency and equilibrium, and path dependency and fundamental uncertainty are also discussed. Finally, a typology of dynamical systems is developed to clarify these relationships.

Towards Feature Selection in Actor-Critic Algorithms

National Research Council Canada - National Science Library

Rohanimanesh, Khashayar; Roy, Nicholas; Tedrake, Russ

2007-01-01

.... They demonstrate that two popular representations for value methods -- the barycentric interpolators and the graph Laplacian proto-value functions -- can be used to represent the actor so as to satisfy these conditions...

Spectral segmentation of polygonized images with normalized cuts

Energy Technology Data Exchange (ETDEWEB)

Matsekh, Anna [Los Alamos National Laboratory; Skurikhin, Alexei [Los Alamos National Laboratory; Rosten, Edward [UNIV OF CAMBRIDGE

2009-01-01

We analyze numerical behavior of the eigenvectors corresponding to the lowest eigenvalues of the generalized graph Laplacians arising in the Normalized Cuts formulations of the image segmentation problem on coarse polygonal grids.

Dependent Classes

DEFF Research Database (Denmark)

Gasiunas, Vaidas; Mezini, Mira; Ostermann, Klaus

2007-01-01

of dependent classes and a machine-checked type soundness proof in Isabelle/HOL [29], the first of this kind for a language with virtual classes and path-dependent types. [29] T.Nipkow, L.C. Poulson, and M. Wenzel. Isabelle/HOL -- A Proof Assistant for Higher-Order Logic, volume 2283 of LNCS, Springer, 2002......Virtual classes allow nested classes to be refined in subclasses. In this way nested classes can be seen as dependent abstractions of the objects of the enclosing classes. Expressing dependency via nesting, however, has two limitations: Abstractions that depend on more than one object cannot...... be modeled and a class must know all classes that depend on its objects. This paper presents dependent classes, a generalization of virtual classes that expresses similar semantics by parameterization rather than by nesting. This increases expressivity of class variations as well as the flexibility...

Detecting positive quadrant dependence and positive function dependence

NARCIS (Netherlands)

Janic-Wróblewska, A.; Kallenberg, W.C.M.; Ledwina, T.

2004-01-01

There is a lot of interest in positive dependence going beyond linear correlation. In this paper three new rank tests for testing independence against positive dependence are introduced. The first one is directed on positive quadrant dependence, the second and third one concentrate on positive

Detecting positive quadrant dependence and positive function dependence

NARCIS (Netherlands)

Janic-Wróblewska, A.; Kallenberg, W.C.M.; Ledwina, T.

2003-01-01

There is a lot of interest in positive dependence going beyond linear correlation. In this paper three new rank tests for testing independence against positive dependence are introduced. The first one is directed on positive quadrant dependence, the second and third one concentrate on positive

Origin of the solar system. I

International Nuclear Information System (INIS)

Prentice, A.J.R.

1978-01-01

A theory for the origin of the solar system, which is based on ideas of supersonic turbulent convection and indicates the possibility that the original Laplacian hypothesis may by valid, is presented. (Auth.)

Design of self-supporting surfaces

KAUST Repository

Vouga, Etienne; Hö binger, Mathias; Wallner, Johannes; Pottmann, Helmut

2012-01-01

us to close connections between diverse topics in discrete differential geometry, such as a finite-element discretization of the Airy stress potential, perfect graph Laplacians, and computing admissible loads via curvatures of polyhedral surfaces

EEG signatures of arm isometric exertions in preparation, planning and execution.

Science.gov (United States)

