An Adaptive Multilevel Factorized Sparse Approximate Inverse Preconditioning
Czech Academy of Sciences Publication Activity Database
Kopal, Jiří; Rozložník, Miroslav; Tůma, Miroslav
2017-01-01
Roč. 113, November (2017), s. 19-24 ISSN 0965-9978 R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : approximate inverse * Gram–Schmidt orthogonalization * incomplete factorization * multilevel methods * preconditioned conjugate gradient method Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 3.000, year: 2016
Approximate inverse preconditioning of iterative methods for nonsymmetric linear systems
Energy Technology Data Exchange (ETDEWEB)
Benzi, M. [Universita di Bologna (Italy); Tuma, M. [Inst. of Computer Sciences, Prague (Czech Republic)
1996-12-31
A method for computing an incomplete factorization of the inverse of a nonsymmetric matrix A is presented. The resulting factorized sparse approximate inverse is used as a preconditioner in the iterative solution of Ax = b by Krylov subspace methods.
Kaporin, I. E.
2012-02-01
In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.
Approximate Inverse Preconditioners with Adaptive Dropping
Czech Academy of Sciences Publication Activity Database
Kopal, J.; Rozložník, Miroslav; Tůma, Miroslav
2015-01-01
Roč. 84, June (2015), s. 13-20 ISSN 0965-9978 R&D Projects: GA ČR(CZ) GAP108/11/0853; GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : approximate inverse * Gram-Schmidt orthogonalization * incomplete decomposition * preconditioned conjugate gradient method * algebraic preconditioning * pivoting Subject RIV: BA - General Mathematics Impact factor: 1.673, year: 2015
Factorized Approximate Inverses With Adaptive Dropping
Czech Academy of Sciences Publication Activity Database
Kopal, Jiří; Rozložník, Miroslav; Tůma, Miroslav
2016-01-01
Roč. 38, č. 3 (2016), A1807-A1820 ISSN 1064-8275 R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : approximate inverses * incomplete factorization * Gram–Schmidt orthogonalization * preconditioned iterative methods Subject RIV: BA - General Mathematics Impact factor: 2.195, year: 2016
Zhang, Xiao-bo
2017-06-01
The gradient preconditioning approach based on seismic wave energy can effectively avoid the huge storage consumption in the gradient preconditioning algorithms based on Hessian matrices in time-domain full waveform inversion (FWI), but the accuracy is affected by the energy of reflected waves when strong reflectors are present in velocity model. To address this problem, we propose a gradient preconditioning method, which scales the gradient based on the energy of the “approximated transmitted wavefield” simulated by the nonreflecting acoustic wave equation. The method does not require computing or storing the Hessian matrix or its inverse. Furthermore, it can effectively eliminate the effects caused by geometric diffusion and non-uniformity illumination on gradient. The results of model experiments confirm that the time-domain FWI using the gradient preconditioning based on transmitted waves energy can achieve higher inversion precision for high-velocity body and the deep strata below when compared with using the gradient preconditioning based on seismic waves energy.
A Sparse Approximate Inverse Preconditioner for Nonsymmetric Linear Systems
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Tůma, Miroslav
1998-01-01
Roč. 19, č. 3 (1998), s. 968-994 ISSN 1064-8275 R&D Projects: GA ČR GA201/93/0067; GA AV ČR IAA230401 Keywords : large sparse systems * interative methods * preconditioning * approximate inverse * sparse linear systems * sparse matrices * incomplete factorizations * conjugate gradient -type methods Subject RIV: BA - General Mathematics Impact factor: 1.378, year: 1998
Zhang, Xiao-bo; Tan, Jun; Song, Peng; Li, Jin-shan; Xia, Dong-ming; Liu, Zhao-lun
2017-01-01
The gradient preconditioning approach based on seismic wave energy can effectively avoid the huge storage consumption in the gradient preconditioning algorithms based on Hessian matrices in time-domain full waveform inversion (FWI), but the accuracy
Parallelizable approximate solvers for recursions arising in preconditioning
Energy Technology Data Exchange (ETDEWEB)
Shapira, Y. [Israel Inst. of Technology, Haifa (Israel)
1996-12-31
For the recursions used in the Modified Incomplete LU (MILU) preconditioner, namely, the incomplete decomposition, forward elimination and back substitution processes, a parallelizable approximate solver is presented. The present analysis shows that the solutions of the recursions depend only weakly on their initial conditions and may be interpreted to indicate that the inexact solution is close, in some sense, to the exact one. The method is based on a domain decomposition approach, suitable for parallel implementations with message passing architectures. It requires a fixed number of communication steps per preconditioned iteration, independently of the number of subdomains or the size of the problem. The overlapping subdomains are either cubes (suitable for mesh-connected arrays of processors) or constructed by the data-flow rule of the recursions (suitable for line-connected arrays with possibly SIMD or vector processors). Numerical examples show that, in both cases, the overhead in the number of iterations required for convergence of the preconditioned iteration is small relatively to the speed-up gained.
Fast wavelet based sparse approximate inverse preconditioner
Energy Technology Data Exchange (ETDEWEB)
Wan, W.L. [Univ. of California, Los Angeles, CA (United States)
1996-12-31
Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.
Mengxuan, Zhong
2017-06-01
The gradient preconditioning algorithms based on Hessian matrices in time-domain full waveform inversion (FWI) are widely used now, but consume a lot of memory and do not fit the FWI of large models or actual seismic data well. To avoid the huge storage consumption, the gradient preconditioning approach based on seismic wave energy has been proposed it simulates the “approximated wave field” with the acoustic wave equation and uses the energy of the simulated wavefield to precondition the gradient. The method does not require computing and storing the Hessian matrix or its inverse and can effectively eliminate the effect caused by geometric diffusion and uneven illumination on gradient. The result of experiments in this article with field data from South China Sea confirms that the time-domain FWI using the gradient preconditioning based on seismic wave energy (GPWE) can achieve higher inversion accuracy for the deep high-velocity model and its underlying strata.
Robust Approximate Inverse Preconditioning for the Conjugate Gradient Method
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Cullum, J. K.; Tůma, Miroslav
2000-01-01
Roč. 22, č. 4 (2000), s. 1318-1332 ISSN 1064-8275 R&D Projects: GA AV ČR IAA2030706; GA AV ČR IAA2030801 Institutional research plan: AV0Z1030915 Subject RIV: BA - General Mathematics Impact factor: 1.421, year: 2000
Approximate Schur complement preconditioning of the lowest order nodal discretizations
Energy Technology Data Exchange (ETDEWEB)
Moulton, J.D.; Ascher, U.M. [Univ. of British Columbia, Vancouver, British Columbia (Canada); Morel, J.E. [Los Alamos National Lab., NM (United States)
1996-12-31
Particular classes of nodal methods and mixed hybrid finite element methods lead to equivalent, robust and accurate discretizations of 2nd order elliptic PDEs. However, widespread popularity of these discretizations has been hindered by the awkward linear systems which result. The present work exploits this awkwardness, which provides a natural partitioning of the linear system, by defining two optimal preconditioners based on approximate Schur complements. Central to the optimal performance of these preconditioners is their sparsity structure which is compatible with Dendy`s black box multigrid code.
Preconditioned alternating direction method of multipliers for inverse problems with constraints
International Nuclear Information System (INIS)
Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie
2017-01-01
We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method. (paper)
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Kouhia, R.; Tůma, Miroslav
2001-01-01
Roč. 190, - (2001), s. 6533-6554 ISSN 0045-7825 R&D Projects: GA AV ČR IAA2030801; GA ČR GA201/00/0080 Institutional research plan: AV0Z1030915 Keywords : preconditioning * conjugate gradient * factorized sparse approximate inverse * block algorithms * finite elements * shells Subject RIV: BA - General Mathematics Impact factor: 0.913, year: 2001
Approximation of Bayesian Inverse Problems for PDEs
Cotter, S. L.; Dashti, M.; Stuart, A. M.
2010-01-01
Inverse problems are often ill posed, with solutions that depend sensitively on data.n any numerical approach to the solution of such problems, regularization of some form is needed to counteract the resulting instability. This paper is based on an approach to regularization, employing a Bayesian formulation of the problem, which leads to a notion of well posedness for inverse problems, at the level of probability measures. The stability which results from this well posedness may be used as t...
On quasiclassical approximation in the inverse scattering method
International Nuclear Information System (INIS)
Geogdzhaev, V.V.
1985-01-01
Using as an example quasiclassical limits of the Korteweg-de Vries equation and nonlinear Schroedinger equation, the quasiclassical limiting variant of the inverse scattering problem method is presented. In quasiclassical approximation the inverse scattering problem for the Schroedinger equation is reduced to the classical inverse scattering problem
Frame approximation of pseudo-inverse operators
DEFF Research Database (Denmark)
Christensen, Ole
2001-01-01
Let T denote an operator on a Hilbert space (H, [.,.]), and let {f(i)}(i=1)(infinity) be a frame for the orthogonal complement of the kernel NT. We construct a sequence of operators {Phi (n)} of the form Phi (n) (.) = Sigma (n)(i=1) [., g(t)(n)]f(i) which converges to the psuedo-inverse T+ of T i...... in the strong operator topology as n --> infinity. The operators {Phi (n)} can be found using finite-dimensional methods. We also prove an adaptive iterative version of the result. (C) 2001 Academic Press....
Approximation of the inverse G-frame operator
Indian Academy of Sciences (India)
... projection method for -frames which works for all conditional -Riesz frames. We also derive a method for approximation of the inverse -frame operator which is efficient for all -frames. We show how the inverse of -frame operator can be approximated as close as we like using finite-dimensional linear algebra.
Mitigating nonlinearity in full waveform inversion using scaled-Sobolev pre-conditioning
Zuberi, M. AH; Pratt, R. G.
2018-04-01
The Born approximation successfully linearizes seismic full waveform inversion if the background velocity is sufficiently accurate. When the background velocity is not known it can be estimated by using model scale separation methods. A frequently used technique is to separate the spatial scales of the model according to the scattering angles present in the data, by using either first- or second-order terms in the Born series. For example, the well-known `banana-donut' and the `rabbit ear' shaped kernels are, respectively, the first- and second-order Born terms in which at least one of the scattering events is associated with a large angle. Whichever term of the Born series is used, all such methods suffer from errors in the starting velocity model because all terms in the Born series assume that the background Green's function is known. An alternative approach to Born-based scale separation is to work in the model domain, for example, by Gaussian smoothing of the update vectors, or some other approach for separation by model wavenumbers. However such model domain methods are usually based on a strict separation in which only the low-wavenumber updates are retained. This implies that the scattered information in the data is not taken into account. This can lead to the inversion being trapped in a false (local) minimum when sharp features are updated incorrectly. In this study we propose a scaled-Sobolev pre-conditioning (SSP) of the updates to achieve a constrained scale separation in the model domain. The SSP is obtained by introducing a scaled Sobolev inner product (SSIP) into the measure of the gradient of the objective function with respect to the model parameters. This modified measure seeks reductions in the L2 norm of the spatial derivatives of the gradient without changing the objective function. The SSP does not rely on the Born prediction of scale based on scattering angles, and requires negligible extra computational cost per iteration. Synthetic
Approximate 2D inversion of airborne TEM data
DEFF Research Database (Denmark)
Christensen, N.B.; Wolfgram, Peter
2006-01-01
We propose an approximate two-dimensional inversion procedure for transient electromagnetic data. The method is a two-stage procedure, where data are first inverted with 1D multi-layer models. The 1D model section is then considered as data for the next inversion stage that produces the 2D model...... section. For moving platform data there is translational invariance and the second part of the inversion becomes a deconvolution. The convolution kernels are computed by perturbing one model element in an otherwise homogeneous 2D section and calculating full nonlinear responses. These responses...... are then inverted with 1D models to produce a 1D model section. This section is the convolution kernel for the deconvolution. Within its limitations, the approximate 2D inversion performs well. Theoretical modeling shows that it delivers model sections that are a definite improvement over 1D model sections...
A systematic approach to robust preconditioning for gradient-based inverse scattering algorithms
International Nuclear Information System (INIS)
Nordebo, Sven; Fhager, Andreas; Persson, Mikael; Gustafsson, Mats
2008-01-01
This paper presents a systematic approach to robust preconditioning for gradient-based nonlinear inverse scattering algorithms. In particular, one- and two-dimensional inverse problems are considered where the permittivity and conductivity profiles are unknown and the input data consist of the scattered field over a certain bandwidth. A time-domain least-squares formulation is employed and the inversion algorithm is based on a conjugate gradient or quasi-Newton algorithm together with an FDTD-electromagnetic solver. A Fisher information analysis is used to estimate the Hessian of the error functional. A robust preconditioner is then obtained by incorporating a parameter scaling such that the scaled Fisher information has a unit diagonal. By improving the conditioning of the Hessian, the convergence rate of the conjugate gradient or quasi-Newton methods are improved. The preconditioner is robust in the sense that the scaling, i.e. the diagonal Fisher information, is virtually invariant to the numerical resolution and the discretization model that is employed. Numerical examples of image reconstruction are included to illustrate the efficiency of the proposed technique
Mengxuan, Zhong; Jun, Tan; Peng, Song; Xiao-bo, Zhang; Chuang, Xie; Zhao-lun, Liu
2017-01-01
The gradient preconditioning algorithms based on Hessian matrices in time-domain full waveform inversion (FWI) are widely used now, but consume a lot of memory and do not fit the FWI of large models or actual seismic data well. To avoid the huge
On rational approximation methods for inverse source problems
Rundell, William
2011-02-01
The basis of most imaging methods is to detect hidden obstacles or inclusions within a body when one can only make measurements on an exterior surface. Such is the ubiquity of these problems, the underlying model can lead to a partial differential equation of any of the major types, but here we focus on the case of steady-state electrostatic or thermal imaging and consider boundary value problems for Laplace\\'s equation. Our inclusions are interior forces with compact support and our data consists of a single measurement of (say) voltage/current or temperature/heat flux on the external boundary. We propose an algorithm that under certain assumptions allows for the determination of the support set of these forces by solving a simpler "equivalent point source" problem, and which uses a Newton scheme to improve the corresponding initial approximation. © 2011 American Institute of Mathematical Sciences.
On rational approximation methods for inverse source problems
Rundell, William; Hanke, Martin
2011-01-01
The basis of most imaging methods is to detect hidden obstacles or inclusions within a body when one can only make measurements on an exterior surface. Such is the ubiquity of these problems, the underlying model can lead to a partial differential equation of any of the major types, but here we focus on the case of steady-state electrostatic or thermal imaging and consider boundary value problems for Laplace's equation. Our inclusions are interior forces with compact support and our data consists of a single measurement of (say) voltage/current or temperature/heat flux on the external boundary. We propose an algorithm that under certain assumptions allows for the determination of the support set of these forces by solving a simpler "equivalent point source" problem, and which uses a Newton scheme to improve the corresponding initial approximation. © 2011 American Institute of Mathematical Sciences.
Zhang, Zhendong; Schuster, Gerard T.; Liu, Yike; Hanafy, Sherif M.; Li, Jing
2016-01-01
We present a surface-wave inversion method that inverts for the S-wave velocity from the Rayleigh wave dispersion curve using a difference approximation to the gradient of the misfit function. We call this wave equation inversion of skeletonized
Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference
Walden, Maria A.; Bikdash, Marwan; Homaifar, Abdollah
1998-01-01
Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.
Energy Technology Data Exchange (ETDEWEB)
Chen, Ke [Univ. of Liverpool (United Kingdom)
1996-12-31
We study various preconditioning techniques for the iterative solution of boundary integral equations, and aim to provide a theory for a class of sparse preconditioners. Two related ideas are explored here: singularity separation and inverse approximation. Our preliminary conclusion is that singularity separation based preconditioners perform better than approximate inverse based while it is desirable to have both features.
Zhang, Zhendong
2016-07-26
We present a surface-wave inversion method that inverts for the S-wave velocity from the Rayleigh wave dispersion curve using a difference approximation to the gradient of the misfit function. We call this wave equation inversion of skeletonized surface waves because the skeletonized dispersion curve for the fundamental-mode Rayleigh wave is inverted using finite-difference solutions to the multi-dimensional elastic wave equation. The best match between the predicted and observed dispersion curves provides the optimal S-wave velocity model. Our method can invert for lateral velocity variations and also can mitigate the local minimum problem in full waveform inversion with a reasonable computation cost for simple models. Results with synthetic and field data illustrate the benefits and limitations of this method. © 2016 Elsevier B.V.
Khaniani, Hassan
This thesis proposes a "standard strategy" for iterative inversion of elastic properties from the seismic reflection data. The term "standard" refers to the current hands-on commercial techniques that are used for the seismic imaging and inverse problem. The method is established to reduce the computation time associated with elastic Full Waveform Inversion (FWI) methods. It makes use of AVO analysis, prestack time migration and corresponding forward modeling in an iterative scheme. The main objective is to describe the iterative inversion procedure used in seismic reflection data using simplified mathematical expression and their numerical applications. The frame work of the inversion is similar to (FWI) method but with less computational costs. The reduction of computational costs depends on the data conditioning (with or without multiple data), the level of the complexity of geological model and acquisition condition such as Signal to Noise Ratio (SNR). Many processing methods consider multiple events as noise and remove it from the data. This is the motivation for reducing the computational cost associated with Finite Difference Time Domain (FDTD) forward modeling and Reverse Time Migration (RTM)-based techniques. Therefore, a one-way solution of the wave equation for inversion is implemented. While less computationally intensive depth imaging methods are available by iterative coupling of ray theory and the Born approximation, it is shown that we can further reduce the cost of inversion by dropping the cost of ray tracing for traveltime estimation in a way similar to standard Prestack Time Migration (PSTM) and the corresponding forward modeling. This requires the model to have smooth lateral variations in elastic properties, so that the traveltime of the scatterpoints can be approximated by a Double Square Root (DSR) equation. To represent a more realistic and stable solution of the inverse problem, while considering the phase of supercritical angles, the
Preconditioned Iterative Methods for Solving Weighted Linear Least Squares Problems
Czech Academy of Sciences Publication Activity Database
Bru, R.; Marín, J.; Mas, J.; Tůma, Miroslav
2014-01-01
Roč. 36, č. 4 (2014), A2002-A2022 ISSN 1064-8275 Institutional support: RVO:67985807 Keywords : preconditioned iterative methods * incomplete decompositions * approximate inverses * linear least squares Subject RIV: BA - General Mathematics Impact factor: 1.854, year: 2014
Directory of Open Access Journals (Sweden)
Xin-Jia Meng
2015-01-01
Full Text Available Multidisciplinary reliability is an important part of the reliability-based multidisciplinary design optimization (RBMDO. However, it usually has a considerable amount of calculation. The purpose of this paper is to improve the computational efficiency of multidisciplinary inverse reliability analysis. A multidisciplinary inverse reliability analysis method based on collaborative optimization with combination of linear approximations (CLA-CO is proposed in this paper. In the proposed method, the multidisciplinary reliability assessment problem is first transformed into a problem of most probable failure point (MPP search of inverse reliability, and then the process of searching for MPP of multidisciplinary inverse reliability is performed based on the framework of CLA-CO. This method improves the MPP searching process through two elements. One is treating the discipline analyses as the equality constraints in the subsystem optimization, and the other is using linear approximations corresponding to subsystem responses as the replacement of the consistency equality constraint in system optimization. With these two elements, the proposed method realizes the parallel analysis of each discipline, and it also has a higher computational efficiency. Additionally, there are no difficulties in applying the proposed method to problems with nonnormal distribution variables. One mathematical test problem and an electronic packaging problem are used to demonstrate the effectiveness of the proposed method.
Inverse scattering problem for a magnetic field in the Glauber approximation
International Nuclear Information System (INIS)
Bogdanov, I.V.
1985-01-01
New results in the general theory of scattering are obtained. An inverse problem at fixed energy for an axisymmetric magnetic field is formulated and solved within the frames of the quantum-mechanical Glauber approximation. The solution is found in quadratures in the form of an explicit inversion algorithm reproducing a vector potential by the angular dependence of the scattering amplitude. Extreme transitions from the eikonal inversion method to the classical and Born ones are investigated. Integral and differential equations are derived for the eikonal amplitude that ensure the real value of the vector potential and its energy independence. Magnetoelectric analogies the existence of equivalent axisymmetric electric and magnetic fields scattering charged particles in the same manner both in the Glauber and Born approximation are established. The mentioned analogies permit to simulate ion-potential scattering by potential one that is of interest from the practical viewpoint. Three-dimensional (excentral) eikonal inverse problems for the electric and magnetic fields are discussed. The results of the paper can be used in electron optics
Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I
2017-01-01
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.