Nasseroleslami, Bahman; Lakany, Heba; Conway, Bernard A

2014-04-15

The electroencephalographic (EEG) activity patterns in humans during motor behaviour provide insight into normal motor control processes and for diagnostic and rehabilitation applications. While the patterns preceding brisk voluntary movements, and especially movement execution, are well described, there are few EEG studies that address the cortical activation patterns seen in isometric exertions and their planning. In this paper, we report on time and time-frequency EEG signatures in experiments in normal subjects (n=8), using multichannel EEG during motor preparation, planning and execution of directional centre-out arm isometric exertions performed at the wrist in the horizontal plane, in response to instruction-delay visual cues. Our observations suggest that isometric force exertions are accompanied by transient and sustained event-related potentials (ERP) and event-related (de-)synchronisations (ERD/ERS), comparable to those of a movement task. Furthermore, the ERPs and ERD/ERS are also observed during preparation and planning of the isometric task. Comparison of ear-lobe-referenced and surface Laplacian ERPs indicates the contribution of superficial sources in supplementary and pre-motor (FC(z)), parietal (CP(z)) and primary motor cortical areas (C₁ and FC₁) to ERPs (primarily negative peaks in frontal and positive peaks in parietal areas), but contribution of deep sources to sustained time-domain potentials (negativity in planning and positivity in execution). Transient and sustained ERD patterns in μ and β frequency bands of ear-lobe-referenced and surface Laplacian EEG indicate the contribution of both superficial and deep sources to ERD/ERS. As no physical displacement happens during the task, we can infer that the underlying mechanisms of motor-related ERPs and ERD/ERS patterns do not only depend on change in limb coordinate or muscle-length-dependent ascending sensory information and are primary generated by motor preparation, direction-dependent

Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes

International Nuclear Information System (INIS)

Pan Zhengqiang; Balakrishnan, Narayanaswamy

2011-01-01

Many highly reliable products usually have complex structure, with their reliability being evaluated by two or more performance characteristics. In certain physical situations, the degradation of these performance characteristics would be always positive and strictly increasing. In such a case, the gamma process is usually considered as a degradation process due to its independent and non-negative increments properties. In this paper, we suppose that a product has two dependent performance characteristics and that their degradation can be modeled by gamma processes. For such a bivariate degradation involving two performance characteristics, we propose to use a bivariate Birnbaum-Saunders distribution and its marginal distributions to approximate the reliability function. Inferential method for the corresponding model parameters is then developed. Finally, for an illustration of the proposed model and method, a numerical example about fatigue cracks is discussed and some computational results are presented.

Calculation of control rods in rectangular reactor, and applications (1960)

International Nuclear Information System (INIS)

Goshen, S.; Pazy, A.

1960-01-01

The aim of this report is to find a method for estimating the anti-reactivity of control rods perpendicular to the axis in a cylindrical pile. The paper is divided into two parts. In the first is given a method of calculating control rods in a rectangular pile, similar to the Nordheim-Scalettar method for cylindrical piles. As an example the formulas are given for the theories of one and two neutron groups, the generalisation for several groups being evident. In the second part we find by a variation method a formula for estimating the Laplacian of a pile, which may be divided into parallelepipeds for which the Laplacian are given. Finally, this formula is used to calculate the anti-reactivity of rods perpendicular to the axis in a cylindrical pile. (author) [fr

Series expansion solutions for the multi-term time and space fractional partial differential equations in two- and three-dimensions

Science.gov (United States)

Ye, H.; Liu, F.; Turner, I.; Anh, V.; Burrage, K.

2013-09-01

Fractional partial differential equations with more than one fractional derivative in time describe some important physical phenomena, such as the telegraph equation, the power law wave equation, or the Szabo wave equation. In this paper, we consider two- and three-dimensional multi-term time and space fractional partial differential equations. The multi-term time-fractional derivative is defined in the Caputo sense, whose order belongs to the interval (1,2],(2,3],(3,4] or (0, m], and the space-fractional derivative is referred to as the fractional Laplacian form. We derive series expansion solutions based on a spectral representation of the Laplacian operator on a bounded region. Some applications are given for the two- and three-dimensional telegraph equation, power law wave equation and Szabo wave equation.

[Affective dependency].

Science.gov (United States)

Scantamburlo, G; Pitchot, W; Ansseau, M

2013-01-01

Affective dependency is characterized by emotional distress (insecure attachment) and dependency to another person with a low self-esteem and reassurance need. The paper proposes a reflection on the definition of emotional dependency and the confusion caused by various denominations. Overprotective and authoritarian parenting, cultural and socio-environmental factors may contribute to the development of dependent personality. Psychological epigenetic factors, such as early socio-emotional trauma could on neuronal circuits in prefronto-limbic regions that are essential for emotional behaviour.We also focus on the interrelations between dependent personality, domestic violence and addictions. The objective for the clinician is to propose a restoration of self-esteem and therapeutic strategies focused on autonomy.