Energy spectrum inverse problem of q -deformed harmonic oscillator and WBK approximation
International Nuclear Information System (INIS)
Sang, Nguyen Anh; Thuy, Do Thi Thu; Loan, Nguyen Thi Ha; Lan, Nguyen Tri; Viet, Nguyen Ai
2016-01-01
Using the connection between q-deformed harmonic oscillator and Morse-like anharmonic potential we investigate the energy spectrum inverse problem. Consider some energy levels of energy spectrum of q -deformed harmonic oscillator are known, we construct the corresponding Morse-like potential then find out the deform parameter q . The application possibility of using the WKB approximation in the energy spectrum inverse problem was discussed for the cases of parabolic potential (harmonic oscillator), Morse-like potential ( q -deformed harmonic oscillator). so we consider our deformed-three-levels simple model, where the set-parameters of Morse potential and the corresponding set-parameters of level deformations are easily and explicitly defined. For practical problems, we propose the deformed- three-levels simple model, where the set-parameters of Morse potential and the corresponding set-parameters of level deformations are easily and explicitly defined. (paper)
The approximate inverse in action: IV. Semi-discrete equations in a Banach space setting
International Nuclear Information System (INIS)
Schuster, T; Schöpfer, F; Rieder, A
2012-01-01
This article concerns the method of approximate inverse to solve semi-discrete, linear operator equations in Banach spaces. Semi-discrete means that we search for a solution in an infinite-dimensional Banach space having only a finite number of data available. In this sense the situation is applicable to a large variety of applications where a measurement process delivers a discretization of an infinite-dimensional data space. The method of approximate inverse computes scalar products of the data with pre-computed reconstruction kernels which are associated with mollifiers and the dual of the model operator. The convergence, approximation power and regularization property of this method when applied to semi-discrete operator equations in Hilbert spaces has been investigated in three prequels to this paper. Here we extend these results to a Banach space setting. We prove convergence and stability for general Banach spaces and reproduce the results specifically for the integration operator acting on the space of continuous functions. (paper)
Approximate inverse for the common offset acquisition geometry in 2D seismic imaging
Grathwohl, Christine; Kunstmann, Peer; Quinto, Eric Todd; Rieder, Andreas
2018-01-01
We explore how the concept of approximate inverse can be used and implemented to recover singularities in the sound speed from common offset measurements in two space dimensions. Numerical experiments demonstrate the performance of the method. We gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG) through CRC 1173. Quinto additionally thanks the Otto Mønsteds Fond and U.S. National Science Foundation (under grants DMS 1311558 and DMS 1712207) for their support. He thanks colleagues at DTU and KIT for their warm hospitality while this research was being done.
A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion
Energy Technology Data Exchange (ETDEWEB)
Li, Jinglai, E-mail: jinglaili@sjtu.edu.cn [Institute of Natural Sciences, Department of Mathematics, and MOE Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240 (China); Lin, Guang, E-mail: lin491@purdue.edu [Department of Mathematics, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States); Computational Sciences and Mathematics Division, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Yang, Xu, E-mail: xuyang@math.ucsb.edu [Department of Mathematics, University of California, Santa Barbara, CA 93106 (United States)
2015-09-01
In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.
A Hybrid Parallel Preconditioning Algorithm For CFD
Barth,Timothy J.; Tang, Wei-Pai; Kwak, Dochan (Technical Monitor)
1995-01-01
A new hybrid preconditioning algorithm will be presented which combines the favorable attributes of incomplete lower-upper (ILU) factorization with the favorable attributes of the approximate inverse method recently advocated by numerous researchers. The quality of the preconditioner is adjustable and can be increased at the cost of additional computation while at the same time the storage required is roughly constant and approximately equal to the storage required for the original matrix. In addition, the preconditioning algorithm suggests an efficient and natural parallel implementation with reduced communication. Sample calculations will be presented for the numerical solution of multi-dimensional advection-diffusion equations. The matrix solver has also been embedded into a Newton algorithm for solving the nonlinear Euler and Navier-Stokes equations governing compressible flow. The full paper will show numerous examples in CFD to demonstrate the efficiency and robustness of the method.
Approximation in generalized Hardy classes and resolution of inverse problems for tokamaks
International Nuclear Information System (INIS)
Fisher, Y.
2011-11-01
This thesis concerns both the theoretical and constructive resolution of inverse problems for isotropic diffusion equation in planar domains, simply and doubly connected. From partial Cauchy boundary data (potential, flux), we look for those quantities on the remaining part of the boundary, where no information is available, as well as inside the domain. The proposed approach proceeds by considering solutions to the diffusion equation as real parts of complex valued solutions to some conjugated Beltrami equation. These particular generalized analytic functions allow to introduce Hardy classes, where the inverse problem is stated as a best constrained approximation issue (bounded extrema problem), and thereby is regularized. Hence, existence and smoothness properties, together with density results of traces on the boundary, ensure well-posedness. An application is studied, to a free boundary problem for a magnetically confined plasma in the tokamak Tore Supra (CEA Cadarache France). The resolution of the approximation problem on a suitable basis of functions (toroidal harmonics) leads to a qualification criterion for the estimated plasma boundary. A descent algorithm makes it decrease, and refines the estimations. The method does not require any integration of the solution in the overall domain. It furnishes very accurate numerical results, and could be extended to other devices, like JET or ITER. (author)
Inverse bremsstrahlung heating beyond the first Born approximation for dense plasmas in laser fields
International Nuclear Information System (INIS)
Moll, M; Schlanges, M; Bornath, Th; Krainov, V P
2012-01-01
Inverse bremsstrahlung (IB) heating, an important process in the laser-matter interaction, involves two different kinds of interaction—the interaction of the electrons with the external laser field and the electron-ion interaction. This makes analytical approaches very difficult. In a quantum perturbative approach to the IB heating rate in strong laser fields, usually the first Born approximation with respect to the electron-ion potential is considered, whereas the influence of the electric field is taken exactly in the Volkov wave functions. In this paper, a perturbative treatment is presented adopting a screened electron-ion interaction potential. As a new result, we derive the momentum-dependent, angle-averaged heating rate in the first Born approximation. Numerical results are discussed for a broad range of field strengths, and the conditions for the applicability of a linear approximation for the heating rate are analyzed in detail. Going a step further in the perturbation series, we consider the transition amplitude in the second Born approximation, which enables us to calculate the heating rate up to the third order of the interaction strength. (paper)
International Nuclear Information System (INIS)
Otero, F A; Frontini, G L; Elicabe, G E
2011-01-01
An analytic model for the scattering of a spherical particle with spherical inclusions has been proposed under the RG approximation. The model can be used without limitations to describe an X-ray scattering experiment. However, for light scattering several conditions must be fulfilled. Based on this model an inverse methodology is proposed to estimate the radii of host particle and inclusions, the number of inclusions and the Distance Distribution Functions (DDF's) of the distances between inclusions and the distances between inclusions and the origin of coordinates. The methodology is numerically tested in a light scattering example in which the host particle is eliminated by matching the refractive indices of host particle and medium. The results obtained for this cluster particle are very satisfactory.
Zhang, Li-qiang; Ma, Ting-ting; Yu, Chang-shui
2018-03-01
The computability of the quantifier of a given quantum resource is the essential challenge in the resource theory and the inevitable bottleneck for its application. Here we focus on the measurement-induced nonlocality and present a redefinition in terms of the skew information subject to a broken observable. It is shown that the obtained quantity possesses an obvious operational meaning, can tackle the noncontractivity of the measurement-induced nonlocality and has analytic expressions for pure states, (2 ⊗d )-dimensional quantum states, and some particular high-dimensional quantum states. Most importantly, an inverse approximate joint diagonalization algorithm, due to its simplicity, high efficiency, stability, and state independence, is presented to provide almost-analytic expressions for any quantum state, which can also shed light on other aspects in physics. To illustrate applications as well as demonstrate the validity of the algorithm, we compare the analytic and numerical expressions of various examples and show their perfect consistency.
Inverse periodic problem for the discrete approximation of the Schroedinger nonlinear equation
International Nuclear Information System (INIS)
Bogolyubov, N.N.; Prikarpatskij, A.K.; AN Ukrainskoj SSR, Lvov. Inst. Prikladnykh Problem Mekhaniki i Matematiki)
1982-01-01
The problem of numerical solution of the Schroedinger nonlinear equation (1) iPSIsub(t) = PSIsub(xx)+-2(PSI)sup(2)PSI. The numerical solution of nonlinear differential equation supposes its discrete approximation is required for the realization of the computer calculation process. Tor the equation (1) there exists the following discrete approximation by variable x(2) iPSIsub(n, t) = (PSIsub(n+1)-2PSIsub(n)+PSIsub(n-1))/(Δx)sup(2)+-(PSIsub(n))sup(2)(PSIsub(n+1)+PSIsub(n-1)), n=0, +-1, +-2... where PSIsub(n)(+) is the corresponding value of PSI(x, t) function in the node and divisions with the equilibrium step Δx. The main problem is obtaining analytically exact solutions of the equations (2). The analysis of the equation system (2) is performed on the base of the discrete analogue of the periodic variant of the inverse scattering problem method developed with the aid of nonlinear equations of the Korteweg-de Vries type. Obtained in explicit form are analytical solutions of the equations system (2). The solutions are expressed through the Riemann THETA-function [ru
Solution accelerators for large scale 3D electromagnetic inverse problems
International Nuclear Information System (INIS)
Newman, Gregory A.; Boggs, Paul T.
2004-01-01
We provide a framework for preconditioning nonlinear 3D electromagnetic inverse scattering problems using nonlinear conjugate gradient (NLCG) and limited memory (LM) quasi-Newton methods. Key to our approach is the use of an approximate adjoint method that allows for an economical approximation of the Hessian that is updated at each inversion iteration. Using this approximate Hessian as a preconditoner, we show that the preconditioned NLCG iteration converges significantly faster than the non-preconditioned iteration, as well as converging to a data misfit level below that observed for the non-preconditioned method. Similar conclusions are also observed for the LM iteration; preconditioned with the approximate Hessian, the LM iteration converges faster than the non-preconditioned version. At this time, however, we see little difference between the convergence performance of the preconditioned LM scheme and the preconditioned NLCG scheme. A possible reason for this outcome is the behavior of the line search within the LM iteration. It was anticipated that, near convergence, a step size of one would be approached, but what was observed, instead, were step lengths that were nowhere near one. We provide some insights into the reasons for this behavior and suggest further research that may improve the performance of the LM methods
Behroozmand, Ahmad A.; Auken, Esben; Fiandaca, Gianluca; Christiansen, Anders Vest; Christensen, Niels B.
2012-08-01
We present a new, efficient and accurate forward modelling and inversion scheme for magnetic resonance sounding (MRS) data. MRS, also called surface-nuclear magnetic resonance (surface-NMR), is the only non-invasive geophysical technique that directly detects free water in the subsurface. Based on the physical principle of NMR, protons of the water molecules in the subsurface are excited at a specific frequency, and the superposition of signals from all protons within the excited earth volume is measured to estimate the subsurface water content and other hydrological parameters. In this paper, a new inversion scheme is presented in which the entire data set is used, and multi-exponential behaviour of the NMR signal is approximated by the simple stretched-exponential approach. Compared to the mono-exponential interpretation of the decaying NMR signal, we introduce a single extra parameter, the stretching exponent, which helps describe the porosity in terms of a single relaxation time parameter, and helps to determine correct initial amplitude and relaxation time of the signal. Moreover, compared to a multi-exponential interpretation of the MRS data, the decay behaviour is approximated with considerably fewer parameters. The forward response is calculated in an efficient numerical manner in terms of magnetic field calculation, discretization and integration schemes, which allows fast computation while maintaining accuracy. A piecewise linear transmitter loop is considered for electromagnetic modelling of conductivities in the layered half-space providing electromagnetic modelling of arbitrary loop shapes. The decaying signal is integrated over time windows, called gates, which increases the signal-to-noise ratio, particularly at late times, and the data vector is described with a minimum number of samples, that is, gates. The accuracy of the forward response is investigated by comparing a MRS forward response with responses from three other approaches outlining
Franssens, G; De Maziére, M; Fonteyn, D
2000-08-20
A new derivation is presented for the analytical inversion of aerosol spectral extinction data to size distributions. It is based on the complex analytic extension of the anomalous diffraction approximation (ADA). We derive inverse formulas that are applicable to homogeneous nonabsorbing and absorbing spherical particles. Our method simplifies, generalizes, and unifies a number of results obtained previously in the literature. In particular, we clarify the connection between the ADA transform and the Fourier and Laplace transforms. Also, the effect of the particle refractive-index dispersion on the inversion is examined. It is shown that, when Lorentz's model is used for this dispersion, the continuous ADA inverse transform is mathematically well posed, whereas with a constant refractive index it is ill posed. Further, a condition is given, in terms of Lorentz parameters, for which the continuous inverse operator does not amplify the error.
Chen, Liwen; Xu, Qiang
2018-02-01
This paper proposes new iterative algorithms for the unknown input and state recovery from the system outputs using an approximate inverse of the strictly proper linear time-invariant (LTI) multivariable system. One of the unique advantages from previous system inverse algorithms is that the output differentiation is not required. The approximate system inverse is stable due to the systematic optimal design of a dummy feedthrough D matrix in the state-space model via the feedback stabilization. The optimal design procedure avoids trial and error to identify such a D matrix which saves tremendous amount of efforts. From the derived and proved convergence criteria, such an optimal D matrix also guarantees the convergence of algorithms. Illustrative examples show significant improvement of the reference input signal tracking by the algorithms and optimal D design over non-iterative counterparts on controllable or stabilizable LTI systems, respectively. Case studies of two Boeing-767 aircraft aerodynamic models further demonstrate the capability of the proposed methods.
DEFF Research Database (Denmark)
Christensen, Ole; Lindner, Alexander M
2001-01-01
We give lower frame bounds for finite subfamilies of a frame of exponentials {e(i lambdak(.))}k is an element ofZ in L-2(-pi,pi). We also present a method for approximation of the inverse frame operator corresponding to {e(i lambdak(.))}k is an element ofZ, where knowledge of the frame bounds for...
Seismic Imaging and Velocity Analysis Using a Pseudo Inverse to the Extended Born Approximation
Alali, Abdullah A.
2018-05-01
Prestack depth migration requires an accurate kinematic velocity model to image the subsurface correctly. Wave equation migration velocity analysis techniques aim to update the background velocity model by minimizing image residuals to achieve the correct model. The most commonly used technique is differential semblance optimization (DSO), which depends on applying an image extension and penalizing the energy in the non-physical extension. However, studies show that the conventional DSO gradient is contaminated with artifact noise and unwanted oscillations which might lead to local minima. To deal with this issue and improve the stability of DSO, recent studies proposed to use an inversion formula rather than migration to obtain the image. Migration is defined as the adjoint of Born modeling. Since the inversion is complicated and expensive, a pseudo inverse is used instead. A pseudo inverse formula has been developed recently for the horizontal space shift extended Born. This formula preserves the true amplitude and reduces the artifact noise even when an incorrect velocity is used. Although the theory for such an inverse is well developed, it has only been derived and tested on laterally homogeneous models. This is because the formula contains a derivative of the image with respect to a vertical extension evaluated at zero offset. Implementing the vertical extension is computationally expensive, which means this derivative needs to be computed without applying the additional extension. For laterally invariant models, the inverse is simplified and this derivative is eliminated. I implement the full asymptotic inverse to the extended Born to account for laterally heterogeneity. I compute the derivative of the image with respect to a vertical extension without performing any additional shift. This is accomplished by applying the derivative to the imaging condition and utilizing the chain rule. The fact that this derivative is evaluated at zero offset vertical
International Nuclear Information System (INIS)
Hamman, E.; Zorgati, R.
1995-01-01
Eddy current non-destructive testing is used by EDF to detect flaws affecting conductive objects such as steam generator tubes. With a view to obtaining ever more accurate information on equipment integrity, thereby facilitating diagnosis, studies aimed at using measurements to reconstruct an image of the flaw have been proceeding now for about ten years. In this context, our approach to eddy current imaging is based on inverse problem formalism. The direct problem, involving a mathematical model linking measurements provided by a probe with variables characterizing the defect, is dealt with elsewhere. Using the model results, we study the possibility of inverting it, i.e. of reconstructing an image of the flaw from the measurements. We first give an overview of the different inversion techniques, representative of the state of the art and all based on linearization of the inverse problem by means of the Born approximation. The model error resulting from an excessive Born approximation nevertheless severely limits the quantity of the images which can be obtained. In order to counteract this often critical error and extend the eddy current imaging application field, we have to del with the non-linear inverse problem. A method derived from recent research is proposed and implemented to ensure consistency with the exact model. Based on an 'optimization' type approach and provided with a convergence theorem, the method is highly efficient. (authors). 17 refs., 7 figs., 1 append
Cui, Tiangang; Marzouk, Youssef; Willcox, Karen
2016-06-01
Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.
2011-04-01
L1u. Assume that geodesic lines, generated by the eikonal equation corresponding to the function c (x) are regular, i.e. any two points in R3 can be...source x0 is located far from Ω, then similarly with (107) ∆l (x, x0) ≈ 0 in Ω. The function l (x, x0) satisfies the eikonal equation [38] |∇xl (x, x0...called “inverse kinematic problem” which aims to recover the function c (x) from the eikonal equation assuming that the function l (x, x0) is known for
International Nuclear Information System (INIS)
Chan, C.K.; Hoffman, D.K.; Evans, J.W.
1985-01-01
Local, i.e., multiplicative, operators satisfy well-known linear factorization relations wherein matrix elements (between states associated with a complete set of wave functions) can be obtained as a linear combination of those out of the ground state (the input data). Analytic derivation of factorization relations for general state input data results in singular integral expressions for the coefficients, which can, however, be regularized using consistency conditions between matrix elements out of a single (nonground) state. Similar results hold for suitable ''symmetry class'' averaged matrix elements where the symmetry class projection operators are ''complete.'' In several cases where the wave functions or projection operators incorporate orthogonal polynomial dependence, we show that the ground state factorization relations have a simplified structure allowing an alternative derivation of the general factorization relations via an infinite matrix inversion procedure. This form is shown to have some advantages over previous versions. In addition, this matrix inversion procedure obtains all consistency conditions (which is not always the case from regularization of singular integrals)
Porr, Bernd; von Ferber, Christian; Wörgötter, Florentin
2003-04-01
In "Isotropic Sequence Order Learning" (pp. 831-864 in this issue), we introduced a novel algorithm for temporal sequence learning (ISO learning). Here, we embed this algorithm into a formal nonevaluating (teacher free) environment, which establishes a sensor-motor feedback. The system is initially guided by a fixed reflex reaction, which has the objective disadvantage that it can react only after a disturbance has occurred. ISO learning eliminates this disadvantage by replacing the reflex-loop reactions with earlier anticipatory actions. In this article, we analytically demonstrate that this process can be understood in terms of control theory, showing that the system learns the inverse controller of its own reflex. Thereby, this system is able to learn a simple form of feedforward motor control.
Brown, Malcolm
2009-01-01
Inversions are fascinating phenomena. They are reversals of the normal or expected order. They occur across a wide variety of contexts. What do inversions have to do with learning spaces? The author suggests that they are a useful metaphor for the process that is unfolding in higher education with respect to education. On the basis of…
International Nuclear Information System (INIS)
Pozdnyakov, Yu.A.; Terenetskij, K.O.
1981-01-01
The approximate method for solution of the inverse scattering problem (ISP) at fixed energy for complex spherically symmetric potentials decreasing faster 1/r is considered. The method is based on using a generalized WKB approximation. For the designed potential V(r) a sufficiently ''close'' reference potential V(r) has been chosen. For both potentials S-matrix elements (ME) have been calculated and inversion procedure has been carried out. S-ME have been calculated for integral-valued and intermediate angular moment values. S-ME are presented in a graphical form for being restored reference, and restored potentials for proton scattering with Esub(p)=49.48 MeV energy on 12 C nuclei. The restoration is the better the ''closer'' the sought-for potential to the reference one. This allows to specify the potential by means of iterations: the restored potential can be used as a reference one, etc. The operation of a restored potential smoothing before the following iteration is introduced. Drawbacks and advantages of the ISP solution method under consideration are pointed out. The method application is strongly limited by the requirement that the energy should be higher than a certain ''critical'' one. The method is applicable in a wider region of particle energies (in the low-energies direction) than the ordinary WKB method. The method is more simple in realization conformably to complex potentials. The investigations carried out of the proposed ISP solution method at fixed energy for complex spherically-symmetric potentials allow to conclude that the method can be successFully applied to specify the central part of interaction of nucleons, α-particles and heavy ions of average and high energies with atomic nuclei [ru
International Nuclear Information System (INIS)
Aboanber, A E; Nahla, A A
2002-01-01
A method based on the Pade approximations is applied to the solution of the point kinetics equations with a time varying reactivity. The technique consists of treating explicitly the roots of the inhour formula. A significant improvement has been observed by treating explicitly the most dominant roots of the inhour equation, which usually would make the Pade approximation inaccurate. Also the analytical inversion method which permits a fast inversion of polynomials of the point kinetics matrix is applied to the Pade approximations. Results are presented for several cases of Pade approximations using various options of the method with different types of reactivity. The formalism is applicable equally well to non-linear problems, where the reactivity depends on the neutron density through temperature feedback. It was evident that the presented method is particularly good for cases in which the reactivity can be represented by a series of steps and performed quite well for more general cases
International Nuclear Information System (INIS)
Ranaivo Nomenjanahary, F.; Rakoto, H.; Ratsimbazafy, J.B.
1994-08-01
This paper is concerned with resistivity sounding measurements performed from single site (vertical sounding) or from several sites (profiles) within a bounded area. The objective is to present an accurate information about the study area and to estimate the likelihood of the produced quantitative models. The achievement of this objective obviously requires quite relevant data and processing methods. It also requires interpretation methods which should take into account the probable effect of an heterogeneous structure. In front of such difficulties, the interpretation of resistivity sounding data inevitably involves the use of inversion methods. We suggest starting the interpretation in simple situation (1-D approximation), and using the rough but correct model obtained as an a-priori model for any more refined interpretation. Related to this point of view, special attention should be paid for the inverse problem applied to the resistivity sounding data. This inverse problem is nonlinear, while linearity inherent in the functional response used to describe the physical experiment. Two different approaches are used to build an approximate but higher dimensional inversion of geoelectrical data: the linear approach and the bayesian statistical approach. Some illustrations of their application in resistivity sounding data acquired at Tritrivakely volcanic lake (single site) and at Mahitsy area (several sites) will be given. (author). 28 refs, 7 figs
Kronecker Products on Preconditioning
Gao, Longfei
2013-01-01
techniques have become increasingly popular due to their great potential on large scale computation. In this work, we present preconditioning techniques for linear systems built with tensor product basis functions. Efficient algorithms are designed
Directory of Open Access Journals (Sweden)
Hozejowski Leszek
2012-04-01
Full Text Available The paper is devoted to a computational problem of predicting a local heat transfer coefficient from experimental temperature data. The experimental part refers to boiling flow of a refrigerant in a minichannel. Heat is dissipated from heating alloy to the flowing liquid due to forced convection. The mathematical model of the problem consists of the governing Poisson equation and the proper boundary conditions. For accurate results it is required to smooth the measurements which was obtained by using Trefftz functions. The measurements were approximated with a linear combination of Trefftz functions. Due to the computational procedure in which the measurement errors are known, it was possible to smooth the data and also to reduce the residuals of approximation on the boundaries.
Fully 3D PET image reconstruction using a fourier preconditioned conjugate-gradient algorithm
International Nuclear Information System (INIS)
Fessler, J.A.; Ficaro, E.P.
1996-01-01
Since the data sizes in fully 3D PET imaging are very large, iterative image reconstruction algorithms must converge in very few iterations to be useful. One can improve the convergence rate of the conjugate-gradient (CG) algorithm by incorporating preconditioning operators that approximate the inverse of the Hessian of the objective function. If the 3D cylindrical PET geometry were not truncated at the ends, then the Hessian of the penalized least-squares objective function would be approximately shift-invariant, i.e. G'G would be nearly block-circulant, where G is the system matrix. We propose a Fourier preconditioner based on this shift-invariant approximation to the Hessian. Results show that this preconditioner significantly accelerates the convergence of the CG algorithm with only a small increase in computation
Fymat, A. L.; Smith, C. B.
1979-01-01
It is shown that the inverse analytical solutions, provided separately by Fymat and Box-McKellar, for reconstructing particle size distributions from remote spectral transmission measurements under the anomalous diffraction approximation can be derived using a cosine and a sine transform, respectively. Sufficient conditions of validity of the two formulas are established. Their comparison shows that the former solution is preferable to the latter in that it requires less a priori information (knowledge of the particle number density is not needed) and has wider applicability. For gamma-type distributions, and either a real or a complex refractive index, explicit expressions are provided for retrieving the distribution parameters; such expressions are, interestingly, proportional to the geometric area of the polydispersion.
Kronecker Products on Preconditioning
Gao, Longfei
2013-08-01
Numerical techniques for linear systems arising from discretization of partial differential equations are nowadays essential for understanding the physical world. Among these techniques, iterative methods and the accompanying preconditioning techniques have become increasingly popular due to their great potential on large scale computation. In this work, we present preconditioning techniques for linear systems built with tensor product basis functions. Efficient algorithms are designed for various problems by exploiting the Kronecker product structure in the matrices, inherited from tensor product basis functions. Specifically, we design preconditioners for mass matrices to remove the complexity from the basis functions used in isogeometric analysis, obtaining numerical performance independent of mesh size, polynomial order and continuity order; we also present a compound iteration preconditioner for stiffness matrices in two dimensions, obtaining fast convergence speed; lastly, for the Helmholtz problem, we present a strategy to `hide\\' its indefiniteness from Krylov subspace methods by eliminating the part of initial error that corresponds to those negative generalized eigenvalues. For all three cases, the Kronecker product structure in the matrices is exploited to achieve high computational efficiency.
40 CFR 80.52 - Vehicle preconditioning.
2010-07-01
... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...
A subspace preconditioning algorithm for eigenvector/eigenvalue computation
Energy Technology Data Exchange (ETDEWEB)
Bramble, J.H.; Knyazev, A.V.; Pasciak, J.E.
1996-12-31
We consider the problem of computing a modest number of the smallest eigenvalues along with orthogonal bases for the corresponding eigen-spaces of a symmetric positive definite matrix. In our applications, the dimension of a matrix is large and the cost of its inverting is prohibitive. In this paper, we shall develop an effective parallelizable technique for computing these eigenvalues and eigenvectors utilizing subspace iteration and preconditioning. Estimates will be provided which show that the preconditioned method converges linearly and uniformly in the matrix dimension when used with a uniform preconditioner under the assumption that the approximating subspace is close enough to the span of desired eigenvectors.
Orderings for conjugate gradient preconditionings
Ortega, James M.
1991-01-01
The effect of orderings on the rate of convergence of the conjugate gradient method with SSOR or incomplete Cholesky preconditioning is examined. Some results also are presented that help to explain why red/black ordering gives an inferior rate of convergence.
Macro-elementwise preconditioning methods
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe
2012-01-01
Roč. 82, č. 10 (2012), s. 1952-1963 ISSN 0378-4754 Institutional research plan: CEZ:AV0Z30860518 Keywords : heterogeniety * elementwise preconditioning * block matrix partitioning * macro-elements Subject RIV: BA - General Mathematics Impact factor: 0.836, year: 2012 http://www.sciencedirect.com/science/journal/03784754
Pharmacological preconditioning with GYKI 52466: a prophylactic approach to neuroprotection
Directory of Open Access Journals (Sweden)
Chelsea S Goulton
2010-08-01
Full Text Available Some toxins and drugs can trigger lasting neuroprotective mechanisms that enable neurons to resist a subsequent severe insult. This ‘pharmacological preconditioning’ has far-reaching implications for conditions in which blood flow to the brain is interrupted. We have previously shown that in vitro preconditioning with the AMPA receptor antagonist GYKI 52466 induces tolerance to kainic acid (KA toxicity in hippocampus. This effect persists well after washout of the drug and may be mediated via inverse agonism of G protein linked receptors. Given the amplifying nature of metabotropic modulation, we hypothesised that GYKI 52466 may be effective in reducing seizure severity at doses well below those normally associated with adverse side effects. Here we report that pharmacological preconditioning with low-dose GYKI imparts a significant protection against KA-induced seizures in vivo. GYKI (3 mg/kg, s.c., 90 to 180 min. prior to high-dose KA, markedly reduced seizure scores, virtually abolished all level 3 and level 4 seizures, and completely suppressed KA-induced hippocampal cFOS expression. In addition, preconditioned animals exhibited significant reductions in high frequency/high amplitude spiking and ECoG power in the delta, theta, alpha and beta bands during KA. Adverse behaviours often associated with higher doses of GYKI were not evident during preconditioning. The fact that GYKI is effective at doses well-below, and at pre-administration intervals well-beyond previous studies, suggests that a classical blockade of ionotropic AMPA receptors does not underlie anticonvulsant effects. Low-dose GYKI preconditioning may represent a novel, prophylactic strategy for neuroprotection in a field almost completely devoid of effective pharmaceuticals.
Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.
Fessler, J A; Booth, S D
1999-01-01
Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.
Koldan, Jelena; Puzyrev, Vladimir; de la Puente, Josep; Houzeaux, Guillaume; Cela, José María
2014-06-01
We present an elaborate preconditioning scheme for Krylov subspace methods which has been developed to improve the performance and reduce the execution time of parallel node-based finite-element (FE) solvers for 3-D electromagnetic (EM) numerical modelling in exploration geophysics. This new preconditioner is based on algebraic multigrid (AMG) that uses different basic relaxation methods, such as Jacobi, symmetric successive over-relaxation (SSOR) and Gauss-Seidel, as smoothers and the wave front algorithm to create groups, which are used for a coarse-level generation. We have implemented and tested this new preconditioner within our parallel nodal FE solver for 3-D forward problems in EM induction geophysics. We have performed series of experiments for several models with different conductivity structures and characteristics to test the performance of our AMG preconditioning technique when combined with biconjugate gradient stabilized method. The results have shown that, the more challenging the problem is in terms of conductivity contrasts, ratio between the sizes of grid elements and/or frequency, the more benefit is obtained by using this preconditioner. Compared to other preconditioning schemes, such as diagonal, SSOR and truncated approximate inverse, the AMG preconditioner greatly improves the convergence of the iterative solver for all tested models. Also, when it comes to cases in which other preconditioners succeed to converge to a desired precision, AMG is able to considerably reduce the total execution time of the forward-problem code-up to an order of magnitude. Furthermore, the tests have confirmed that our AMG scheme ensures grid-independent rate of convergence, as well as improvement in convergence regardless of how big local mesh refinements are. In addition, AMG is designed to be a black-box preconditioner, which makes it easy to use and combine with different iterative methods. Finally, it has proved to be very practical and efficient in the
Preconditioned iterations to calculate extreme eigenvalues
Energy Technology Data Exchange (ETDEWEB)
Brand, C.W.; Petrova, S. [Institut fuer Angewandte Mathematik, Leoben (Austria)
1994-12-31
Common iterative algorithms to calculate a few extreme eigenvalues of a large, sparse matrix are Lanczos methods or power iterations. They converge at a rate proportional to the separation of the extreme eigenvalues from the rest of the spectrum. Appropriate preconditioning improves the separation of the eigenvalues. Davidson`s method and its generalizations exploit this fact. The authors examine a preconditioned iteration that resembles a truncated version of Davidson`s method with a different preconditioning strategy.
Management of Preconditioned Calves and Impacts of Preconditioning.
Hilton, W Mark
2015-07-01
When studying the practice of preconditioning (PC) calves, many factors need to be examined to determine if cow-calf producers should make this investment. Factors such as average daily gain, feed efficiency, available labor, length of the PC period, genetics, and marketing options must be analyzed. The health sales price advantage is an additional benefit in producing and selling PC calves but not the sole determinant of PC's financially feasibility. Studies show that a substantial advantage of PC is the selling of additional pounds at a cost of gain well below the marginal return of producing those additional pounds. Copyright © 2015 Elsevier Inc. All rights reserved.
Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y
2018-04-01
Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping
Isoflurane preconditions myocardium against infarction via release of free radicals
Müllenheim, Jost; Ebel, Dirk; Frässdorf, Jan; Preckel, Benedikt; Thämer, Volker; Schlack, Wolfgang
2002-01-01
BACKGROUND: Isoflurane exerts cardioprotective effects that mimic the ischemic preconditioning phenomenon. Generation of free radicals is implicated in ischemic preconditioning. The authors investigated whether isoflurane-induced preconditioning may involve release of free radicals. METHODS:
Preconditioning for Mixed Finite Element Formulations of Elliptic Problems
Wildey, Tim; Xue, Guangri
2013-01-01
In this paper, we discuss a preconditioning technique for mixed finite element discretizations of elliptic equations. The technique is based on a block-diagonal approximation of the mass matrix which maintains the sparsity and positive definiteness of the corresponding Schur complement. This preconditioner arises from the multipoint flux mixed finite element method and is robust with respect to mesh size and is better conditioned for full permeability tensors than a preconditioner based on a diagonal approximation of the mass matrix. © Springer-Verlag Berlin Heidelberg 2013.
Ischemic preconditioning protects against ischemic brain injury
Directory of Open Access Journals (Sweden)
Xiao-meng Ma
2016-01-01
Full Text Available In this study, we hypothesized that an increase in integrin αv ß 3 and its co-activator vascular endothelial growth factor play important neuroprotective roles in ischemic injury. We performed ischemic preconditioning with bilateral common carotid artery occlusion for 5 minutes in C57BL/6J mice. This was followed by ischemic injury with bilateral common carotid artery occlusion for 30 minutes. The time interval between ischemic preconditioning and lethal ischemia was 48 hours. Histopathological analysis showed that ischemic preconditioning substantially diminished damage to neurons in the hippocampus 7 days after ischemia. Evans Blue dye assay showed that ischemic preconditioning reduced damage to the blood-brain barrier 24 hours after ischemia. This demonstrates the neuroprotective effect of ischemic preconditioning. Western blot assay revealed a significant reduction in protein levels of integrin αv ß 3, vascular endothelial growth factor and its receptor in mice given ischemic preconditioning compared with mice not given ischemic preconditioning 24 hours after ischemia. These findings suggest that the neuroprotective effect of ischemic preconditioning is associated with lower integrin αv ß 3 and vascular endothelial growth factor levels in the brain following ischemia.
Rational Approximations of the Inverse Gaussian Function.
Byars, Jackson A.; Roscoe, John T.
There are at least two situations in which the behavioral scientist wishes to transform uniformly distributed data into normally distributed data: (1) In studies of sampling distributions where uniformly distributed pseudo-random numbers are generated by a computer but normally distributed numbers are desired; and (2) In measurement applications…
Improving Inversions of the Overlap Operator
International Nuclear Information System (INIS)
Krieg, S.; Cundy, N.; Eshof, J. van den; Frommer, A.; Lippert, Th.; Schaefer, K.
2005-01-01
We present relaxation and preconditioning techniques which accelerate the inversion of the overlap operator by a factor of four on small lattices, with larger gains as the lattice size increases. These improvements can be used in both propagator calculations and dynamical simulations
Preconditioned Krylov subspace methods for eigenvalue problems
Energy Technology Data Exchange (ETDEWEB)
Wu, Kesheng; Saad, Y.; Stathopoulos, A. [Univ. of Minnesota, Minneapolis, MN (United States)
1996-12-31
Lanczos algorithm is a commonly used method for finding a few extreme eigenvalues of symmetric matrices. It is effective if the wanted eigenvalues have large relative separations. If separations are small, several alternatives are often used, including the shift-invert Lanczos method, the preconditioned Lanczos method, and Davidson method. The shift-invert Lanczos method requires direct factorization of the matrix, which is often impractical if the matrix is large. In these cases preconditioned schemes are preferred. Many applications require solution of hundreds or thousands of eigenvalues of large sparse matrices, which pose serious challenges for both iterative eigenvalue solver and preconditioner. In this paper we will explore several preconditioned eigenvalue solvers and identify the ones suited for finding large number of eigenvalues. Methods discussed in this paper make up the core of a preconditioned eigenvalue toolkit under construction.
Incomplete block factorization preconditioning for indefinite elliptic problems
Energy Technology Data Exchange (ETDEWEB)
Guo, Chun-Hua [Univ. of Calgary, Alberta (Canada)
1996-12-31
The application of the finite difference method to approximate the solution of an indefinite elliptic problem produces a linear system whose coefficient matrix is block tridiagonal and symmetric indefinite. Such a linear system can be solved efficiently by a conjugate residual method, particularly when combined with a good preconditioner. We show that specific incomplete block factorization exists for the indefinite matrix if the mesh size is reasonably small. And this factorization can serve as an efficient preconditioner. Some efforts are made to estimate the eigenvalues of the preconditioned matrix. Numerical results are also given.
Moving force identification based on modified preconditioned conjugate gradient method
Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy
2018-06-01
This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.
Ischemic Preconditioning of One Forearm Enhances Static and Dynamic Apnea
DEFF Research Database (Denmark)
Kjeld, Thomas; Rasmussen, Mads Reinholdt; Jattu, Timo
2014-01-01
INTRODUCTION: Ischemic preconditioning enhances ergometer cycling and swimming performance. We evaluated whether ischemic preconditioning of one forearm (four times for 5 min) also affects static breath hold and underwater swimming, whereas the effect of similar preconditioning on ergometer rowing...... preconditioning reduced the forearm oxygen saturation from 65% ± 7% to 19% ± 7% (mean ± SD; P right thigh.......05). CONCLUSIONS: We conclude that while the effect of ischemic preconditioning (of one forearm) on ergometer rowing was minimal, probably because of reduced muscle oxygenation during the warm-up, ischemic preconditioning does enhance both static and dynamic apnea, supporting that muscle ischemia is an important...
Xenon preconditioning: molecular mechanisms and biological effects
Directory of Open Access Journals (Sweden)
Liu Wenwu
2013-01-01
Full Text Available Abstract Xenon is one of noble gases and has been recognized as an anesthetic for more than 50 years. Xenon possesses many of the characteristics of an ideal anesthetic, but it is not widely applied in clinical practice mainly because of its high cost. In recent years, numerous studies have demonstrated that xenon as an anesthetic can exert neuroprotective and cardioprotective effects in different models. Moreover, xenon has been applied in the preconditioning, and the neuroprotective and cardioprotective effects of xenon preconditioning have been investigated in a lot of studies in which some mechanisms related to these protections are proposed. In this review, we summarized these mechanisms and the biological effects of xenon preconditioning.
Minimal residual method stronger than polynomial preconditioning
Energy Technology Data Exchange (ETDEWEB)
Faber, V.; Joubert, W.; Knill, E. [Los Alamos National Lab., NM (United States)] [and others
1994-12-31
Two popular methods for solving symmetric and nonsymmetric systems of equations are the minimal residual method, implemented by algorithms such as GMRES, and polynomial preconditioning methods. In this study results are given on the convergence rates of these methods for various classes of matrices. It is shown that for some matrices, such as normal matrices, the convergence rates for GMRES and for the optimal polynomial preconditioning are the same, and for other matrices such as the upper triangular Toeplitz matrices, it is at least assured that if one method converges then the other must converge. On the other hand, it is shown that matrices exist for which restarted GMRES always converges but any polynomial preconditioning of corresponding degree makes no progress toward the solution for some initial error. The implications of these results for these and other iterative methods are discussed.
Projection preconditioning for Lanczos-type methods
Energy Technology Data Exchange (ETDEWEB)
Bielawski, S.S.; Mulyarchik, S.G.; Popov, A.V. [Belarusian State Univ., Minsk (Belarus)
1996-12-31
We show how auxiliary subspaces and related projectors may be used for preconditioning nonsymmetric system of linear equations. It is shown that preconditioned in such a way (or projected) system is better conditioned than original system (at least if the coefficient matrix of the system to be solved is symmetrizable). Two approaches for solving projected system are outlined. The first one implies straightforward computation of the projected matrix and consequent using some direct or iterative method. The second approach is the projection preconditioning of conjugate gradient-type solver. The latter approach is developed here in context with biconjugate gradient iteration and some related Lanczos-type algorithms. Some possible particular choices of auxiliary subspaces are discussed. It is shown that one of them is equivalent to using colorings. Some results of numerical experiments are reported.
Preconditioning the modified conjugate gradient method ...
African Journals Online (AJOL)
In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. And the convergence analysis of the modified conjugate Gradient method was analysed with our extension on preconditioning the algorithm. Convergence of the algorithm is a function of the condition number of M-1A.
Equivalent operator preconditioning for elliptic problems
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2009-01-01
Roč. 50, č. 3 (2009), s. 297-380 ISSN 1017-1398 Institutional research plan: CEZ:AV0Z30860518 Keywords : Elliptic problem * Conjugate gradient method * preconditioning * equivalent operators * compact operators Subject RIV: BA - General Mathematics Impact factor: 0.716, year: 2009 http://en.scientificcommons.org/42514649
Preconditioning of iterative methods - theory and applications
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Blaheta, Radim; Neytcheva, M.; Pultarová, I.
2015-01-01
Roč. 22, č. 6 (2015), s. 901-902 ISSN 1070-5325 Institutional support: RVO:68145535 Keywords : preconditioning * iterative methods * applications Subject RIV: BA - General Mathematics Impact factor: 1.431, year: 2015 http://onlinelibrary.wiley.com/doi/10.1002/nla.2016/epdf
Itoh, Shoji; Sugihara, Masaaki
2016-01-01
We present a theorem that defines the direction of a preconditioned system for the bi-conjugate gradient (BiCG) method, and we extend it to preconditioned bi-Lanczos-type algorithms. We show that the direction of a preconditioned system is switched by construction and by the settings of the initial shadow residual vector. We analyze and compare the polynomial structures of four preconditioned BiCG algorithms.
CERN. Geneva
2015-01-01
Most physics results at the LHC end in a likelihood ratio test. This includes discovery and exclusion for searches as well as mass, cross-section, and coupling measurements. The use of Machine Learning (multivariate) algorithms in HEP is mainly restricted to searches, which can be reduced to classification between two fixed distributions: signal vs. background. I will show how we can extend the use of ML classifiers to distributions parameterized by physical quantities like masses and couplings as well as nuisance parameters associated to systematic uncertainties. This allows for one to approximate the likelihood ratio while still using a high dimensional feature vector for the data. Both the MEM and ABC approaches mentioned above aim to provide inference on model parameters (like cross-sections, masses, couplings, etc.). ABC is fundamentally tied Bayesian inference and focuses on the “likelihood free” setting where only a simulator is available and one cannot directly compute the likelihood for the dat...
Schmidt, Wolfgang M
1980-01-01
"In 1970, at the U. of Colorado, the author delivered a course of lectures on his famous generalization, then just established, relating to Roth's theorem on rational approxi- mations to algebraic numbers. The present volume is an ex- panded and up-dated version of the original mimeographed notes on the course. As an introduction to the author's own remarkable achievements relating to the Thue-Siegel-Roth theory, the text can hardly be bettered and the tract can already be regarded as a classic in its field."(Bull.LMS) "Schmidt's work on approximations by algebraic numbers belongs to the deepest and most satisfactory parts of number theory. These notes give the best accessible way to learn the subject. ... this book is highly recommended." (Mededelingen van het Wiskundig Genootschap)
Preconditions for Citizen Journalism: A Sociological Assessment
Hayley Watson
2011-01-01
The rise of the citizen journalist and increased attention to this phenomenon requires a sociological assessment that seeks to develop an understanding of how citizen journalism has emerged in contemporary society. This article makes a distinction between two different subcategories of citizen journalism, that is independent and dependent citizen journalism. The purpose of this article is to present four preconditions for citizen journalism to emerge in contemporary society: advanced technolo...
Error Estimation in Preconditioned Conjugate Gradients
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2005-01-01
Roč. 45, - (2005), s. 789-817 ISSN 0006-3835 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB1030306 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned conjugate gradient method * error bounds * stopping criteria * evaluation of convergence * numerical stability * finite precision arithmetic * rounding errors Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2005
M-step preconditioned conjugate gradient methods
Adams, L.
1983-01-01
Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems of linear equations are described. Necessary and sufficient conditions are given for when these preconditioners can be used and an analysis of their effectiveness is given. Efficient computer implementations of these methods are discussed and results on the CYBER 203 and the Finite Element Machine under construction at NASA Langley Research Center are included.