Sparse PDF maps for non-linear multi-resolution image operations

KAUST Repository

Hadwiger, Markus; Sicat, Ronell Barrera; Beyer, Johanna; Krü ger, Jens J.; Mö ller, Torsten

2012-01-01

feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters

Dependency Parsing

CERN Document Server

Kubler, Sandra; Nivre, Joakim

2009-01-01

Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it close

On the fourth moment of Hecke Maass forms and the Random Wave Conjecture

OpenAIRE

Buttcane, Jack; Khan, Rizwanur

2016-01-01

Conditionally on the Generalized Lindel\\"of Hypothesis, we obtain an asymptotic for the fourth moment of Hecke Maass cusp forms of large Laplacian eigenvalue for the full modular group. This lends support to the Random Wave Conjecture.

Numerical study of fractional nonlinear Schrodinger equations

KAUST Repository

Klein, Christian; Sparber, Christof; Markowich, Peter A.

2014-01-01

Using a Fourier spectral method, we provide a detailed numerical investigation of dispersive Schrödinger-type equations involving a fractional Laplacian in an one-dimensional case. By an appropriate choice of the dispersive exponent, both mass

Electrokinetic Control of Viscous Fingering

Science.gov (United States)

Mirzadeh, Mohammad; Bazant, Martin Z.

2017-10-01

We present a theory of the interfacial stability of two immiscible electrolytes under the coupled action of pressure gradients and electric fields in a Hele-Shaw cell or porous medium. Mathematically, our theory describes a phenomenon of "vector Laplacian growth," in which the interface moves in response to the gradient of a vector-valued potential function through a generalized mobility tensor. Physically, we extend the classical Saffman-Taylor problem to electrolytes by incorporating electrokinetic (EK) phenomena. A surprising prediction is that viscous fingering can be controlled by varying the injection ratio of electric current to flow rate. Beyond a critical injection ratio, stability depends only upon the relative direction of flow and current, regardless of the viscosity ratio. Possible applications include porous materials processing, electrically enhanced oil recovery, and EK remediation of contaminated soils.

Finding quasi-optimal network topologies for information transmission in active networks.

Science.gov (United States)

Baptista, Murilo S; de Carvalho, Josué X; Hussein, Mahir S

2008-01-01

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Finding quasi-optimal network topologies for information transmission in active networks.

Directory of Open Access Journals (Sweden)

Murilo S Baptista

Full Text Available This work clarifies the relation between network circuit (topology and behaviour (information transmission and synchronization in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Open systems dependability dependability engineering for ever-changing systems

CERN Document Server

Tokoro, Mario

2015-01-01

The book describes a fundamentally new approach to software dependability, considering a software system as an ever-changing system due to changes in service objectives, users' requirements, standards and regulations, and to advances in technology. Such a system is viewed as an Open System since its functions, structures, and boundaries are constantly changing. Thus, the approach to dependability is called Open Systems Dependability. The DEOS technology realizes Open Systems Dependability. It puts more emphasis on stakeholders' agreement and accountability achievement for business/service cont

Black hole perturbations in vector-tensor theories: the odd-mode analysis

Science.gov (United States)

Kase, Ryotaro; Minamitsuji, Masato; Tsujikawa, Shinji; Zhang, Ying-li

2018-02-01

In generalized Proca theories with vector-field derivative couplings, a bunch of hairy black hole solutions have been derived on a static and spherically symmetric background. In this paper, we formulate the odd-parity black hole perturbations in generalized Proca theories by expanding the corresponding action up to second order and investigate whether or not black holes with vector hair suffer ghost or Laplacian instabilities. We show that the models with cubic couplings G3(X), where X=‑AμAμ/2 with a vector field Aμ, do not provide any additional stability condition as in General Relativity. On the other hand, the exact charged stealth Schwarzschild solution with a nonvanishing longitudinal vector component A1, which originates from the coupling to the Einstein tensor GμνAμ Aν equivalent to the quartic coupling G4(X) containing a linear function of X, is unstable in the vicinity of the event horizon. The same instability problem also persists for hairy black holes arising from general quartic power-law couplings G4(X) ⊃ β4 Xn with the nonvanishing A1, while the other branch with A1=0 can be consistent with conditions for the absence of ghost and Laplacian instabilities. We also discuss the case of other exact and numerical black hole solutions associated with intrinsic vector-field derivative couplings and show that there exists a wide range of parameter spaces in which the solutions suffer neither ghost nor Laplacian instabilities against odd-parity perturbations.