Radiographers' preconditions for evidence-based radiography
International Nuclear Information System (INIS)
Ahonen, Sanna-Mari; Liikanen, Eeva
2010-01-01
Evidence-based practice (EBP) is essential in today's health care, but its establishment requires several preconditions from individuals and organizations (e.g. knowledge, understanding, attitudes, abilities, self-confidence, support, and resources). Previous studies suggest that radiographers do generate and use evidence in their work, but evidence-based radiography (EBR) is not yet used routinely as established practice, especially in terms of research utilization. This paper aims to describe radiographers' preconditions for EBR, and their participation in research activities. Main focus is on research utilization. Using an electronic questionnaire developed for this study, a survey was conducted: data collected from Finnish radiographers and radiotherapists (N = 438) were analysed both statistically and qualitatively. The final response rate was 39%. The results suggest radiographers' preconditions for EBR to consist of knowledge of research, significance of research activities, research-orientated way of working, and support. In addition, adequate resourcing is essential. Reading scientific journals, participation in research activities, a higher degree of education, and senior post seem to be significant promoters of EBR and research utilization. The results support the notion that EBR, and especially research utilization, are not yet well-established in Finland, and radiographers' viewpoints concerning the role and significance of research evidence and research activities still seem to vary.
International Nuclear Information System (INIS)
Namatame, Hirofumi; Taniguchi, Masaki
1994-01-01
Photoelectron spectroscopy is regarded as the most powerful means since it can measure almost perfectly the occupied electron state. On the other hand, inverse photoelectron spectroscopy is the technique for measuring unoccupied electron state by using the inverse process of photoelectron spectroscopy, and in principle, the similar experiment to photoelectron spectroscopy becomes feasible. The development of the experimental technology for inverse photoelectron spectroscopy has been carried out energetically by many research groups so far. At present, the heightening of resolution of inverse photoelectron spectroscopy, the development of inverse photoelectron spectroscope in which light energy is variable and so on are carried out. But the inverse photoelectron spectroscope for vacuum ultraviolet region is not on the market. In this report, the principle of inverse photoelectron spectroscopy and the present state of the spectroscope are described, and the direction of the development hereafter is groped. As the experimental equipment, electron guns, light detectors and so on are explained. As the examples of the experiment, the inverse photoelectron spectroscopy of semimagnetic semiconductors and resonance inverse photoelectron spectroscopy are reported. (K.I.)
An improved saddlepoint approximation.
Gillespie, Colin S; Renshaw, Eric
2007-08-01
Given a set of third- or higher-order moments, not only is the saddlepoint approximation the only realistic 'family-free' technique available for constructing an associated probability distribution, but it is 'optimal' in the sense that it is based on the highly efficient numerical method of steepest descents. However, it suffers from the problem of not always yielding full support, and whilst [S. Wang, General saddlepoint approximations in the bootstrap, Prob. Stat. Lett. 27 (1992) 61.] neat scaling approach provides a solution to this hurdle, it leads to potentially inaccurate and aberrant results. We therefore propose several new ways of surmounting such difficulties, including: extending the inversion of the cumulant generating function to second-order; selecting an appropriate probability structure for higher-order cumulants (the standard moment closure procedure takes them to be zero); and, making subtle changes to the target cumulants and then optimising via the simplex algorithm.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Blaheta, Radim
2013-01-01
Roč. 20, č. 3 (2013), s. 536-539 ISSN 1070-5325 Institutional support: RVO:68145535 Keywords : saddle point matrices * inverses * preconditioning Subject RIV: BA - General Mathematics Impact factor: 1.424, year: 2013 http://onlinelibrary.wiley.com/doi/10.1002/nla.816/pdf
Solving large mixed linear models using preconditioned conjugate gradient iteration.
Strandén, I; Lidauer, M
1999-12-01
Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.
Matrix preconditioning: a robust operation for optical linear algebra processors.
Ghosh, A; Paparao, P
1987-07-15
Analog electrooptical processors are best suited for applications demanding high computational throughput with tolerance for inaccuracies. Matrix preconditioning is one such application. Matrix preconditioning is a preprocessing step for reducing the condition number of a matrix and is used extensively with gradient algorithms for increasing the rate of convergence and improving the accuracy of the solution. In this paper, we describe a simple parallel algorithm for matrix preconditioning, which can be implemented efficiently on a pipelined optical linear algebra processor. From the results of our numerical experiments we show that the efficacy of the preconditioning algorithm is affected very little by the errors of the optical system.
Ischemic preconditioning protects against gap junctional uncoupling in cardiac myofibroblasts.
Sundset, Rune; Cooper, Marie; Mikalsen, Svein-Ole; Ytrehus, Kirsti
2004-01-01
Ischemic preconditioning increases the heart's tolerance to a subsequent longer ischemic period. The purpose of this study was to investigate the role of gap junction communication in simulated preconditioning in cultured neonatal rat cardiac myofibroblasts. Gap junctional intercellular communication was assessed by Lucifer yellow dye transfer. Preconditioning preserved intercellular coupling after prolonged ischemia. An initial reduction in coupling in response to the preconditioning stimulus was also observed. This may protect neighboring cells from damaging substances produced during subsequent regional ischemia in vivo, and may preserve gap junctional communication required for enhanced functional recovery during subsequent reperfusion.
Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.
Temel, Burcin; Mills, Greg; Metiu, Horia
2008-03-27
We describe and test an implementation, using a basis set of Chebyshev polynomials, of a variational method for solving scattering problems in quantum mechanics. This minimum error method (MEM) determines the wave function Psi by minimizing the least-squares error in the function (H Psi - E Psi), where E is the desired scattering energy. We compare the MEM to an alternative, the Kohn variational principle (KVP), by solving the Secrest-Johnson model of two-dimensional inelastic scattering, which has been studied previously using the KVP and for which other numerical solutions are available. We use a conjugate gradient (CG) method to minimize the error, and by preconditioning the CG search, we are able to greatly reduce the number of iterations necessary; the method is thus faster and more stable than a matrix inversion, as is required in the KVP. Also, we avoid errors due to scattering off of the boundaries, which presents substantial problems for other methods, by matching the wave function in the interaction region to the correct asymptotic states at the specified energy; the use of Chebyshev polynomials allows this boundary condition to be implemented accurately. The use of Chebyshev polynomials allows for a rapid and accurate evaluation of the kinetic energy. This basis set is as efficient as plane waves but does not impose an artificial periodicity on the system. There are problems in surface science and molecular electronics which cannot be solved if periodicity is imposed, and the Chebyshev basis set is a good alternative in such situations.
van Caster, Patrick; Eiling, Sandra; Boekholt, Yvonne; Behmenburg, Friederike; Dorsch, Marianne; Heinen, André; Hollmann, Markus W.; Huhn, Ragnar
2018-01-01
Prior studies have suggested that the antifibrinolytic drug aprotinin increases the infarct size after ischemia and reperfusion (I/R) and attenuates the effect of ischemic preconditioning (IPC). Aprotinin was replaced by tranexamic acid (TXA) in clinical practice. Here, we investigated whether TXA
Ingram, WT
2012-01-01
Inverse limits provide a powerful tool for constructing complicated spaces from simple ones. They also turn the study of a dynamical system consisting of a space and a self-map into a study of a (likely more complicated) space and a self-homeomorphism. In four chapters along with an appendix containing background material the authors develop the theory of inverse limits. The book begins with an introduction through inverse limits on [0,1] before moving to a general treatment of the subject. Special topics in continuum theory complete the book. Although it is not a book on dynamics, the influen
Parallel preconditioning techniques for sparse CG solvers
Energy Technology Data Exchange (ETDEWEB)
Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)
1996-12-31
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.
Preconditioning, postconditioning and their application to clinical cardiology.
Kloner, Robert A; Rezkalla, Shereif H
2006-05-01
Ischemic preconditioning is a well-established phenomenon first described in experimental preparations in which brief episodes of ischemia/reperfusion applied prior to a longer coronary artery occlusion reduce myocardial infarct size. There are ample correlates of ischemic preconditioning in the clinical realm. Preconditioning mimetic agents that stimulate the biochemical pathways of ischemic preconditioning and protect the heart without inducing ischemia have been examined in numerous experimental studies. However, despite the effectiveness of ischemic preconditioning and preconditioning mimetics for protecting ischemic myocardium, there are no preconditioning-based therapies that are routinely used in clinical medicine at the current time. Part of the problem is the need to administer therapy prior to the known ischemic event. Other issues are that percutaneous coronary intervention technology has advanced so far (with the development of stents and drug-eluting stents) that ischemic preconditioning or preconditioning mimetics have not been needed in most interventional cases. Recent clinical trials such as AMISTAD I and II (Acute Myocardial Infarction STudy of ADenosine) suggest that some preconditioning mimetics may reduce myocardial infarct size when given along with reperfusion or, as in the IONA trial, have benefit on clinical events when administered chronically in patients with known coronary artery disease. It is possible that some of the benefit described for adenosine in the AMISTAD 1 and 2 trials represents a manifestation of the recently described postconditioning phenomenon. It is probable that postconditioning--in which reperfusion is interrupted with brief coronary occlusions and reperfusion sequences--is more likely than preconditioning to be feasible as a clinical application to patients undergoing percutaneous coronary intervention for acute myocardial infarction.
Convergence Analysis of the Preconditioned Group Splitting Methods in Boundary Value Problems
Directory of Open Access Journals (Sweden)
Norhashidah Hj. Mohd Ali
2012-01-01
Full Text Available The construction of a specific splitting-type preconditioner in block formulation applied to a class of group relaxation iterative methods derived from the centred and rotated (skewed finite difference approximations has been shown to improve the convergence rates of these methods. In this paper, we present some theoretical convergence analysis on this preconditioner specifically applied to the linear systems resulted from these group iterative schemes in solving an elliptic boundary value problem. We will theoretically show the relationship between the spectral radiuses of the iteration matrices of the preconditioned methods which affects the rate of convergence of these methods. We will also show that the spectral radius of the preconditioned matrices is smaller than that of their unpreconditioned counterparts if the relaxation parameter is in a certain optimum range. Numerical experiments will also be presented to confirm the agreement between the theoretical and the experimental results.
Field-Split Preconditioned Inexact Newton Algorithms
Liu, Lulu
2015-06-02
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm is presented as a complement to additive Schwarz preconditioned inexact Newton (ASPIN). At an algebraic level, ASPIN and MSPIN are variants of the same strategy to improve the convergence of systems with unbalanced nonlinearities; however, they have natural complementarity in practice. MSPIN is naturally based on partitioning of degrees of freedom in a nonlinear PDE system by field type rather than by subdomain, where a modest factor of concurrency can be sacrificed for physically motivated convergence robustness. ASPIN, originally introduced for decompositions into subdomains, is natural for high concurrency and reduction of global synchronization. We consider both types of inexact Newton algorithms in the field-split context, and we augment the classical convergence theory of ASPIN for the multiplicative case. Numerical experiments show that MSPIN can be significantly more robust than Newton methods based on global linearizations, and that MSPIN can be more robust than ASPIN and maintain fast convergence even for challenging problems, such as high Reynolds number Navier--Stokes equations.
Field-Split Preconditioned Inexact Newton Algorithms
Liu, Lulu; Keyes, David E.
2015-01-01
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm is presented as a complement to additive Schwarz preconditioned inexact Newton (ASPIN). At an algebraic level, ASPIN and MSPIN are variants of the same strategy to improve the convergence of systems with unbalanced nonlinearities; however, they have natural complementarity in practice. MSPIN is naturally based on partitioning of degrees of freedom in a nonlinear PDE system by field type rather than by subdomain, where a modest factor of concurrency can be sacrificed for physically motivated convergence robustness. ASPIN, originally introduced for decompositions into subdomains, is natural for high concurrency and reduction of global synchronization. We consider both types of inexact Newton algorithms in the field-split context, and we augment the classical convergence theory of ASPIN for the multiplicative case. Numerical experiments show that MSPIN can be significantly more robust than Newton methods based on global linearizations, and that MSPIN can be more robust than ASPIN and maintain fast convergence even for challenging problems, such as high Reynolds number Navier--Stokes equations.
The multigrid preconditioned conjugate gradient method
Tatebe, Osamu
1993-01-01
A multigrid preconditioned conjugate gradient method (MGCG method), which uses the multigrid method as a preconditioner of the PCG method, is proposed. The multigrid method has inherent high parallelism and improves convergence of long wavelength components, which is important in iterative methods. By using this method as a preconditioner of the PCG method, an efficient method with high parallelism and fast convergence is obtained. First, it is considered a necessary condition of the multigrid preconditioner in order to satisfy requirements of a preconditioner of the PCG method. Next numerical experiments show a behavior of the MGCG method and that the MGCG method is superior to both the ICCG method and the multigrid method in point of fast convergence and high parallelism. This fast convergence is understood in terms of the eigenvalue analysis of the preconditioned matrix. From this observation of the multigrid preconditioner, it is realized that the MGCG method converges in very few iterations and the multigrid preconditioner is a desirable preconditioner of the conjugate gradient method.
Ren, Chuancheng; Gao, Xuwen; Steinberg, Gary K.; Zhao, Heng
2009-01-01
Remote ischemic preconditioning is an emerging concept for stroke treatment, but its protection against focal stroke has not been established. We tested whether remote preconditioning, performed in the ipsilateral hind limb, protects against focal stroke and explored its protective parameters. Stroke was generated by a permanent occlusion of the left distal middle cerebral artery (MCA) combined with a 30 minute occlusion of the bilateral common carotid arteries (CCA) in male rats. Limb preconditioning was generated by 5 or 15 minute occlusion followed with the same period of reperfusion of the left hind femoral artery, and repeated for 2 or 3 cycles. Infarct was measured 2 days later. The results showed that rapid preconditioning with 3 cycles of 15 minutes performed immediately before stroke reduced infarct size from 47.7±7.6% of control ischemia to 9.8±8.6%; at 2 cycles of 15 minutes, infarct was reduced to 24.7±7.3%; at 2 cycles of 5 minutes, infarct was not reduced. Delayed preconditioning with 3 cycles of 15 minutes conducted 2 days before stroke also reduced infarct to 23.0 ±10.9%, but with 2 cycles of 15 minutes it offered no protection. The protective effects at these two therapeutic time windows of remote preconditioning are consistent with those of conventional preconditioning, in which the preconditioning ischemia is induced in the brain itself. Unexpectedly, intermediate preconditioning with 3 cycles of 15 minutes performed 12 hours before stroke also reduced infarct to 24.7±4.7%, which contradicts the current dogma for therapeutic time windows for the conventional preconditioning that has no protection at this time point. In conclusion, remote preconditioning performed in one limb protected against ischemic damage after focal cerebral ischemia. PMID:18201834
40 CFR 86.532-78 - Vehicle preconditioning.
2010-07-01
... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Vehicle preconditioning. 86.532-78... (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES Emission Regulations for 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle...
Helium induces preconditioning in human endothelium in vivo
Smit, Kirsten F.; Oei, Gezina T. M. L.; Brevoord, Daniel; Stroes, Erik S.; Nieuwland, Rienk; Schlack, Wolfgang S.; Hollmann, Markus W.; Weber, Nina C.; Preckel, Benedikt
2013-01-01
Helium protects myocardium by inducing preconditioning in animals. We investigated whether human endothelium is preconditioned by helium inhalation in vivo. Forearm ischemia-reperfusion (I/R) in healthy volunteers (each group n = 10) was performed by inflating a blood pressure cuff for 20 min.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong; Alkhalifah, Tariq Ali
2016-01-01
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong
2016-03-28
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
Approximate systems with confluent bonding mappings
Lončar, Ivan
2001-01-01
If X = {Xn, pnm, N} is a usual inverse system with confluent (monotone) bonding mappings, then the projections are confluent (monotone). This is not true for approximate inverse system. The main purpose of this paper is to show that the property of Kelley (smoothness) of the space Xn is a sufficient condition for the confluence (monotonicity) of the projections.
Codd, A. L.; Gross, L.
2018-03-01
We present a new inversion method for Electrical Resistivity Tomography which, in contrast to established approaches, minimizes the cost function prior to finite element discretization for the unknown electric conductivity and electric potential. Minimization is performed with the Broyden-Fletcher-Goldfarb-Shanno method (BFGS) in an appropriate function space. BFGS is self-preconditioning and avoids construction of the dense Hessian which is the major obstacle to solving large 3-D problems using parallel computers. In addition to the forward problem predicting the measurement from the injected current, the so-called adjoint problem also needs to be solved. For this problem a virtual current is injected through the measurement electrodes and an adjoint electric potential is obtained. The magnitude of the injected virtual current is equal to the misfit at the measurement electrodes. This new approach has the advantage that the solution process of the optimization problem remains independent to the meshes used for discretization and allows for mesh adaptation during inversion. Computation time is reduced by using superposition of pole loads for the forward and adjoint problems. A smoothed aggregation algebraic multigrid (AMG) preconditioned conjugate gradient is applied to construct the potentials for a given electric conductivity estimate and for constructing a first level BFGS preconditioner. Through the additional reuse of AMG operators and coarse grid solvers inversion time for large 3-D problems can be reduced further. We apply our new inversion method to synthetic survey data created by the resistivity profile representing the characteristics of subsurface fluid injection. We further test it on data obtained from a 2-D surface electrode survey on Heron Island, a small tropical island off the east coast of central Queensland, Australia.
Weighted SGD for ℓp Regression with Randomized Preconditioning*
Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W.
2018-01-01
In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems—e.g., ℓ2 and ℓ1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓp regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓp solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ1 regression with size n by d, pwSGD returns an approximate solution with ε relative error in the objective value in 𝒪(log n·nnz(A)+poly(d)/ε2) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in
Laterally constrained inversion for CSAMT data interpretation
Wang, Ruo; Yin, Changchun; Wang, Miaoyue; Di, Qingyun
2015-10-01
Laterally constrained inversion (LCI) has been successfully applied to the inversion of dc resistivity, TEM and airborne EM data. However, it hasn't been yet applied to the interpretation of controlled-source audio-frequency magnetotelluric (CSAMT) data. In this paper, we apply the LCI method for CSAMT data inversion by preconditioning the Jacobian matrix. We apply a weighting matrix to Jacobian to balance the sensitivity of model parameters, so that the resolution with respect to different model parameters becomes more uniform. Numerical experiments confirm that this can improve the convergence of the inversion. We first invert a synthetic dataset with and without noise to investigate the effect of LCI applications to CSAMT data, for the noise free data, the results show that the LCI method can recover the true model better compared to the traditional single-station inversion; and for the noisy data, the true model is recovered even with a noise level of 8%, indicating that LCI inversions are to some extent noise insensitive. Then, we re-invert two CSAMT datasets collected respectively in a watershed and a coal mine area in Northern China and compare our results with those from previous inversions. The comparison with the previous inversion in a coal mine shows that LCI method delivers smoother layer interfaces that well correlate to seismic data, while comparison with a global searching algorithm of simulated annealing (SA) in a watershed shows that though both methods deliver very similar good results, however, LCI algorithm presented in this paper runs much faster. The inversion results for the coal mine CSAMT survey show that a conductive water-bearing zone that was not revealed by the previous inversions has been identified by the LCI. This further demonstrates that the method presented in this paper works for CSAMT data inversion.
A fast, preconditioned conjugate gradient Toeplitz solver
Pan, Victor; Schrieber, Robert
1989-01-01
A simple factorization is given of an arbitrary hermitian, positive definite matrix in which the factors are well-conditioned, hermitian, and positive definite. In fact, given knowledge of the extreme eigenvalues of the original matrix A, an optimal improvement can be achieved, making the condition numbers of each of the two factors equal to the square root of the condition number of A. This technique is to applied to the solution of hermitian, positive definite Toeplitz systems. Large linear systems with hermitian, positive definite Toeplitz matrices arise in some signal processing applications. A stable fast algorithm is given for solving these systems that is based on the preconditioned conjugate gradient method. The algorithm exploits Toeplitz structure to reduce the cost of an iteration to O(n log n) by applying the fast Fourier Transform to compute matrix-vector products. Matrix factorization is used as a preconditioner.
Anesthetic Preconditioning as Endogenous Neuroprotection in Glaucoma
Directory of Open Access Journals (Sweden)
Tsung-Han Chou
2018-01-01
Full Text Available Blindness in glaucoma is the result of death of Retinal Ganglion Cells (RGCs and their axons. RGC death is generally preceded by a stage of reversible dysfunction and structural remodeling. Current treatments aimed at reducing intraocular pressure (IOP are ineffective or incompletely effective in management of the disease. IOP-independent neuroprotection or neuroprotection as adjuvant to IOP lowering in glaucoma remains a challenge as effective agents without side effects have not been identified yet. We show in DBA/2J mice with spontaneous IOP elevation and glaucoma that the lifespan of functional RGCs can be extended by preconditioning RGCs with retrobulbar lidocaine in one eye at four months of age that temporary blocks RGC axonal transport. The contralateral, PBS-injected eye served as control. Lidocaine-induced impairment of axonal transport to superior colliculi was assessed by intravitreal injection of cholera toxin B. Long-term (nine months effect of lidocaine were assessed on RGC electrical responsiveness (PERG, IOP, expression of relevant protein (BDNF, TrkB, PSD95, GFAP, Synaptophysin, and GAPDH and RGC density. While lidocaine treatment did not alter the age-related increase of IOP, TrkB expression was elevated, GFAP expression was decreased, RGC survival was improved by 35%, and PERG function was preserved. Results suggest that the lifespan of functional RGCs in mouse glaucoma can be extended by preconditioning RGCs in early stages of the disease using a minimally invasive treatment with retrobulbar lidocaine, a common ophthalmologic procedure. Lidocaine is inexpensive, safe and is approved by Food and Drug Administration (FDA to be administered intravenously.
Mapping moveout approximations in TI media
Stovas, Alexey; Alkhalifah, Tariq Ali
2013-01-01
Moveout approximations play a very important role in seismic modeling, inversion, and scanning for parameters in complex media. We developed a scheme to map one-way moveout approximations for transversely isotropic media with a vertical axis of symmetry (VTI), which is widely available, to the tilted case (TTI) by introducing the effective tilt angle. As a result, we obtained highly accurate TTI moveout equations analogous with their VTI counterparts. Our analysis showed that the most accurate approximation is obtained from the mapping of generalized approximation. The new moveout approximations allow for, as the examples demonstrate, accurate description of moveout in the TTI case even for vertical heterogeneity. The proposed moveout approximations can be easily used for inversion in a layered TTI medium because the parameters of these approximations explicitly depend on corresponding effective parameters in a layered VTI medium.
Mapping moveout approximations in TI media
Stovas, Alexey
2013-11-21
Moveout approximations play a very important role in seismic modeling, inversion, and scanning for parameters in complex media. We developed a scheme to map one-way moveout approximations for transversely isotropic media with a vertical axis of symmetry (VTI), which is widely available, to the tilted case (TTI) by introducing the effective tilt angle. As a result, we obtained highly accurate TTI moveout equations analogous with their VTI counterparts. Our analysis showed that the most accurate approximation is obtained from the mapping of generalized approximation. The new moveout approximations allow for, as the examples demonstrate, accurate description of moveout in the TTI case even for vertical heterogeneity. The proposed moveout approximations can be easily used for inversion in a layered TTI medium because the parameters of these approximations explicitly depend on corresponding effective parameters in a layered VTI medium.
Directory of Open Access Journals (Sweden)
Joel Sereno
2010-01-01
Full Text Available Inverse kinematics is the process of converting a Cartesian point in space into a set of joint angles to more efficiently move the end effector of a robot to a desired orientation. This project investigates the inverse kinematics of a robotic hand with fingers under various scenarios. Assuming the parameters of a provided robot, a general equation for the end effector point was calculated and used to plot the region of space that it can reach. Further, the benefits obtained from the addition of a prismatic joint versus an extra variable angle joint were considered. The results confirmed that having more movable parts, such as prismatic points and changing angles, increases the effective reach of a robotic hand.
International Nuclear Information System (INIS)
Desesquelles, P.
1997-01-01
Computer Monte Carlo simulations occupy an increasingly important place between theory and experiment. This paper introduces a global protocol for the comparison of model simulations with experimental results. The correlated distributions of the model parameters are determined using an original recursive inversion procedure. Multivariate analysis techniques are used in order to optimally synthesize the experimental information with a minimum number of variables. This protocol is relevant in all fields if physics dealing with event generators and multi-parametric experiments. (authors)
Diophantine approximation and badly approximable sets
DEFF Research Database (Denmark)
Kristensen, S.; Thorn, R.; Velani, S.
2006-01-01
. The classical set Bad of `badly approximable' numbers in the theory of Diophantine approximation falls within our framework as do the sets Bad(i,j) of simultaneously badly approximable numbers. Under various natural conditions we prove that the badly approximable subsets of Omega have full Hausdorff dimension...
Psychological preconditions of game activity development in the early childhood
Valeriya Spitsyna; Ekaterina Saraykina
2013-01-01
The article is devoted for detection the psychological preconditions of game activity development at early age and interrelation of game formation with the development of subject actions, informative activity and procedural game.
Association of Exercise Preconditioning With Immediate Cardioprotection: A Review.
Thijssen, D.H.J.; Redington, A.; George, K.P.; Hopman, M.T.E.; Jones, H.
2018-01-01
Importance: Exercise reduces the risk of cardiovascular events, including through an underrecognized, clinically useful form of acute cardioprotection accessible after a single episode of exercise, which is called cardiovascular preconditioning. Observations: Preclinical evidence shows that 1 to 3
Heister, Timo
2012-01-29
Efficient preconditioning for Oseen-type problems is an active research topic. We present a novel approach leveraging stabilization for inf-sup stable discretizations. The Grad-Div stabilization shares the algebraic properties with an augmented Lagrangian-type term. Both simplify the approximation of the Schur complement, especially in the convection-dominated case. We exploit this for the construction of the preconditioner. Solving the discretized Oseen problem with an iterative Krylov-type method shows that the outer iteration numbers are retained independent of mesh size, viscosity, and finite element order. Thus, the preconditioner is very competitive. © 2012 John Wiley & Sons, Ltd.
Heister, Timo; Rapin, Gerd
2012-01-01
Efficient preconditioning for Oseen-type problems is an active research topic. We present a novel approach leveraging stabilization for inf-sup stable discretizations. The Grad-Div stabilization shares the algebraic properties with an augmented Lagrangian-type term. Both simplify the approximation of the Schur complement, especially in the convection-dominated case. We exploit this for the construction of the preconditioner. Solving the discretized Oseen problem with an iterative Krylov-type method shows that the outer iteration numbers are retained independent of mesh size, viscosity, and finite element order. Thus, the preconditioner is very competitive. © 2012 John Wiley & Sons, Ltd.
Nonlinear Multiplicative Schwarz Preconditioning in Natural Convection Cavity Flow
Liu, Lulu; Zhang, Wei; Keyes, David E.
2017-01-01
A natural convection cavity flow problem is solved using nonlinear multiplicative Schwarz preconditioners, as a Gauss-Seidel-like variant of additive Schwarz preconditioned inexact Newton (ASPIN). The nonlinear preconditioning extends the domain of convergence of Newton’s method to high Rayleigh numbers. Convergence performance varies widely with respect to different groupings of the fields of this multicomponent problem, and with respect to different orderings of the groupings.
Decentralisation in developing countries: preconditions for successful implementation
Directory of Open Access Journals (Sweden)
Yasin Olum
2014-07-01
Full Text Available Decentralisation has been implemented and is being implemented in many developing countries without much success. Although several unique factors inhibit the implementation of decentralisation in individual countries, the paper argues that there are six pre-conditions that these countries should fulfill before decentralisation can be successfully implemented. These preconditions are: institutional mechanisms; creation of spaces for participation; political will and civil will; capacity development at the local level; careful implementation; and democratic governance.
Nonlinear Multiplicative Schwarz Preconditioning in Natural Convection Cavity Flow
Liu, Lulu
2017-03-17
A natural convection cavity flow problem is solved using nonlinear multiplicative Schwarz preconditioners, as a Gauss-Seidel-like variant of additive Schwarz preconditioned inexact Newton (ASPIN). The nonlinear preconditioning extends the domain of convergence of Newton’s method to high Rayleigh numbers. Convergence performance varies widely with respect to different groupings of the fields of this multicomponent problem, and with respect to different orderings of the groupings.
Ukraine Agricultural Land Market Formation Preconditions
Directory of Open Access Journals (Sweden)
Evgen Dankevych
2017-01-01
Full Text Available The theoretical land relations reforming principles were reviewed.Land relations in agriculture transformation process was studied. The land use features were detected and agricultural land use efficiency analysis was conducted.Ukraine land market formation research problems results have been shown. It was established that private land ownership institution ambiguous attitude, rent relations deformation, lack of the property rights ensure mechanism inhibit the land market development. Sociological research of Ukrainian Polesie region to determine the prerequisites for agricultural land marketformation preconditions has been conducted. 787 respondents from Zhytomyr, Rivne and Volyn regions were interviewed. Land shares owners age structure, their distribution by education level, their employment, land shares owners and agricultural enterprises executives to the agricultural land sale moratorium cancellation attitudes, land purchase financial resources, directions of Ukrainian Polissya region land shares use, shares owners land issues level of awareness have been determined during the research. Was substantiated that agricultural land market turnover includes not only land sale moratorium cancellation but also the adoption of the legislative framework and the appropriate infrastructure development, one of the key elements of which is land relations regulation specialized state agency – State Land Bank.
The protective effect of ischemic preconditioning on rat testis
Directory of Open Access Journals (Sweden)
Ciralik Harun
2007-12-01
Full Text Available Abstract Background It has been demonstrated that brief episodes of sublethal ischemia-reperfusion, so-called ischemic preconditioning, provide powerful tissue protection in different tissues such as heart, brain, skeletal muscle, lung, liver, intestine, kidney, retina, and endothelial cells. Although a recent study has claimed that there are no protective effects of ischemic preconditioning in rat testis, the protective effects of ischemic preconditioning on testicular tissue have not been investigated adequately. The present study was thus planned to investigate whether ischemic preconditioning has a protective effect on testicular tissue. Methods Rats were divided into seven groups that each contained seven rats. In group 1 (control group, only unilateral testicular ischemia was performed by creating a testicular torsion by a 720 degree clockwise rotation for 180 min. In group 2, group 3, group 4, group 5, group 6, and group 7, unilateral testicular ischemia was performed for 180 min following different periods of ischemic preconditioning. The ischemic preconditioning periods were as follows: 10 minutes of ischemia with 10 minutes of reperfusion in group 2; 20 minutes of ischemia with 10 minutes of reperfusion in group 3; 30 minutes of ischemia with 10 minutes of reperfusion in group 4; multiple preconditioning periods were used (3 × 10 min early phase transient ischemia with 10 min reperfusion in all episodes in group 5; multiple preconditioning periods were used (5, 10, and 15 min early phase transient ischemia with 10 min reperfusion in all episodes in group 6; and, multiple preconditioning periods were used (10, 20, and 30 min early phase transient ischemia with 10 min reperfusion in all episodes in group 7. After the ischemic protocols were carried out, animals were sacrificed by cervical dislocation and testicular tissue samples were taken for biochemical measurements (protein, malondialdehyde, nitric oxide and histological examination
Least-squares reverse time migration with local Radon-based preconditioning
Dutta, Gaurav
2017-03-08
Least-squares migration (LSM) can produce images with better balanced amplitudes and fewer artifacts than standard migration. The conventional objective function used for LSM minimizes the L2-norm of the data residual between the predicted and the observed data. However, for field-data applications in which the recorded data are noisy and undersampled, the conventional formulation of LSM fails to provide the desired uplift in the quality of the inverted image. We have developed a leastsquares reverse time migration (LSRTM) method using local Radon-based preconditioning to overcome the low signal-tonoise ratio (S/N) problem of noisy or severely undersampled data. A high-resolution local Radon transform of the reflectivity is used, and sparseness constraints are imposed on the inverted reflectivity in the local Radon domain. The sparseness constraint is that the inverted reflectivity is sparse in the Radon domain and each location of the subsurface is represented by a limited number of geologic dips. The forward and the inverse mapping of the reflectivity to the local Radon domain and vice versa is done through 3D Fourier-based discrete Radon transform operators. The weights for the preconditioning are chosen to be varying locally based on the relative amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard LSRTM.
Approximation methods in probability theory
Čekanavičius, Vydas
2016-01-01
This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function. Emphasising the correct usage of the methods presented, each step required for the proofs is examined in detail. As a result, this textbook provides valuable tools for proving approximation theorems. While Approximation Methods in Probability Theory will appeal to everyone interested in limit theorems of probability theory, the book is particularly aimed at graduate students who have completed a standard intermediate course in probability theory. Furthermore, experienced researchers wanting to enlarge their toolkit will also find this book useful.
Hatazaki, S; Bellver-Estelles, C; Jimenez-Mateos, E M; Meller, R; Bonner, C; Murphy, N; Matsushima, S; Taki, W; Prehn, J H M; Simon, R P; Henshall, D C
2007-12-05
A neuroprotected state can be acquired by preconditioning brain with a stimulus that is subthreshold for damage (tolerance). Acquisition of tolerance involves coordinate, bi-directional changes to gene expression levels and the re-programmed phenotype is determined by the preconditioning stimulus. While best studied in ischemic brain there is evidence brief seizures can confer tolerance against prolonged seizures (status epilepticus). Presently, we developed a model of epileptic preconditioning in mice and used microarrays to gain insight into the transcriptional phenotype within the target hippocampus at the time tolerance had been acquired. Epileptic tolerance was induced by an episode of non-damaging seizures in adult C57Bl/6 mice using a systemic injection of kainic acid. Neuron and DNA damage-positive cell counts 24 h after status epilepticus induced by intraamygdala microinjection of kainic acid revealed preconditioning given 24 h prior reduced CA3 neuronal death by approximately 45% compared with non-tolerant seizure mice. Microarray analysis of over 39,000 transcripts (Affymetrix 430 2.0 chip) from microdissected CA3 subfields was undertaken at the point at which tolerance was acquired. Results revealed a unique profile of small numbers of equivalently up- and down-regulated genes with biological functions that included transport and localization, ubiquitin metabolism, apoptosis and cell cycle control. Select microarray findings were validated post hoc by real-time polymerase chain reaction and Western blotting. The present study defines a paradigm for inducing epileptic preconditioning in mice and first insight into the global transcriptome of the seizure-damage refractory brain.
[Anaesthetic-induced myocardial preconditioning: fundamental basis and clinical implications].
Chiari, P; Bouvet, F; Piriou, V
2005-04-01
Volatile halogenated anaesthetics offer a myocardial protection when they are administrated before a myocardial ischaemia. Cellular mechanisms involved in anaesthetic preconditioning are now better understood. The objectives of this review are to understand the anaesthetic-induced preconditioning underlying mechanisms and to know the clinical implications. References were obtained from PubMed data bank (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi) using the following keywords: volatile anaesthetic, isoflurane, halothane, sevoflurane, desflurane, preconditioning, protection, myocardium. Ischaemic preconditioning (PC) is a myocardial endogenous protection against ischaemia. It has been described as one or several short ischaemia before a sustained ischemia. These short ischaemia trigger a protective signal against this longer ischaemia. An ischemic organ is able to precondition a remote organ. It is possible to replace the short ischaemia by a preadministration of halogenated volatile anaesthetic with the same protective effect, this is called anaesthetic PC (APC). APC and ischaemic PC share similar underlying biochemical mechanisms including protein kinase C, tyrosine kinase activation and mitochondrial and sarcolemnal K(ATP) channels opening. All halogenated anaesthetics can produce an anaesthetic PC effect. Myocardial protection during reperfusion, after the long ischaemia, has been shown by successive short ischaemia or volatile anaesthetic administration, this is called postconditioning. Ischaemic PC has been described in humans in 1993. Clinical studies in human cardiac surgery have shown the possibility of anaesthetic PC with volatile anaesthetics. These studies have shown a decrease of postoperative troponin in patient receiving halogenated anaesthetics.
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Operator-Based Preconditioning of Stiff Hyperbolic Systems
International Nuclear Information System (INIS)
Reynolds, Daniel R.; Samtaney, Ravi; Woodward, Carol S.
2009-01-01
We introduce an operator-based scheme for preconditioning stiff components encountered in implicit methods for hyperbolic systems of partial differential equations posed on regular grids. The method is based on a directional splitting of the implicit operator, followed by a characteristic decomposition of the resulting directional parts. This approach allows for solution to any number of characteristic components, from the entire system to only the fastest, stiffness-inducing waves. We apply the preconditioning method to stiff hyperbolic systems arising in magnetohydro- dynamics and gas dynamics. We then present numerical results showing that this preconditioning scheme works well on problems where the underlying stiffness results from the interaction of fast transient waves with slowly-evolving dynamics, scales well to large problem sizes and numbers of processors, and allows for additional customization based on the specific problems under study
The Role of Ionospheric Outflow Preconditioning in Determining Storm Geoeffectiveness
Welling, D. T.; Liemohn, M. W.; Ridley, A. J.
2012-12-01
It is now well accepted that ionospheric outflow plays an important role in the development of the plasma sheet and ring current during geomagnetic storms. Furthermore, even during quiet times, ionospheric plasma populates the magnetospheric lobes, producing a reservoir of hydrogen and oxygen ions. When the Interplanetary Magnetic Field (IMF) turns southward, this reservoir is connected to the plasma sheet and ring current through magnetospheric convection. Hence, the conditions of the ionosphere and magnetospheric lobes leading up to magnetospheric storm onset have important implications for storm development. Despite this, there has been little research on this preconditioning; most global simulations begin just before storm onset, neglecting preconditioning altogether. This work explores the role of preconditioning in determining the geoeffectiveness of storms using a coupled global model system. A model of ionospheric outflow (the Polar Wind Outflow Model, PWOM) is two-way coupled to a global magnetohydrodynamic model (the Block-Adaptive Tree Solar wind Roe-type Upwind Scheme, BATS-R-US), which in turn drives a ring current model (the Ring current Atmosphere interactions Model, RAM). This unique setup is used to simulate an idealized storm. The model is started at many different times, from 1 hour before storm onset to 12 hours before. The effects of storm preconditioning are examined by investigating the total ionospheric plasma content in the lobes just before onset, the total ionospheric contribution in the ring current just after onset, and the effects on Dst, magnetic elevation angle at geosynchronous, and total ring current energy density. This experiment is repeated for different solar activity levels as set by F10.7 flux. Finally, a synthetic double-dip storm is constructed to see how two closely spaced storms affect each other by changing the preconditioning environment. It is found that preconditioning of the magnetospheric lobes via ionospheric
Application of preconditioned conjugate gradient-like methods to reactor kinetics
International Nuclear Information System (INIS)
Yang, D.Y.; Chen, G.S.; Chou, H.P.
1993-01-01
Several conjugate gradient-like (CG-like) methods are applied to solve the nonsymmetric linear systems of equations derived from the time-dependent two-dimensional two-energy-group neutron diffusion equations by a finite difference approximation. The methods are: the generalized conjugate residual method; the generalized conjugate gradient least-square method; the generalized minimal residual method (GMRES); the conjugate gradient square method; and a variant of bi-conjugate gradient method (Bi-CGSTAB). In order to accelerate these methods, six preconditioning techniques are investigated. Two are based on pointwise incomplete factorization: the incomplete LU (ILU) and the modified incomplete LU (MILU) decompositions; two, based on the block tridiagonal structure of the coefficient matrix, are blockwise and modified blockwise incomplete factorizations, BILU and MBILU; two are the alternating-direction implicit and symmetric successive overrelaxation (SSOR) preconditioners, derived from the basic iterative schemes. Comparisons are made by using CG-like methods combined with different preconditioners to solve a sequence of time-step reactor transient problems. Numerical tests indicate that preconditioned BI-CGSTAB with the preconditioner MBILU requires less CPU time and fewer iterations than other methods. The preconditioned CG-like methods are less sensitive to the time-step size used than the Chebyshev semi-iteration method and line SOR method. The indication is that the CGS, Bi-CGSTAB and GMRES methods are, on average, better than the other methods in reactor kinetics computation and that a good preconditioner is more important than the choice of CG-like methods. The MILU decomposition based on the conventional row-sum criterion has difficulty yielding a convergent solution and an improved version is introduced. (author)
Fourier analysis of finite element preconditioned collocation schemes
Deville, Michel O.; Mund, Ernest H.
1990-01-01
The spectrum of the iteration operator of some finite element preconditioned Fourier collocation schemes is investigated. The first part of the paper analyses one-dimensional elliptic and hyperbolic model problems and the advection-diffusion equation. Analytical expressions of the eigenvalues are obtained with use of symbolic computation. The second part of the paper considers the set of one-dimensional differential equations resulting from Fourier analysis (in the tranverse direction) of the 2-D Stokes problem. All results agree with previous conclusions on the numerical efficiency of finite element preconditioning schemes.
Effects of ketamine and its isomers on ischemic preconditioning in the isolated rat heart
Molojavyi, A.; Preckel, B.; Comfère, T.; Müllenheim, J.; Thämer, V.; Schlack, W.
2001-01-01
BACKGROUND: Ischemic preconditioning protects the heart against subsequent ischemia. Opening of the adenosine triphosphate-sensitive potassium (KATP) channel is a key mechanism of preconditioning. Ketamine blocks KATP channels of isolated cardiomyocytes. The authors investigated the effects of
40 CFR 86.132-00 - Vehicle preconditioning.
2010-07-01
... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Vehicle preconditioning. 86.132-00... (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES Emission Regulations for 1977 and Later Model Year New Light-Duty Vehicles and New Light-Duty Trucks and New Otto-Cycle Complete...
40 CFR 86.232-94 - Vehicle preconditioning.
2010-07-01
... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Vehicle preconditioning. 86.232-94... (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES Emission Regulations for 1994 and Later Model Year Gasoline-Fueled New Light-Duty Vehicles, New Light-Duty Trucks and New Medium...
Preconditioned stochastic gradient descent optimisation for monomodal image registration
Klein, S.; Staring, M.; Andersson, J.P.; Pluim, J.P.W.; Fichtinger, G.; Martel, A.; Peters, T.
2011-01-01
We present a stochastic optimisation method for intensity-based monomodal image registration. The method is based on a Robbins-Monro stochastic gradient descent method with adaptive step size estimation, and adds a preconditioning matrix. The derivation of the pre-conditioner is based on the
Manipulation in political stock markets: Preconditions and evidence
Hansen, Jan; Schmidt, Carsten; Strobel, Martin
2001-01-01
Political stock markets (PSM) are sometimes seen as substitutes for opinion polls. On the bases of a behavioral model, specific preconditions were drawn out under which manipulation in PSM can weaken this argument. Evidence for manipulation is reported from the data of two separate PSM during the Berlin 99 state elections.
Preconditions of origin, essence and assignment of strategic managerial accounting
Boiko, I.
2010-01-01
The article is devoted to the research of preconditions and necessity of creation strategic managerial accounting in the accounting system of enterprise. There are investigated economic essence and assignment of strategic managerial accounting and substantiated its importance for making strategic decisions on an enterprise.
New preconditioned conjugate gradient algorithms for nonlinear unconstrained optimization problems
International Nuclear Information System (INIS)
Al-Bayati, A.; Al-Asadi, N.
1997-01-01
This paper presents two new predilection conjugate gradient algorithms for nonlinear unconstrained optimization problems and examines their computational performance. Computational experience shows that the new proposed algorithms generally imp lone the efficiency of Nazareth's [13] preconditioned conjugate gradient algorithm. (authors). 16 refs., 1 tab
Deflation in preconditioned conjugate gradient methods for Finite Element Problems
Vermolen, F.J.; Vuik, C.; Segal, A.
2002-01-01
We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods applied to a Finite Element discretization for an elliptic equation. Our set-up is a Poisson problem in two dimensions with continuous or discontinuous
Accurate reanalysis of structures by a preconditioned conjugate gradient method
Czech Academy of Sciences Publication Activity Database
Kirsch, U.; Kočvara, Michal; Zowe, J.