Synchronization in complex networks with switching topology

International Nuclear Information System (INIS)

Wang, Lei; Wang, Qing-guo

2011-01-01

This Letter investigates synchronization issues of complex dynamical networks with switching topology. By constructing a common Lyapunov function, we show that local and global synchronization for a linearly coupled network with switching topology can be evaluated by the time average of second smallest eigenvalues corresponding to the Laplacians of switching topology. This result is quite powerful and can be further used to explore various switching cases for complex dynamical networks. Numerical simulations illustrate the effectiveness of the obtained results in the end. -- Highlights: → Synchronization of complex networks with switching topology is investigated. → A common Lyapunov function is established for synchronization of switching network. → The common Lyapunov function is not necessary to monotonically decrease with time. → Synchronization is determined by the second smallest eigenvalue of its Laplacian. → Synchronization criterion can be used to investigate various switching cases.

Minimal Webs in Riemannian Manifolds

DEFF Research Database (Denmark)

Markvorsen, Steen

2008-01-01

For a given combinatorial graph $G$ a {\\it geometrization} $(G, g)$ of the graph is obtained by considering each edge of the graph as a $1-$dimensional manifold with an associated metric $g$. In this paper we are concerned with {\\it minimal isometric immersions} of geometrized graphs $(G, g......)$ into Riemannian manifolds $(N^{n}, h)$. Such immersions we call {\\em{minimal webs}}. They admit a natural 'geometric' extension of the intrinsic combinatorial discrete Laplacian. The geometric Laplacian on minimal webs enjoys standard properties such as the maximum principle and the divergence theorems, which...... are of instrumental importance for the applications. We apply these properties to show that minimal webs in ambient Riemannian spaces share several analytic and geometric properties with their smooth (minimal submanifold) counterparts in such spaces. In particular we use appropriate versions of the divergence...

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.

Science.gov (United States)

Nikoloulopoulos, Aristidis K

2017-10-01

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.

Gradient augmented level set method for phase change simulations

Science.gov (United States)

Anumolu, Lakshman; Trujillo, Mario F.

2018-01-01

A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.

[Caffeine dependence].

Science.gov (United States)

Ogawa, Naoshi; Ueki, Hirofumi

2010-08-01

Caffeine is the most widely consumed psychoactive substance in the world and is a legal stimulant that is readily available to children. The potential for dependence on caffeine has been debated. Presently, due to a paucity of clinical evidence on caffeine dependence, no such diagnosis is included in the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition, Text Revision (DSM-IV-TR). Although in recent studies, a subset of the general population was found to demonstrate caffeine dependence. It is valuable for psychiatrists and primary care physicians to recognize caffeine dependence as a clinical syndrome, since some people are distressed by their caffeine use and feel they can not control or stop their problematic use.

Efficient anisotropic quasi-P wavefield extrapolation using an isotropic low-rank approximation

KAUST Repository

Zhang, Zhendong

2017-12-17

The computational cost of quasi-P wave extrapolation depends on the complexity of the medium, and specifically the anisotropy. Our effective-model method splits the anisotropic dispersion relation into an isotropic background and a correction factor to handle this dependency. The correction term depends on the slope (measured using the gradient) of current wavefields and the anisotropy. As a result, the computational cost is independent of the nature of anisotropy, which makes the extrapolation efficient. A dynamic implementation of this approach decomposes the original pseudo-differential operator into a Laplacian, handled using the low-rank approximation of the spectral operator, plus an angular dependent correction factor applied in the space domain to correct for anisotropy. We analyze the role played by the correction factor and propose a new spherical decomposition of the dispersion relation. The proposed method provides accurate wavefields in phase and more balanced amplitudes than a previous spherical decomposition. Also, it is free of SV-wave artifacts. Applications to a simple homogeneous transverse isotropic medium with a vertical symmetry axis (VTI) and a modified Hess VTI model demonstrate the effectiveness of the approach. The Reverse Time Migration (RTM) applied to a modified BP VTI model reveals that the anisotropic migration using the proposed modeling engine performs better than an isotropic migration.