2002-01-01
Roč. 55, č. 2 (2002), s. 233-251 ISSN 0029-5981 R&D Projects: GA AV ČR IAA1075005 Grant - others:BMBF(DE) 03ZOM3ER Institutional research plan: CEZ:AV0Z1075907 Keywords : preconditioned conjugate gradient s * structural reanalysis Subject RIV: BA - General Mathematics Impact factor: 1.468, year: 2002
The Inverse of Banded Matrices
2013-01-01
indexed entries all zeros. In this paper, generalizing a method of Mallik (1999) [5], we give the LU factorization and the inverse of the matrix Br,n (if it...r ≤ i ≤ r, 1 ≤ j ≤ r, with the remaining un-indexed entries all zeros. In this paper generalizing a method of Mallik (1999) [5...matrices and applications to piecewise cubic approximation, J. Comput. Appl. Math. 8 (4) (1982) 285–288. [5] R.K. Mallik , The inverse of a lower
Priming of the Cells: Hypoxic Preconditioning for Stem Cell Therapy.
Wei, Zheng Z; Zhu, Yan-Bing; Zhang, James Y; McCrary, Myles R; Wang, Song; Zhang, Yong-Bo; Yu, Shan-Ping; Wei, Ling
2017-10-05
Stem cell-based therapies are promising in regenerative medicine for protecting and repairing damaged brain tissues after injury or in the context of chronic diseases. Hypoxia can induce physiological and pathological responses. A hypoxic insult might act as a double-edged sword, it induces cell death and brain damage, but on the other hand, sublethal hypoxia can trigger an adaptation response called hypoxic preconditioning or hypoxic tolerance that is of immense importance for the survival of cells and tissues. This review was based on articles published in PubMed databases up to August 16, 2017, with the following keywords: "stem cells," "hypoxic preconditioning," "ischemic preconditioning," and "cell transplantation." Original articles and critical reviews on the topics were selected. Hypoxic preconditioning has been investigated as a primary endogenous protective mechanism and possible treatment against ischemic injuries. Many cellular and molecular mechanisms underlying the protective effects of hypoxic preconditioning have been identified. In cell transplantation therapy, hypoxic pretreatment of stem cells and neural progenitors markedly increases the survival and regenerative capabilities of these cells in the host environment, leading to enhanced therapeutic effects in various disease models. Regenerative treatments can mobilize endogenous stem cells for neurogenesis and angiogenesis in the adult brain. Furthermore, transplantation of stem cells/neural progenitors achieves therapeutic benefits via cell replacement and/or increased trophic support. Combinatorial approaches of cell-based therapy with additional strategies such as neuroprotective protocols, anti-inflammatory treatment, and rehabilitation therapy can significantly improve therapeutic benefits. In this review, we will discuss the recent progress regarding cell types and applications in regenerative medicine as well as future applications.
Blokhin, I O; Galagudza, M M; Vlasov, T D; Nifontov, E M; Petrishchev, N N
2008-07-01
Traditionally infarction size reduction by ischemic preconditioning is estimated in duration of test ischemia. This approach limits the understanding of real antiischemic efficacy of ischemic preconditioning. Present study was performed in the in vivo rat model of regional myocardial ischemia-reperfusion and showed that protective effect afforded by ischemic preconditioning progressively decreased with prolongation of test ischemia. There were no statistically significant differences in infarction size between control and preconditioned animals when the duration of test ischemia was increased up to 1 hour. Preconditioning ensured maximal infarction-limiting effect in duration of test ischemia varying from 20 to 40 minutes.
International Nuclear Information System (INIS)
Ginsburg, C.A.
1980-01-01
In many problems, a desired property A of a function f(x) is determined by the behaviour of f(x) approximately equal to g(x,A) as x→xsup(*). In this letter, a method for resuming the power series in x of f(x) and approximating A (modulated Pade approximant) is presented. This new approximant is an extension of a resumation method for f(x) in terms of rational functions. (author)
Approximation Properties of Certain Summation Integral Type Operators
Directory of Open Access Journals (Sweden)
Patel P.
2015-03-01
Full Text Available In the present paper, we study approximation properties of a family of linear positive operators and establish direct results, asymptotic formula, rate of convergence, weighted approximation theorem, inverse theorem and better approximation for this family of linear positive operators.
Inverse problems of geophysics
International Nuclear Information System (INIS)
Yanovskaya, T.B.
2003-07-01
This report gives an overview and the mathematical formulation of geophysical inverse problems. General principles of statistical estimation are explained. The maximum likelihood and least square fit methods, the Backus-Gilbert method and general approaches for solving inverse problems are discussed. General formulations of linearized inverse problems, singular value decomposition and properties of pseudo-inverse solutions are given
Sparse approximation with bases
2015-01-01
This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications. The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...
Desiccant-Based Preconditioning Market Analysis
Energy Technology Data Exchange (ETDEWEB)
Fischer, J.
2001-01-11
A number of important conclusions can be drawn as a result of this broad, first-phase market evaluation. The more important conclusions include the following: (1) A very significant market opportunity will exist for specialized outdoor air-handling units (SOAHUs) as more construction and renovation projects are designed to incorporate the recommendations made by the ASHRAE 62-1989 standard. Based on this investigation, the total potential market is currently $725,000,000 annually (see Table 6, Sect. 3). Based on the market evaluations completed, it is estimated that approximately $398,000,000 (55%) of this total market could be served by DBC systems if they were made cost-effective through mass production. Approximately $306,000,000 (42%) of the total can be served by a non-regenerated, desiccant-based total recovery approach, based on the information provided by this investigation. Approximately $92,000,000 (13%) can be served by a regenerated desiccant-based cooling approach (see Table 7, Sect. 3). (2) A projection of the market selling price of various desiccant-based SOAHU systems was prepared using prices provided by Trane for central-station, air-handling modules currently manufactured. The wheel-component pricing was added to these components by SEMCO. This resulted in projected pricing for these systems that is significantly less than that currently offered by custom suppliers (see Table 4, Sect. 2). Estimated payback periods for all SOAHU approaches were quite short when compared with conventional over-cooling and reheat systems. Actual paybacks may vary significantly depending on site-specific considerations. (3) In comparing cost vs benefit of each SOAHU approach, it is critical that the total system design be evaluated. For example, the cost premium of a DBC system is very significant when compared to a conventional air handling system, yet the reduced chiller, boiler, cooling tower, and other expense often equals or exceeds this premium, resulting in a
Approximate symmetries of Hamiltonians
Chubb, Christopher T.; Flammia, Steven T.
2017-08-01
We explore the relationship between approximate symmetries of a gapped Hamiltonian and the structure of its ground space. We start by considering approximate symmetry operators, defined as unitary operators whose commutators with the Hamiltonian have norms that are sufficiently small. We show that when approximate symmetry operators can be restricted to the ground space while approximately preserving certain mutual commutation relations. We generalize the Stone-von Neumann theorem to matrices that approximately satisfy the canonical (Heisenberg-Weyl-type) commutation relations and use this to show that approximate symmetry operators can certify the degeneracy of the ground space even though they only approximately form a group. Importantly, the notions of "approximate" and "small" are all independent of the dimension of the ambient Hilbert space and depend only on the degeneracy in the ground space. Our analysis additionally holds for any gapped band of sufficiently small width in the excited spectrum of the Hamiltonian, and we discuss applications of these ideas to topological quantum phases of matter and topological quantum error correcting codes. Finally, in our analysis, we also provide an exponential improvement upon bounds concerning the existence of shared approximate eigenvectors of approximately commuting operators under an added normality constraint, which may be of independent interest.
Inverse problem in nuclear physics
International Nuclear Information System (INIS)
Zakhariev, B.N.
1976-01-01
The method of reconstruction of interaction from the scattering data is formulated in the frame of the R-matrix theory in which the potential is determined by position of resonance Esub(lambda) and their reduced widths γ 2 lambda. In finite difference approximation for the Schroedinger equation this new approach allows to make the logics of the inverse problem IP more clear. A possibility of applications of IP formalism to various nuclear systems is discussed. (author)
Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng
2013-04-01
This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a
HMC algorithm with multiple time scale integration and mass preconditioning
Urbach, C.; Jansen, K.; Shindler, A.; Wenger, U.
2006-01-01
We present a variant of the HMC algorithm with mass preconditioning (Hasenbusch acceleration) and multiple time scale integration. We have tested this variant for standard Wilson fermions at β=5.6 and at pion masses ranging from 380 to 680 MeV. We show that in this situation its performance is comparable to the recently proposed HMC variant with domain decomposition as preconditioner. We give an update of the "Berlin Wall" figure, comparing the performance of our variant of the HMC algorithm to other published performance data. Advantages of the HMC algorithm with mass preconditioning and multiple time scale integration are that it is straightforward to implement and can be used in combination with a wide variety of lattice Dirac operators.
Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.
Yang, Qiang; Vogel, Curtis R; Ellerbroek, Brent L
2006-07-20
By 'atmospheric tomography' we mean the estimation of a layered atmospheric turbulence profile from measurements of the pupil-plane phase (or phase gradients) corresponding to several different guide star directions. We introduce what we believe to be a new Fourier domain preconditioned conjugate gradient (FD-PCG) algorithm for atmospheric tomography, and we compare its performance against an existing multigrid preconditioned conjugate gradient (MG-PCG) approach. Numerical results indicate that on conventional serial computers, FD-PCG is as accurate and robust as MG-PCG, but it is from one to two orders of magnitude faster for atmospheric tomography on 30 m class telescopes. Simulations are carried out for both natural guide stars and for a combination of finite-altitude laser guide stars and natural guide stars to resolve tip-tilt uncertainty.
PRECONDITIONS AND DETERMINING CAUSES OF THE SHADOW ECONOMY IN UKRAINE
Directory of Open Access Journals (Sweden)
Z. Varnalii
2014-03-01
Full Text Available The article analyzes the main processes that led to the high level of the economy shadowing. The historical aspects of the formation of the shadow economy in Ukraine are highlighted. The socio-economic aspects of the shadow economy of Ukraine causality are discussed. The theoretical contribution of foreign and domestic researchers on the preconditions of formation of the shadow economy in transition economies is studied. Theoretical perspective on the factors of the shadowing processes in the economy of Ukraine from the standpoint of modern scientific researches is analyzed. The paper also provides scientific vectors for further development of researches aimed at studying the causes and preconditions of the shadow economy.
Combined incomplete LU and strongly implicit procedure preconditioning
Energy Technology Data Exchange (ETDEWEB)
Meese, E.A. [Univ. of Trondheim (Norway)
1996-12-31
For the solution of large sparse linear systems of equations, the Krylov-subspace methods have gained great merit. Their efficiency are, however, largely dependent upon preconditioning of the equation-system. A family of matrix factorisations often used for preconditioning, is obtained from a truncated Gaussian elimination, ILU(p). Less common, supposedly due to it`s restriction to certain sparsity patterns, is factorisations generated by the strongly implicit procedure (SIP). The ideas from ILU(p) and SIP are used in this paper to construct a generalized strongly implicit procedure, applicable to matrices with any sparsity pattern. The new algorithm has been run on some test equations, and efficiency improvements over ILU(p) was found.
Approximating distributions from moments
Pawula, R. F.
1987-11-01
A method based upon Pearson-type approximations from statistics is developed for approximating a symmetric probability density function from its moments. The extended Fokker-Planck equation for non-Markov processes is shown to be the underlying foundation for the approximations. The approximation is shown to be exact for the beta probability density function. The applicability of the general method is illustrated by numerous pithy examples from linear and nonlinear filtering of both Markov and non-Markov dichotomous noise. New approximations are given for the probability density function in two cases in which exact solutions are unavailable, those of (i) the filter-limiter-filter problem and (ii) second-order Butterworth filtering of the random telegraph signal. The approximate results are compared with previously published Monte Carlo simulations in these two cases.
Remote Ischemic Preconditioning and Outcomes of Cardiac Surgery.
Hausenloy, DJ; Candilio, L; Evans, R; Ariti, C; Jenkins, DP; Kolvekar, S; Knight, R; Kunst, G; Laing, C; Nicholas, J; Pepper, J; Robertson, S; Xenou, M; Clayton, T; Yellon, DM
2015-01-01
: Whether remote ischemic preconditioning (transient ischemia and reperfusion of the arm) can improve clinical outcomes in patients undergoing coronary-artery bypass graft (CABG) surgery is not known. We investigated this question in a randomized trial. : We conducted a multicenter, sham-controlled trial involving adults at increased surgical risk who were undergoing on-pump CABG (with or without valve surgery) with blood cardioplegia. After anesthesia induction and before surgical incision, ...
Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm
Liu, Lulu
2016-10-26
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.
Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm
Liu, Lulu; Keyes, David E.
2016-01-01
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.
Krylov Subspace Methods for Saddle Point Problems with Indefinite Preconditioning
Czech Academy of Sciences Publication Activity Database
Rozložník, Miroslav; Simoncini, V.
2002-01-01
Roč. 24, č. 2 (2002), s. 368-391 ISSN 0895-4798 R&D Projects: GA ČR GA101/00/1035; GA ČR GA201/00/0080 Institutional research plan: AV0Z1030915 Keywords : saddle point problems * preconditioning * indefinite linear systems * finite precision arithmetic * conjugate gradients Subject RIV: BA - General Mathematics Impact factor: 0.753, year: 2002
Ischemic preconditioning enhances integrity of coronary endothelial tight junctions
International Nuclear Information System (INIS)
Li, Zhao; Jin, Zhu-Qiu
2012-01-01
Highlights: ► Cardiac tight junctions are present between coronary endothelial cells. ► Ischemic preconditioning preserves the structural and functional integrity of tight junctions. ► Myocardial edema is prevented in hearts subjected to ischemic preconditioning. ► Ischemic preconditioning enhances translocation of ZO-2 from cytosol to cytoskeleton. -- Abstract: Ischemic preconditioning (IPC) is one of the most effective procedures known to protect hearts against ischemia/reperfusion (IR) injury. Tight junction (TJ) barriers occur between coronary endothelial cells. TJs provide barrier function to maintain the homeostasis of the inner environment of tissues. However, the effect of IPC on the structure and function of cardiac TJs remains unknown. We tested the hypothesis that myocardial IR injury ruptures the structure of TJs and impairs endothelial permeability whereas IPC preserves the structural and functional integrity of TJs in the blood–heart barrier. Langendorff hearts from C57BL/6J mice were prepared and perfused with Krebs–Henseleit buffer. Cardiac function, creatine kinase release, and myocardial edema were measured. Cardiac TJ function was evaluated by measuring Evans blue-conjugated albumin (EBA) content in the extravascular compartment of hearts. Expression and translocation of zonula occludens (ZO)-2 in IR and IPC hearts were detected with Western blot. A subset of hearts was processed for the observation of ultra-structure of cardiac TJs with transmission electron microscopy. There were clear TJs between coronary endothelial cells of mouse hearts. IR caused the collapse of TJs whereas IPC sustained the structure of TJs. IR increased extravascular EBA content in the heart and myocardial edema but decreased the expression of ZO-2 in the cytoskeleton. IPC maintained the structure of TJs. Cardiac EBA content and edema were reduced in IPC hearts. IPC enhanced the translocation of ZO-2 from cytosol to cytoskeleton. In conclusion, TJs occur in
Efficient Preconditioning of Sequences of Nonsymmetric Linear Systems
Czech Academy of Sciences Publication Activity Database
Duintjer Tebbens, Jurjen; Tůma, Miroslav
2007-01-01
Roč. 29, č. 5 (2007), s. 1918-1941 ISSN 1064-8275 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB100300703 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned iterative methods * sparse matrices * sequences of linear algebraic systems * incomplete factorizations * factorization updates * Gauss–Jordan transformations * minimum spanning tree Subject RIV: BA - General Mathematics Impact factor: 1.784, year: 2007
Unified analysis of preconditioning methods for saddle point matrices
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe
2015-01-01
Roč. 22, č. 2 (2015), s. 233-253 ISSN 1070-5325 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : saddle point problems * preconditioning * spectral properties Subject RIV: BA - General Mathematics Impact factor: 1.431, year: 2015 http://onlinelibrary.wiley.com/doi/10.1002/nla.1947/pdf
CONTRIBUTIONS TO RATIONAL APPROXIMATION,
Some of the key results of linear Chebyshev approximation theory are extended to generalized rational functions. Prominent among these is Haar’s...linear theorem which yields necessary and sufficient conditions for uniqueness. Some new results in the classic field of rational function Chebyshev...Furthermore a Weierstrass type theorem is proven for rational Chebyshev approximation. A characterization theorem for rational trigonometric Chebyshev approximation in terms of sign alternation is developed. (Author)
Approximation techniques for engineers
Komzsik, Louis
2006-01-01
Presenting numerous examples, algorithms, and industrial applications, Approximation Techniques for Engineers is your complete guide to the major techniques used in modern engineering practice. Whether you need approximations for discrete data of continuous functions, or you''re looking for approximate solutions to engineering problems, everything you need is nestled between the covers of this book. Now you can benefit from Louis Komzsik''s years of industrial experience to gain a working knowledge of a vast array of approximation techniques through this complete and self-contained resource.
Remote ischaemic preconditioning and prevention of cerebral injury.
Rehni, Ashish K; Shri, Richa; Singh, Manjeet
2007-03-01
Bilateral carotid artery occlusion of 10 min followed by reperfusion for 24 hr was employed in present study to produce ischaemia and reperfusion induced cerebral injury in mice. Cerebral infarct size was measured using triphenyltetrazolium chloride staining. Short-term memory was evaluated using elevated plus maze. Inclined beam walking test was employed to assess motor incoordination. Bilateral carotid artery occlusion followed by reperfusion produced cerebral infarction and impaired short-term memory, motor co-ordination and lateral push response. A preceding episode of mesenteric artery occlusion for 15 min and reperfusion of 15 min (remote mesenteric ischaemic preconditioning) prevented markedly ischaemia-reperfusion-induced cerebral injury measured in terms of infarct size, loss of short-term memory, motor coordination and lateral push response. Glibenclamide (5 mg/kg, iv) a KATP channel blocker and caffeine (7 mg/kg, iv) an adenosine receptor blocker attenuated the neuroprotective effect of remote mesenteric ischaemic preconditioning. It may be concluded that neuroprotective effect of remote mesenteric ischaemic preconditioning may be due to activation of adenosine receptors and consequent activation of KATP channels in mice.
Preconditioned conjugate gradient methods for the Navier-Stokes equations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1994-01-01
A preconditioned Krylov subspace method (GMRES) is used to solve the linear systems of equations formed at each time-integration step of the unsteady, two-dimensional, compressible Navier-Stokes equations of fluid flow. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux-split formulation. Several preconditioning techniques are investigated to enhance the efficiency and convergence rate of the implicit solver based on the GMRES algorithm. The superiority of the new solver is established by comparisons with a conventional implicit solver, namely line Gauss-Seidel relaxation (LGSR). Computational test results for low-speed (incompressible flow over a backward-facing step at Mach 0.1), transonic flow (trailing edge flow in a transonic turbine cascade), and hypersonic flow (shock-on-shock interactions on a cylindrical leading edge at Mach 6.0) are presented. For the Mach 0.1 case, overall speedup factors of up to 17 (in terms of time-steps) and 15 (in terms of CPU time on a CRAY-YMP/8) are found in favor of the preconditioned GMRES solver, when compared with the LGSR solver. The corresponding speedup factors for the transonic flow case are 17 and 23, respectively. The hypersonic flow case shows slightly lower speedup factors of 9 and 13, respectively. The study of preconditioners conducted in this research reveals that a new LUSGS-type preconditioner is much more efficient than a conventional incomplete LU-type preconditioner.
Expectation Consistent Approximate Inference
DEFF Research Database (Denmark)
Opper, Manfred; Winther, Ole
2005-01-01
We propose a novel framework for approximations to intractable probabilistic models which is based on a free energy formulation. The approximation can be understood from replacing an average over the original intractable distribution with a tractable one. It requires two tractable probability dis...
Ordered cones and approximation
Keimel, Klaus
1992-01-01
This book presents a unified approach to Korovkin-type approximation theorems. It includes classical material on the approximation of real-valuedfunctions as well as recent and new results on set-valued functions and stochastic processes, and on weighted approximation. The results are notonly of qualitative nature, but include quantitative bounds on the order of approximation. The book is addressed to researchers in functional analysis and approximation theory as well as to those that want to applythese methods in other fields. It is largely self- contained, but the readershould have a solid background in abstract functional analysis. The unified approach is based on a new notion of locally convex ordered cones that are not embeddable in vector spaces but allow Hahn-Banach type separation and extension theorems. This concept seems to be of independent interest.
A Joint Method of Envelope Inversion Combined with Hybrid-domain Full Waveform Inversion
CUI, C.; Hou, W.
2017-12-01
Full waveform inversion (FWI) aims to construct high-precision subsurface models by fully using the information in seismic records, including amplitude, travel time, phase and so on. However, high non-linearity and the absence of low frequency information in seismic data lead to the well-known cycle skipping problem and make inversion easily fall into local minima. In addition, those 3D inversion methods that are based on acoustic approximation ignore the elastic effects in real seismic field, and make inversion harder. As a result, the accuracy of final inversion results highly relies on the quality of initial model. In order to improve stability and quality of inversion results, multi-scale inversion that reconstructs subsurface model from low to high frequency are applied. But, the absence of very low frequencies (time domain and inversion in the frequency domain. To accelerate the inversion, we adopt CPU/GPU heterogeneous computing techniques. There were two levels of parallelism. In the first level, the inversion tasks are decomposed and assigned to each computation node by shot number. In the second level, GPU multithreaded programming is used for the computation tasks in each node, including forward modeling, envelope extraction, DFT (discrete Fourier transform) calculation and gradients calculation. Numerical tests demonstrated that the combined envelope inversion + hybrid-domain FWI could obtain much faithful and accurate result than conventional hybrid-domain FWI. The CPU/GPU heterogeneous parallel computation could improve the performance speed.