Feature selection and multi-kernel learning for sparse representation on a manifold

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2014-01-01

combination of some basic items in a dictionary. Gao etal. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity

Site response of the Ganges basin inferred from re-evaluated ...

Indian Academy of Sciences (India)

This subsurface slip stressed the shallower regions of the ... where T is a tension factor and L is the Laplacian operator. ..... 'curve-fitting' exercise so that we can analyze the ..... Duda S 1965 Secular seismic energy release in circum-Pacific.

Erratum for "Symmetry of stochastic non-variational differential equations" [Phys. Rep. 686 (2017) 1-62

Science.gov (United States)

Gaeta, G.

2017-11-01

In my recent paper [1], due to a regrettable and rather trivial mistake, a mixed derivatives term is missing in the expression (5.3) for the Ito Laplacian - which is essentially a Taylor expansion. The correct formula is, of course

Chemical dependence - resources

Science.gov (United States)

Substance use - resources, Drug abuse - resources; Resources - chemical dependence ... are a good resource for information on drug dependence: National Council on Alcoholism and Drug Dependence -- ncadd. ...

Frequency dependent changes in NMDAR-dependent synaptic plasticity

Directory of Open Access Journals (Sweden)

Arvind eKumar

2011-09-01

Full Text Available The NMDAR-dependent synaptic plasticity is thought to mediate several forms of learning, and can be induced by spike trains containing a small number of spikes occurring with varying rates and timing, as well as with oscillations. We computed the influence of these variables on the plasticity induced at a single NMDAR containing synapse using a reduced model that was analytically tractable, and these findings were confirmed using detailed, multi-compartment model. In addition to explaining diverse experimental results about the rate and timing dependence of synaptic plasticity, the model made several novel and testable predictions. We found that there was a preferred frequency for inducing long-term potentiation (LTP such that higher frequency stimuli induced lesser LTP, decreasing as 1/f when the number of spikes in the stimulus was kept fixed. Among other things, the preferred frequency for inducing LTP varied as a function of the distance of the synapse from the soma. In fact, same stimulation frequencies could induce LTP or LTD depending on the dendritic location of the synapse. Next, we found that rhythmic stimuli induced greater plasticity then irregular stimuli. Furthermore, brief bursts of spikes significantly expanded the timing dependence of plasticity. Finally, we found that in the ~5-15Hz frequency range both rate- and timing-dependent plasticity mechanisms work synergistically to render the synaptic plasticity most sensitive to spike-timing. These findings provide computational evidence that oscillations can have a profound influence on the plasticity of an NMDAR-dependent synapse, and show a novel role for the dendritic morphology in this process.

Stereology of extremes; bivariate models and computation

Czech Academy of Sciences Publication Activity Database

Beneš, Viktor; Bodlák, M.; Hlubinka, D.

2003-01-01

Roč. 5, č. 3 (2003), s. 289-308 ISSN 1387-5841 R&D Projects: GA AV ČR IAA1075201; GA ČR GA201/03/0946 Institutional research plan: CEZ:AV0Z1075907 Keywords : sample extremes * domain of attraction * normalizing constants Subject RIV: BA - General Mathematics

N=4 Superconformal Bootstrap of the K3 CFT

CERN Multimedia

CERN. Geneva

2015-01-01

We study two-dimensional (4,4) superconformal field theories of central charge c=6, corresponding to nonlinear σ models on K3 surfaces, using the superconformal bootstrap. This is made possible through a surprising relation between the BPS N=4 superconformal blocks with c=6 and bosonic Virasoro conformal blocks with c=28, and an exact result on the moduli dependence of a certain integrated BPS 4-point function. Nontrivial bounds on the non-BPS spectrum in the K3 CFT are obtained as functions of the CFT moduli, that interpolate between the free orbifold points and singular CFT points. We observe directly from the CFT perspective the signature of a continuous spectrum above a gap at the singular moduli, and find numerically an upper bound on this gap that is saturated by the A1 N=4 cigar CFT. We also derive an analytic upper bound on the first nonzero eigenvalue of the scalar Laplacian on K3 in the large volume regime, that depends on the K3 moduli data. As two byproducts, we find an exact equivalence...

Near-field acoustic imaging based on Laplacian sparsity

DEFF Research Database (Denmark)

Fernandez Grande, Efren; Daudet, Laurent

2016-01-01

We present a sound source identification method for near-field acoustic imaging of extended sources. The methodology is based on a wave superposition method (or equivalent source method) that promotes solutions with sparse higher order spatial derivatives. Instead of promoting direct sparsity......, and the validity of the wave extrapolation used for the reconstruction is examined. It is shown that this methodology can overcome conventional limits of spatial sampling, and is therefore valid for wide-band acoustic imaging of extended sources....

Some Optimization Problems for p-Laplacian Type Equations

International Nuclear Information System (INIS)

Del Pezzo, L. M.; Fernandez Bonder, J.

2009-01-01

In this paper we study some optimization problems for nonlinear elastic membranes. More precisely, we consider the problem of optimizing the cost functional over some admissible class of loads f where u is the (unique) solution to the problem -Δ p u+ vertical bar u vertical bar p-2 u=0 in Ω with vertical bar ∇u vertical bar p-2 u ν =f on ∂Ω

Time-dependent spectral analysis of interactions within groups of walking pedestrians and vertical structural motion using wavelets

Science.gov (United States)

Bocian, M.; Brownjohn, J. M. W.; Racic, V.; Hester, D.; Quattrone, A.; Gilbert, L.; Beasley, R.

2018-05-01

A multi-scale and multi-object interaction phenomena can arise when a group of walking pedestrians crosses a structure capable of exhibiting dynamic response. This is because each pedestrian is an autonomous dynamic system capable of displaying intricate behaviour affected by social, psychological, biomechanical and environmental factors, including adaptations to the structural motion. Despite a wealth of mathematical models attempting to describe and simulate coupled crowd-structure system, their applicability can generally be considered uncertain. This can be assigned to a number of assumptions made in their development and the scarcity or unavailability of data suitable for their validation, in particular those associated with pedestrian-pedestrian and pedestrian-structure interaction. To alleviate this problem, data on behaviour of individual pedestrians within groups of six walkers with different spatial arrangements are gathered simultaneously with data on dynamic structural response of a footbridge, from a series of measurements utilising wireless motion monitors. Unlike in previous studies on coordination of pedestrian behaviour, the collected data can serve as a proxy for pedestrian vertical force, which is of critical importance from the point of view of structural stability. A bivariate analysis framework is proposed and applied to these data, encompassing wavelet transform, synchronisation measures based on Shannon entropy and circular statistics. A topological pedestrian map is contrived showing the strength and directionality of between-subjects interactions. It is found that the coordination in pedestrians' vertical force depends on the spatial collocation within a group, but it is generally weak. The relationship between the bridge and pedestrian behaviour is also analysed, revealing stronger propensity for pedestrians to coordinate their force with the structural motion rather than with each other.

Comparing of the Reaction Time in Substance-Dependent and Non-Dependent Individuals

Directory of Open Access Journals (Sweden)

Mohammad Narimani

2012-11-01

Full Text Available Aim: The aim of this study was to compare the simple, selective, and discrimination reaction time in substance-dependent and non-dependent individuals. Method: In this causal-comparative study, the population included of 425 males (opium and crystal dependents who were referred to addiction rehabilitation centers in Tabriz. By random sampling, 16 opium dependents, 16 crystal dependents, and 16 non-dependent individuals with no history of dependency as the compare group were selected. All groups peered in age, and marital status. For gathering data, “Addicts Admit Questionnaire” and laboratory device known as the "Reaction Time Assay" have been used. Results: The results of this study showed that there are significant differences among all groups in simple reaction time, choice reaction time and reaction time to auditory stimuli, but no significant difference in discrimination reaction time and reaction time to visual stimulus observed. Conclusion: The reaction time of substance-dependent groups is slower than non-dependent groups.