Approximate and renormgroup symmetries
Energy Technology Data Exchange (ETDEWEB)
Ibragimov, Nail H. [Blekinge Institute of Technology, Karlskrona (Sweden). Dept. of Mathematics Science; Kovalev, Vladimir F. [Russian Academy of Sciences, Moscow (Russian Federation). Inst. of Mathematical Modeling
2009-07-01
''Approximate and Renormgroup Symmetries'' deals with approximate transformation groups, symmetries of integro-differential equations and renormgroup symmetries. It includes a concise and self-contained introduction to basic concepts and methods of Lie group analysis, and provides an easy-to-follow introduction to the theory of approximate transformation groups and symmetries of integro-differential equations. The book is designed for specialists in nonlinear physics - mathematicians and non-mathematicians - interested in methods of applied group analysis for investigating nonlinear problems in physical science and engineering. (orig.)
Approximate and renormgroup symmetries
International Nuclear Information System (INIS)
Ibragimov, Nail H.; Kovalev, Vladimir F.
2009-01-01
''Approximate and Renormgroup Symmetries'' deals with approximate transformation groups, symmetries of integro-differential equations and renormgroup symmetries. It includes a concise and self-contained introduction to basic concepts and methods of Lie group analysis, and provides an easy-to-follow introduction to the theory of approximate transformation groups and symmetries of integro-differential equations. The book is designed for specialists in nonlinear physics - mathematicians and non-mathematicians - interested in methods of applied group analysis for investigating nonlinear problems in physical science and engineering. (orig.)
Approximations of Fuzzy Systems
Directory of Open Access Journals (Sweden)
Vinai K. Singh
2013-03-01
Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions
Potvin, Guy
2015-10-01
We examine how the Rytov approximation describing log-amplitude and phase fluctuations of a wave propagating through weak uniform turbulence can be generalized to the case of turbulence with a large-scale nonuniform component. We show how the large-scale refractive index field creates Fermat rays using the path integral formulation for paraxial propagation. We then show how the second-order derivatives of the Fermat ray action affect the Rytov approximation, and we discuss how a numerical algorithm would model the general Rytov approximation.
Geometric approximation algorithms
Har-Peled, Sariel
2011-01-01
Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises. Close to 200 color figures are included in the text to illustrate proofs and ideas.
International Nuclear Information System (INIS)
Knobloch, A.F.
1980-01-01
A simplified cost approximation for INTOR parameter sets in a narrow parameter range is shown. Plausible constraints permit the evaluation of the consequences of parameter variations on overall cost. (orig.) [de
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Gautschi, Walter; Rassias, Themistocles M
2011-01-01
Approximation theory and numerical analysis are central to the creation of accurate computer simulations and mathematical models. Research in these areas can influence the computational techniques used in a variety of mathematical and computational sciences. This collection of contributed chapters, dedicated to renowned mathematician Gradimir V. Milovanovia, represent the recent work of experts in the fields of approximation theory and numerical analysis. These invited contributions describe new trends in these important areas of research including theoretic developments, new computational alg
International Nuclear Information System (INIS)
Wang Shuxia
2001-01-01
Ischemic preconditioning is the intrinsic and most potently myocardial protection. Its mechanism is the foundation of rational therapeutic application. Nowadays there are some theories about delayed phase of preconditioning such as nitric oxide hypothesis, free radical mechanisms, protective protein synthesis and opening of ATP-sensitive potassium channels. By incorporation 3 H-leucine, using liquid scintillation counter, the authors know there was protective protein synthesis during preconditioning. SPECT could study the characteristics of preconditioned myocardium in vivo, and PET might further show the metabolism, energy consumption and its relationship to myocardium dysfunction
Preconditioned iterative methods for space-time fractional advection-diffusion equations
Zhao, Zhi; Jin, Xiao-Qing; Lin, Matthew M.
2016-08-01
In this paper, we propose practical numerical methods for solving a class of initial-boundary value problems of space-time fractional advection-diffusion equations. First, we propose an implicit method based on two-sided Grünwald formulae and discuss its stability and consistency. Then, we develop the preconditioned generalized minimal residual (preconditioned GMRES) method and preconditioned conjugate gradient normal residual (preconditioned CGNR) method with easily constructed preconditioners. Importantly, because resulting systems are Toeplitz-like, fast Fourier transform can be applied to significantly reduce the computational cost. We perform numerical experiments to demonstrate the efficiency of our preconditioners, even in cases with variable coefficients.
Approximate kernel competitive learning.
Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang
2015-03-01
Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.
Wave-equation dispersion inversion
Li, Jing
2016-12-08
We present the theory for wave-equation inversion of dispersion curves, where the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. The dispersion curves are obtained from Rayleigh waves recorded by vertical-component geophones. Similar to wave-equation traveltime tomography, the complicated surface wave arrivals in traces are skeletonized as simpler data, namely the picked dispersion curves in the phase-velocity and frequency domains. Solutions to the elastic wave equation and an iterative optimization method are then used to invert these curves for 2-D or 3-D S-wave velocity models. This procedure, denoted as wave-equation dispersion inversion (WD), does not require the assumption of a layered model and is significantly less prone to the cycle-skipping problems of full waveform inversion. The synthetic and field data examples demonstrate that WD can approximately reconstruct the S-wave velocity distributions in laterally heterogeneous media if the dispersion curves can be identified and picked. The WD method is easily extended to anisotropic data and the inversion of dispersion curves associated with Love waves.
Perturbation expansions generated by an approximate propagator
International Nuclear Information System (INIS)
Znojil, M.
1987-01-01
Starting from a knowledge of an approximate propagator R at some trial energy guess E 0 , a new perturbative prescription for p-plet of bound states and of their energies is proposed. It generalizes the Rayleigh-Schroedinger (RS) degenerate perturbation theory to the nondiagonal operators R (eliminates a RS need of their diagnolisation) and defines an approximate Hamiltonian T by mere inversion. The deviation V of T from the exact Hamiltonian H is assumed small only after a substraction of a further auxiliary Hartree-Fock-like separable ''selfconsistent'' potential U of rank p. The convergence is illustrated numerically on the anharmonic oscillator example
Preconditioned Conjugate Gradient methods for low speed flow calculations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1993-01-01
An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations are integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and the convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the lower-upper (L-U)-successive symmetric over-relaxation iterative scheme is more efficient than a preconditioner based on incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional line Gauss-Seidel relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.
Preconditioned alternating projection algorithms for maximum a posteriori ECT reconstruction
International Nuclear Information System (INIS)
Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng
2012-01-01
We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constraint involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the PAPA. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. (paper)
Design Considerations for a Flexible Multigrid Preconditioning Library
Directory of Open Access Journals (Sweden)
Jérémie Gaidamour
2012-01-01
Full Text Available MueLu is a library within the Trilinos software project [An overview of Trilinos, Technical Report SAND2003-2927, Sandia National Laboratories, 2003] and provides a framework for parallel multigrid preconditioning methods for large sparse linear systems. While providing efficient implementations of modern multigrid methods based on smoothed aggregation and energy minimization concepts, MueLu is designed to be customized and extended. This article gives an overview of design considerations for the MueLu package: user interfaces, internal design, data management, usage of modern software constructs, leveraging Trilinos capabilities, linear algebra operations and advanced application.
Ischemic preconditioning enhances integrity of coronary endothelial tight junctions
Energy Technology Data Exchange (ETDEWEB)
Li, Zhao [Department of Pharmaceutical Sciences, College of Pharmacy, South Dakota State University, Brookings, SD 57007 (United States); Jin, Zhu-Qiu, E-mail: zhu-qiu.jin@sdstate.edu [Department of Pharmaceutical Sciences, College of Pharmacy, South Dakota State University, Brookings, SD 57007 (United States)
2012-08-31
Highlights: Black-Right-Pointing-Pointer Cardiac tight junctions are present between coronary endothelial cells. Black-Right-Pointing-Pointer Ischemic preconditioning preserves the structural and functional integrity of tight junctions. Black-Right-Pointing-Pointer Myocardial edema is prevented in hearts subjected to ischemic preconditioning. Black-Right-Pointing-Pointer Ischemic preconditioning enhances translocation of ZO-2 from cytosol to cytoskeleton. -- Abstract: Ischemic preconditioning (IPC) is one of the most effective procedures known to protect hearts against ischemia/reperfusion (IR) injury. Tight junction (TJ) barriers occur between coronary endothelial cells. TJs provide barrier function to maintain the homeostasis of the inner environment of tissues. However, the effect of IPC on the structure and function of cardiac TJs remains unknown. We tested the hypothesis that myocardial IR injury ruptures the structure of TJs and impairs endothelial permeability whereas IPC preserves the structural and functional integrity of TJs in the blood-heart barrier. Langendorff hearts from C57BL/6J mice were prepared and perfused with Krebs-Henseleit buffer. Cardiac function, creatine kinase release, and myocardial edema were measured. Cardiac TJ function was evaluated by measuring Evans blue-conjugated albumin (EBA) content in the extravascular compartment of hearts. Expression and translocation of zonula occludens (ZO)-2 in IR and IPC hearts were detected with Western blot. A subset of hearts was processed for the observation of ultra-structure of cardiac TJs with transmission electron microscopy. There were clear TJs between coronary endothelial cells of mouse hearts. IR caused the collapse of TJs whereas IPC sustained the structure of TJs. IR increased extravascular EBA content in the heart and myocardial edema but decreased the expression of ZO-2 in the cytoskeleton. IPC maintained the structure of TJs. Cardiac EBA content and edema were reduced in IPC hearts. IPC
Parallel preconditioned conjugate gradient algorithm applied to neutron diffusion problem
International Nuclear Information System (INIS)
Majumdar, A.; Martin, W.R.
1992-01-01
Numerical solution of the neutron diffusion problem requires solving a linear system of equations such as Ax = b, where A is an n x n symmetric positive definite (SPD) matrix; x and b are vectors with n components. The preconditioned conjugate gradient (PCG) algorithm is an efficient iterative method for solving such a linear system of equations. In this paper, the authors describe the implementation of a parallel PCG algorithm on a shared memory machine (BBN TC2000) and on a distributed workstation (IBM RS6000) environment created by the parallel virtual machine parallelization software
Weighted graph based ordering techniques for preconditioned conjugate gradient methods
Clift, Simon S.; Tang, Wei-Pai
1994-01-01
We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.
International Nuclear Information System (INIS)
Chiueh, C.C.; Andoh, Tsugunobu; Chock, P. Boon
2005-01-01
Hormesis, a stress tolerance, can be induced by ischemic preconditioning stress. In addition to preconditioning, it may be induced by other means, such as gas anesthetics. Preconditioning mechanisms, which may be mediated by reprogramming survival genes and proteins, are obscure. A known neurotoxicant, 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), causes less neurotoxicity in the mice that are preconditioned. Pharmacological evidences suggest that the signaling pathway of ·NO-cGMP-PKG (protein kinase G) may mediate preconditioning phenomenon. We developed a human SH-SY5Y cell model for investigating · NO-mediated signaling pathway, gene regulation, and protein expression following a sublethal preconditioning stress caused by a brief 2-h serum deprivation. Preconditioned human SH-SY5Y cells are more resistant against severe oxidative stress and apoptosis caused by lethal serum deprivation and 1-mehtyl-4-phenylpyridinium (MPP + ). Both sublethal and lethal oxidative stress caused by serum withdrawal increased neuronal nitric oxide synthase (nNOS/NOS1) expression and · NO levels to a similar extent. In addition to free radical scavengers, inhibition of nNOS, guanylyl cyclase, and PKG blocks hormesis induced by preconditioning. S-nitrosothiols and 6-Br-cGMP produce a cytoprotection mimicking the action of preconditioning tolerance. There are two distinct cGMP-mediated survival pathways: (i) the up-regulation of a redox protein thioredoxin (Trx) for elevating mitochondrial levels of antioxidant protein Mn superoxide dismutase (MnSOD) and antiapoptotic protein Bcl-2, and (ii) the activation of mitochondrial ATP-sensitive potassium channels [K(ATP)]. Preconditioning induction of Trx increased tolerance against MPP + , which was blocked by Trx mRNA antisense oligonucleotide and Trx reductase inhibitor. It is concluded that Trx plays a pivotal role in · NO-dependent preconditioning hormesis against MPTP/MPP +
On Covering Approximation Subspaces
Directory of Open Access Journals (Sweden)
Xun Ge
2009-06-01
Full Text Available Let (U';C' be a subspace of a covering approximation space (U;C and X⊂U'. In this paper, we show that and B'(X⊂B(X∩U'. Also, iff (U;C has Property Multiplication. Furthermore, some connections between outer (resp. inner definable subsets in (U;C and outer (resp. inner definable subsets in (U';C' are established. These results answer a question on covering approximation subspace posed by J. Li, and are helpful to obtain further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.
Pan, Wenyong; Geng, Yu; Innanen, Kristopher A.
2018-05-01
The problem of inverting for multiple physical parameters in the subsurface using seismic full-waveform inversion (FWI) is complicated by interparameter trade-off arising from inherent ambiguities between different physical parameters. Parameter resolution is often characterized using scattering radiation patterns, but these neglect some important aspects of interparameter trade-off. More general analysis and mitigation of interparameter trade-off in isotropic-elastic FWI is possible through judiciously chosen multiparameter Hessian matrix-vector products. We show that products of multiparameter Hessian off-diagonal blocks with model perturbation vectors, referred to as interparameter contamination kernels, are central to the approach. We apply the multiparameter Hessian to various vectors designed to provide information regarding the strengths and characteristics of interparameter contamination, both locally and within the whole volume. With numerical experiments, we observe that S-wave velocity perturbations introduce strong contaminations into density and phase-reversed contaminations into P-wave velocity, but themselves experience only limited contaminations from other parameters. Based on these findings, we introduce a novel strategy to mitigate the influence of interparameter trade-off with approximate contamination kernels. Furthermore, we recommend that the local spatial and interparameter trade-off of the inverted models be quantified using extended multiparameter point spread functions (EMPSFs) obtained with pre-conditioned conjugate-gradient algorithm. Compared to traditional point spread functions, the EMPSFs appear to provide more accurate measurements for resolution analysis, by de-blurring the estimations, scaling magnitudes and mitigating interparameter contamination. Approximate eigenvalue volumes constructed with stochastic probing approach are proposed to evaluate the resolution of the inverted models within the whole model. With a synthetic
Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.
1988-11-01
Many physical problems require the solution of coupled partial differential equations on two-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES2 allows each spatial operator to have 5 or 9 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect indices which is vectorizable on some of the newer scientific computers.
On Convex Quadratic Approximation
den Hertog, D.; de Klerk, E.; Roos, J.
2000-01-01
In this paper we prove the counterintuitive result that the quadratic least squares approximation of a multivariate convex function in a finite set of points is not necessarily convex, even though it is convex for a univariate convex function. This result has many consequences both for the field of
Prestack wavefield approximations
Alkhalifah, Tariq
2013-01-01
The double-square-root (DSR) relation offers a platform to perform prestack imaging using an extended single wavefield that honors the geometrical configuration between sources, receivers, and the image point, or in other words, prestack wavefields. Extrapolating such wavefields, nevertheless, suffers from limitations. Chief among them is the singularity associated with horizontally propagating waves. I have devised highly accurate approximations free of such singularities which are highly accurate. Specifically, I use Padé expansions with denominators given by a power series that is an order lower than that of the numerator, and thus, introduce a free variable to balance the series order and normalize the singularity. For the higher-order Padé approximation, the errors are negligible. Additional simplifications, like recasting the DSR formula as a function of scattering angle, allow for a singularity free form that is useful for constant-angle-gather imaging. A dynamic form of this DSR formula can be supported by kinematic evaluations of the scattering angle to provide efficient prestack wavefield construction. Applying a similar approximation to the dip angle yields an efficient 1D wave equation with the scattering and dip angles extracted from, for example, DSR ray tracing. Application to the complex Marmousi data set demonstrates that these approximations, although they may provide less than optimal results, allow for efficient and flexible implementations. © 2013 Society of Exploration Geophysicists.
DEFF Research Database (Denmark)
Madsen, Rasmus Elsborg
2005-01-01
The Dirichlet compound multinomial (DCM), which has recently been shown to be well suited for modeling for word burstiness in documents, is here investigated. A number of conceptual explanations that account for these recent results, are provided. An exponential family approximation of the DCM...
Approximation by Cylinder Surfaces
DEFF Research Database (Denmark)
Randrup, Thomas
1997-01-01
We present a new method for approximation of a given surface by a cylinder surface. It is a constructive geometric method, leading to a monorail representation of the cylinder surface. By use of a weighted Gaussian image of the given surface, we determine a projection plane. In the orthogonal...
Prestack wavefield approximations
Alkhalifah, Tariq
2013-09-01
The double-square-root (DSR) relation offers a platform to perform prestack imaging using an extended single wavefield that honors the geometrical configuration between sources, receivers, and the image point, or in other words, prestack wavefields. Extrapolating such wavefields, nevertheless, suffers from limitations. Chief among them is the singularity associated with horizontally propagating waves. I have devised highly accurate approximations free of such singularities which are highly accurate. Specifically, I use Padé expansions with denominators given by a power series that is an order lower than that of the numerator, and thus, introduce a free variable to balance the series order and normalize the singularity. For the higher-order Padé approximation, the errors are negligible. Additional simplifications, like recasting the DSR formula as a function of scattering angle, allow for a singularity free form that is useful for constant-angle-gather imaging. A dynamic form of this DSR formula can be supported by kinematic evaluations of the scattering angle to provide efficient prestack wavefield construction. Applying a similar approximation to the dip angle yields an efficient 1D wave equation with the scattering and dip angles extracted from, for example, DSR ray tracing. Application to the complex Marmousi data set demonstrates that these approximations, although they may provide less than optimal results, allow for efficient and flexible implementations. © 2013 Society of Exploration Geophysicists.
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla
2014-07-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla; Bagci, Hakan
2014-01-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Two numerical methods for an inverse problem for the 2-D Helmholtz equation
Gryazin, Y A; Lucas, T R
2003-01-01
Two solution methods for the inverse problem for the 2-D Helmholtz equation are developed, tested, and compared. The proposed approaches are based on a marching finite-difference scheme which requires the solution of an overdetermined system at each step. The preconditioned conjugate gradient method is used for rapid solutions of these systems and an efficient preconditioner has been developed for this class of problems. Underlying target applications include the imaging of land mines, unexploded ordinance, and pollutant plumes in environmental cleanup sites, each formulated as an inverse problem for a 2-D Helmholtz equation. The images represent the electromagnetic properties of the respective underground regions. Extensive numerical results are presented.
Preconditioning 2D Integer Data for Fast Convex Hull Computations.
Cadenas, José Oswaldo; Megson, Graham M; Luengo Hendriks, Cris L
2016-01-01
In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.
Bilirubin nanoparticle preconditioning protects against hepatic ischemia-reperfusion injury.
Kim, Jin Yong; Lee, Dong Yun; Kang, Sukmo; Miao, Wenjun; Kim, Hyungjun; Lee, Yonghyun; Jon, Sangyong
2017-07-01
Hepatic ischemia-reperfusion injury (IRI) remains a major concern in liver transplantation and resection, despite continuing efforts to prevent it. Accumulating evidence suggests that bilirubin possesses antioxidant, anti-inflammatory and anti-apoptotic properties. However, despite obvious potential health benefits of bilirubin, its clinical applications are limited by its poor solubility. We recently developed bilirubin nanoparticles (BRNPs) consisting of polyethylene glycol (PEG)-conjugated bilirubin. Here, we sought to investigate whether BRNPs protect against IRI in the liver by preventing oxidative stress. BRNPs exerted potent antioxidant and anti-apoptotic activity in primary hepatocytes exposed to hydrogen peroxide, a precursor of reactive oxygen species (ROS). In a model of hepatic IRI in mice, BRNP preconditioning exerted profound protective effects against hepatocellular injury by reducing oxidative stress, pro-inflammatory cytokine production, and recruitment of neutrophils. They also preferentially accumulated in IRI-induced inflammatory lesions. Collectively, our findings indicate that BRNP preconditioning provides a simple and safe approach that can be easily monitored in the blood like endogenous bilirubin, and could be a promising strategy to protect against IRI in a clinical setting. Copyright © 2017 Elsevier Ltd. All rights reserved.
Stress preconditioning of spreading depression in the locust CNS.
Directory of Open Access Journals (Sweden)
Corinne I Rodgers
Full Text Available Cortical spreading depression (CSD is closely associated with important pathologies including stroke, seizures and migraine. The mechanisms underlying SD in its various forms are still incompletely understood. Here we describe SD-like events in an invertebrate model, the ventilatory central pattern generator (CPG of locusts. Using K(+ -sensitive microelectrodes, we measured extracellular K(+ concentration ([K(+](o in the metathoracic neuropile of the CPG while monitoring CPG output electromyographically from muscle 161 in the second abdominal segment to investigate the role K(+ in failure of neural circuit operation induced by various stressors. Failure of ventilation in response to different stressors (hyperthermia, anoxia, ATP depletion, Na(+/K(+ ATPase impairment, K(+ injection was associated with a disturbance of CNS ion homeostasis that shares the characteristics of CSD and SD-like events in vertebrates. Hyperthermic failure was preconditioned by prior heat shock (3 h, 45 degrees C and induced-thermotolerance was associated with an increase in the rate of clearance of extracellular K(+ that was not linked to changes in ATP levels or total Na(+/K(+ ATPase activity. Our findings suggest that SD-like events in locusts are adaptive to terminate neural network operation and conserve energy during stress and that they can be preconditioned by experience. We propose that they share mechanisms with CSD in mammals suggesting a common evolutionary origin.
Ketamine, but not S(+)-ketamine, blocks ischemic preconditioning in rabbit hearts in vivo
Müllenheim, J.; Frässdorf, J.; Preckel, B.; Thämer, V.; Schlack, W.
2001-01-01
BACKGROUND: Ketamine blocks KATP channels in isolated cells and abolishes the cardioprotective effect of ischemic preconditioning in vitro. The authors investigated the effects of ketamine and S(+)-ketamine on ischemic preconditioning in the rabbit heart in vivo. METHODS: In 46
Two-level preconditioned conjugate gradient methods with applications to bubbly flow problems
Tang, J.M.
2008-01-01
The Preconditioned Conjugate Gradient (PCG) method is one of the most popular iterative methods for solving large linear systems with a symmetric and positive semi-definite coefficient matrix. However, if the preconditioned coefficient matrix is ill-conditioned, the convergence of the PCG method
Sensory Preconditioning in Newborn Rabbits: From Common to Distinct Odor Memories
Coureaud, Gerard; Tourat, Audrey; Ferreira, Guillaume
2013-01-01
This study evaluated whether olfactory preconditioning is functional in newborn rabbits and based on joined or independent memory of odorants. First, after exposure to odorants A+B, the conditioning of A led to high responsiveness to odorant B. Second, responsiveness to B persisted after amnesia of A. Third, preconditioning was also functional…
CSIR Research Space (South Africa)
Toper, AZ
1998-01-01
Full Text Available This research report discusses the development of preconditioning techniques to control face bursts, for safer mining in seismically hazardous areas. Preconditioning involves regularly setting off carefully tailored blasts in the fractured rock...
DenInv3D: a geophysical software for three-dimensional density inversion of gravity field data
Tian, Yu; Ke, Xiaoping; Wang, Yong
2018-04-01
This paper presents a three-dimensional density inversion software called DenInv3D that operates on gravity and gravity gradient data. The software performs inversion modelling, kernel function calculation, and inversion calculations using the improved preconditioned conjugate gradient (PCG) algorithm. In the PCG algorithm, due to the uncertainty of empirical parameters, such as the Lagrange multiplier, we use the inflection point of the L-curve as the regularisation parameter. The software can construct unequally spaced grids and perform inversions using such grids, which enables changing the resolution of the inversion results at different depths. Through inversion of airborne gradiometry data on the Australian Kauring test site, we discovered that anomalous blocks of different sizes are present within the study area in addition to the central anomalies. The software of DenInv3D can be downloaded from http://159.226.162.30.
Three-dimensional inverse modelling of damped elastic wave propagation in the Fourier domain
Petrov, Petr V.; Newman, Gregory A.
2014-09-01
3-D full waveform inversion (FWI) of seismic wavefields is routinely implemented with explicit time-stepping simulators. A clear advantage of explicit time stepping is the avoidance of solving large-scale implicit linear systems that arise with frequency domain formulations. However, FWI using explicit time stepping may require a very fine time step and (as a consequence) significant computational resources and run times. If the computational challenges of wavefield simulation can be effectively handled, an FWI scheme implemented within the frequency domain utilizing only a few frequencies, offers a cost effective alternative to FWI in the time domain. We have therefore implemented a 3-D FWI scheme for elastic wave propagation in the Fourier domain. To overcome the computational bottleneck in wavefield simulation, we have exploited an efficient Krylov iterative solver for the elastic wave equations approximated with second and fourth order finite differences. The solver does not exploit multilevel preconditioning for wavefield simulation, but is coupled efficiently to the inversion iteration workflow to reduce computational cost. The workflow is best described as a series of sequential inversion experiments, where in the case of seismic reflection acquisition geometries, the data has been laddered such that we first image highly damped data, followed by data where damping is systemically reduced. The key to our modelling approach is its ability to take advantage of solver efficiency when the elastic wavefields are damped. As the inversion experiment progresses, damping is significantly reduced, effectively simulating non-damped wavefields in the Fourier domain. While the cost of the forward simulation increases as damping is reduced, this is counterbalanced by the cost of the outer inversion iteration, which is reduced because of a better starting model obtained from the larger damped wavefield used in the previous inversion experiment. For cross-well data, it is
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2011-01-01
Most prestack traveltime relations we tend work with are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multi-focusing or double square-root (DSR) and the common reflection stack (CRS) equations. Using the DSR equation, I analyze the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I derive expansion based solutions of this eikonal based on polynomial expansions in terms of the reflection and dip angles in a generally inhomogenous background medium. These approximate solutions are free of singularities and can be used to estimate travetimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. A Marmousi example demonstrates the usefulness of the approach. © 2011 Society of Exploration Geophysicists.
Topology, calculus and approximation
Komornik, Vilmos
2017-01-01
Presenting basic results of topology, calculus of several variables, and approximation theory which are rarely treated in a single volume, this textbook includes several beautiful, but almost forgotten, classical theorems of Descartes, Erdős, Fejér, Stieltjes, and Turán. The exposition style of Topology, Calculus and Approximation follows the Hungarian mathematical tradition of Paul Erdős and others. In the first part, the classical results of Alexandroff, Cantor, Hausdorff, Helly, Peano, Radon, Tietze and Urysohn illustrate the theories of metric, topological and normed spaces. Following this, the general framework of normed spaces and Carathéodory's definition of the derivative are shown to simplify the statement and proof of various theorems in calculus and ordinary differential equations. The third and final part is devoted to interpolation, orthogonal polynomials, numerical integration, asymptotic expansions and the numerical solution of algebraic and differential equations. Students of both pure an...
Acute puerperal uterine inversion
International Nuclear Information System (INIS)
Hussain, M.; Liaquat, N.; Noorani, K.; Bhutta, S.Z; Jabeen, T.
2004-01-01
Objective: To determine the frequency, causes, clinical presentations, management and maternal mortality associated with acute puerperal inversion of the uterus. Materials and Methods: All the patients who developed acute puerperal inversion of the uterus either in or outside the JPMC were included in the study. Patients of chronic uterine inversion were not included in the present study. Abdominal and vaginal examination was done to confirm and classify inversion into first, second or third degrees. Results: 57036 deliveries and 36 acute uterine inversions occurred during the study period, so the frequency of uterine inversion was 1 in 1584 deliveries. Mismanagement of third stage of labour was responsible for uterine inversion in 75% of patients. Majority of the patients presented with shock, either hypovolemic (69%) or neurogenic (13%) in origin. Manual replacement of the uterus under general anaesthesia with 2% halothane was successfully done in 35 patients (97.5%). Abdominal hysterectomy was done in only one patient. There were three maternal deaths due to inversion. Conclusion: Proper education and training regarding placental delivery, diagnosis and management of uterine inversion must be imparted to the maternity care providers especially to traditional birth attendants and family physicians to prevent this potentially life-threatening condition. (author)
Approximate Bayesian recursive estimation
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
Approximating Preemptive Stochastic Scheduling
Megow Nicole; Vredeveld Tjark
2009-01-01
We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...
Optimization and approximation
Pedregal, Pablo
2017-01-01
This book provides a basic, initial resource, introducing science and engineering students to the field of optimization. It covers three main areas: mathematical programming, calculus of variations and optimal control, highlighting the ideas and concepts and offering insights into the importance of optimality conditions in each area. It also systematically presents affordable approximation methods. Exercises at various levels have been included to support the learning process.
On transparent potentials: a Born approximation study
International Nuclear Information System (INIS)
Coudray, C.
1980-01-01
In the frame of the scattering inverse problem at fixed energy, a class of potentials transparent in Born approximation is obtained. All these potentials are spherically symmetric and are oscillating functions of the reduced radial variable. Amongst them, the Born approximation of the transparent potential of the Newton-Sabatier method is found. In the same class, quasi-transparent potentials are exhibited. Very general features of potentials transparent in Born approximation are then stated. And bounds are given for the exact scattering amplitudes corresponding to most of the potentials previously exhibited. These bounds, obtained at fixed energy, and for large values of the angular momentum, are found to be independent on the energy
Effects Of Ischemic Preconditioning On The Renal Ischemia- Reperfusion Injury
Directory of Open Access Journals (Sweden)
Anyamanesh S
2003-07-01
Full Text Available During kidney and other organ transplantation, the organ to be transplanted, must inevitably remain out of the body with little or no blood perfusion at all for a long period of time (ischemia. These events have been suggested to cause the formation of oxygen- derived free radicals (OFR. Reperfusion (reintroduction of blood flow will further exacerbate the initial damage caused by the ischemic insult and may result in the production of free radicals. The aim of this study was to investigate whether induction of brief periods of renal artery occlusion (ischemic pre¬conditioning, IPC can provide protection from the effects of a subsequent period of ischemia and reperfusion (IR in the rat kidney."nMaterials and Methods: In this regard, 28 white, male rats were randomly and equally divided into four groups: Control (sham- operated, IPC alone, IR alone (30 min ischemia followed by 10 min reperfusion, and IPC- IR. Preconditioning involved the sequential clamping of the right renal artery for 5 min and declamping for 5 min for a total of 3 cycles. To demonstrate the effectiveness of IPC regimen, vitamin E as an endogenous antioxidant and an index of lipid peroxidation was measured by HPLC after its extraction from right renal venous plasma and right renal tissue."nResults: Results of this study showed that the amount of vitamin E of renal tissue and venous plasma in the IR group had a significant decrease when compared to the control group (P< 0.0001. Whereas the amount of this vitamin in both renal tissue and venous plasma of the IPC- IR group was significantly higher than that in the IR group (P< 0.0001, but did not show any significant difference with the control group."nConclusion: In this study, preconditioning method prevented the reduction of the endogenous antioxidant (Vit. E in encountering the following sustained ischemic insult. Therefore, we suggest that ischemic preconditioning can be used to protect the Vit. E level of kidney from its
Cyclic approximation to stasis
Directory of Open Access Journals (Sweden)
Stewart D. Johnson
2009-06-01
Full Text Available Neighborhoods of points in $mathbb{R}^n$ where a positive linear combination of $C^1$ vector fields sum to zero contain, generically, cyclic trajectories that switch between the vector fields. Such points are called stasis points, and the approximating switching cycle can be chosen so that the timing of the switches exactly matches the positive linear weighting. In the case of two vector fields, the stasis points form one-dimensional $C^1$ manifolds containing nearby families of two-cycles. The generic case of two flows in $mathbb{R}^3$ can be diffeomorphed to a standard form with cubic curves as trajectories.
International Nuclear Information System (INIS)
El Sawi, M.
1983-07-01
A simple approach employing properties of solutions of differential equations is adopted to derive an appropriate extension of the WKBJ method. Some of the earlier techniques that are commonly in use are unified, whereby the general approximate solution to a second-order homogeneous linear differential equation is presented in a standard form that is valid for all orders. In comparison to other methods, the present one is shown to be leading in the order of iteration, and thus possibly has the ability of accelerating the convergence of the solution. The method is also extended for the solution of inhomogeneous equations. (author)
The relaxation time approximation
International Nuclear Information System (INIS)
Gairola, R.P.; Indu, B.D.
1991-01-01
A plausible approximation has been made to estimate the relaxation time from a knowledge of the transition probability of phonons from one state (r vector, q vector) to other state (r' vector, q' vector), as a result of collision. The relaxation time, thus obtained, shows a strong dependence on temperature and weak dependence on the wave vector. In view of this dependence, relaxation time has been expressed in terms of a temperature Taylor's series in the first Brillouin zone. Consequently, a simple model for estimating the thermal conductivity is suggested. the calculations become much easier than the Callaway model. (author). 14 refs
Polynomial approximation on polytopes
Totik, Vilmos
2014-01-01
Polynomial approximation on convex polytopes in \\mathbf{R}^d is considered in uniform and L^p-norms. For an appropriate modulus of smoothness matching direct and converse estimates are proven. In the L^p-case so called strong direct and converse results are also verified. The equivalence of the moduli of smoothness with an appropriate K-functional follows as a consequence. The results solve a problem that was left open since the mid 1980s when some of the present findings were established for special, so-called simple polytopes.
Finite elements and approximation
Zienkiewicz, O C
2006-01-01
A powerful tool for the approximate solution of differential equations, the finite element is extensively used in industry and research. This book offers students of engineering and physics a comprehensive view of the principles involved, with numerous illustrative examples and exercises.Starting with continuum boundary value problems and the need for numerical discretization, the text examines finite difference methods, weighted residual methods in the context of continuous trial functions, and piecewise defined trial functions and the finite element method. Additional topics include higher o
Inverse logarithmic potential problem
Cherednichenko, V G
1996-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Inverse Kinematics using Quaternions
DEFF Research Database (Denmark)
Henriksen, Knud; Erleben, Kenny; Engell-Nørregård, Morten
In this project I describe the status of inverse kinematics research, with the focus firmly on the methods that solve the core problem. An overview of the different methods are presented Three common methods used in inverse kinematics computation have been chosen as subject for closer inspection....
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Institutionalized Ignorance as a Precondition for Rational Risk Expertise
DEFF Research Database (Denmark)
Merkelsen, Henrik
2011-01-01
the lowest organizational level, where concrete risks occur, to the highest organizational level, where the body of professional risk expertise is situated. The article emphasizes the role of knowledge, responsibility, loyalty, and trust as risk-attenuation factors and concludes by suggesting......The present case study seeks to explain the conditions for experts’ rational risk perception by analyzing the institutional contexts that constitute a field of food safety expertise in Denmark. The study highlights the role of risk reporting and how contextual factors affect risk reporting from...... that the preconditions for the expert's rationality may rather be a lack of risk-specific knowledge due to poor risk reporting than a superior level of risk knowledge....
Explicit solution of Calderon preconditioned time domain integral equations
Ulku, Huseyin Arda
2013-07-01
An explicit marching on-in-time (MOT) scheme for solving Calderon-preconditioned time domain integral equations is proposed. The scheme uses Rao-Wilton-Glisson and Buffa-Christiansen functions to discretize the domain and range of the integral operators and a PE(CE)m type linear multistep to march on in time. Unlike its implicit counterpart, the proposed explicit solver requires the solution of an MOT system with a Gram matrix that is sparse and well-conditioned independent of the time step size. Numerical results demonstrate that the explicit solver maintains its accuracy and stability even when the time step size is chosen as large as that typically used by an implicit solver. © 2013 IEEE.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla; Bagci, Hakan
2014-01-01
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla
2014-05-04
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla
2014-01-06
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Least-squares reverse time migration with radon preconditioning
Dutta, Gaurav
2016-09-06
We present a least-squares reverse time migration (LSRTM) method using Radon preconditioning to regularize noisy or severely undersampled data. A high resolution local radon transform is used as a change of basis for the reflectivity and sparseness constraints are applied to the inverted reflectivity in the transform domain. This reflects the prior that for each location of the subsurface the number of geological dips is limited. The forward and the adjoint mapping of the reflectivity to the local Radon domain and back are done through 3D Fourier-based discrete Radon transform operators. The sparseness is enforced by applying weights to the Radon domain components which either vary with the amplitudes of the local dips or are thresholded at given quantiles. Numerical tests on synthetic and field data validate the effectiveness of the proposed approach in producing images with improved SNR and reduced aliasing artifacts when compared with standard RTM or LSRTM.
Natural Preconditioning and Iterative Methods for Saddle Point Systems
Pestana, Jennifer
2015-01-01
© 2015 Society for Industrial and Applied Mathematics. The solution of quadratic or locally quadratic extremum problems subject to linear(ized) constraints gives rise to linear systems in saddle point form. This is true whether in the continuous or the discrete setting, so saddle point systems arising from the discretization of partial differential equation problems, such as those describing electromagnetic problems or incompressible flow, lead to equations with this structure, as do, for example, interior point methods and the sequential quadratic programming approach to nonlinear optimization. This survey concerns iterative solution methods for these problems and, in particular, shows how the problem formulation leads to natural preconditioners which guarantee a fast rate of convergence of the relevant iterative methods. These preconditioners are related to the original extremum problem and their effectiveness - in terms of rapidity of convergence - is established here via a proof of general bounds on the eigenvalues of the preconditioned saddle point matrix on which iteration convergence depends.
Aerodynamic shape optimization using preconditioned conjugate gradient methods
Burgreen, Greg W.; Baysal, Oktay
1993-01-01
In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.
Can endurance exercise preconditioning prevention disuse muscle atrophy?
Directory of Open Access Journals (Sweden)
Michael P Wiggs
2015-03-01
Full Text Available Emerging evidence suggests that exercise training can provide a level of protection against disuse muscle atrophy. Endurance exercise training imposes oxidative, metabolic, and heat stress on skeletal muscle which activates a variety of cellular signaling pathways that ultimately leads to the increased expression of proteins that have been demonstrated to protect muscle from inactivity –induced atrophy. This review will highlight the effect of exercise-induced oxidative stress on endogenous enzymatic antioxidant capacity (i.e., superoxide dismutase, glutathione peroxidase, and catalase, the role of oxidative and metabolic stress on PGC1-α, and finally highlight the effect heat stress and HSP70 induction. Finally, this review will discuss the supporting scientific evidence that these proteins can attenuate muscle atrophy through exercise preconditioning.
Effect of ozone oxidative preconditioning in preventing early radiation-induced lung injury in rats
Energy Technology Data Exchange (ETDEWEB)
Bakkal, B.H. [Department of Radiation Oncology, School of Medicine, Bulent Ecevit University, Kozlu, Zonguldak (Turkey); Gultekin, F.A. [Department of General Surgery, School of Medicine, Bulent Ecevit University, Kozlu, Zonguldak (Turkey); Guven, B. [Department of Biochemistry, School of Medicine, Bulent Ecevit University, Kozlu, Zonguldak (Turkey); Turkcu, U.O. [Mugla School of Health Sciences, Mugla Sitki Kocman University, Mugla (Turkey); Bektas, S. [Department of Pathology, School of Medicine, Bulent Ecevit University, Kozlu, Zonguldak (Turkey); Can, M. [Department of Biochemistry, School of Medicine, Bulent Ecevit University, Kozlu, Zonguldak (Turkey)
2013-09-27
Ionizing radiation causes its biological effects mainly through oxidative damage induced by reactive oxygen species. Previous studies showed that ozone oxidative preconditioning attenuated pathophysiological events mediated by reactive oxygen species. As inhalation of ozone induces lung injury, the aim of this study was to examine whether ozone oxidative preconditioning potentiates or attenuates the effects of irradiation on the lung. Rats were subjected to total body irradiation, with or without treatment with ozone oxidative preconditioning (0.72 mg/kg). Serum proinflammatory cytokine levels, oxidative damage markers, and histopathological analysis were compared at 6 and 72 h after total body irradiation. Irradiation significantly increased lung malondialdehyde levels as an end-product of lipoperoxidation. Irradiation also significantly decreased lung superoxide dismutase activity, which is an indicator of the generation of oxidative stress and an early protective response to oxidative damage. Ozone oxidative preconditioning plus irradiation significantly decreased malondialdehyde levels and increased the activity of superoxide dismutase, which might indicate protection of the lung from radiation-induced lung injury. Serum tumor necrosis factor alpha and interleukin-1 beta levels, which increased significantly following total body irradiation, were decreased with ozone oxidative preconditioning. Moreover, ozone oxidative preconditioning was able to ameliorate radiation-induced lung injury assessed by histopathological evaluation. In conclusion, ozone oxidative preconditioning, repeated low-dose intraperitoneal administration of ozone, did not exacerbate radiation-induced lung injury, and, on the contrary, it provided protection against radiation-induced lung damage.
Warner, Dennis B.
1984-02-01
Recognition of the socioeconomic preconditions for successful rural water-supply and sanitation projects in developing countries is the key to identifying a new project. Preconditions are the social, economic and technical characteristics defining the project environment. There are two basic types of preconditions: those existing at the time of the initial investigation and those induced by subsequent project activities. Successful project identification is dependent upon an accurate recognition of existing constraints and a carefully tailored package of complementary investments intended to overcome the constraints. This paper discusses the socioeconomic aspects of preconditions in the context of a five-step procedure for project identification. The procedure includes: (1) problem identification; (2) determination of socioeconomic status; (3) technology selection; (4) utilization of support conditions; and (5) benefit estimation. Although the establishment of specific preconditions should be based upon the types of projects likely to be implemented, the paper outlines a number of general relationships regarding favourable preconditions in water and sanitation planning. These relationships are used within the above five-step procedure to develop a set of general guidelines for the application of preconditions in the identification of rural water-supply and sanitation projects.
Effect of ozone oxidative preconditioning in preventing early radiation-induced lung injury in rats
International Nuclear Information System (INIS)
Bakkal, B.H.; Gultekin, F.A.; Guven, B.; Turkcu, U.O.; Bektas, S.; Can, M.
2013-01-01
Ionizing radiation causes its biological effects mainly through oxidative damage induced by reactive oxygen species. Previous studies showed that ozone oxidative preconditioning attenuated pathophysiological events mediated by reactive oxygen species. As inhalation of ozone induces lung injury, the aim of this study was to examine whether ozone oxidative preconditioning potentiates or attenuates the effects of irradiation on the lung. Rats were subjected to total body irradiation, with or without treatment with ozone oxidative preconditioning (0.72 mg/kg). Serum proinflammatory cytokine levels, oxidative damage markers, and histopathological analysis were compared at 6 and 72 h after total body irradiation. Irradiation significantly increased lung malondialdehyde levels as an end-product of lipoperoxidation. Irradiation also significantly decreased lung superoxide dismutase activity, which is an indicator of the generation of oxidative stress and an early protective response to oxidative damage. Ozone oxidative preconditioning plus irradiation significantly decreased malondialdehyde levels and increased the activity of superoxide dismutase, which might indicate protection of the lung from radiation-induced lung injury. Serum tumor necrosis factor alpha and interleukin-1 beta levels, which increased significantly following total body irradiation, were decreased with ozone oxidative preconditioning. Moreover, ozone oxidative preconditioning was able to ameliorate radiation-induced lung injury assessed by histopathological evaluation. In conclusion, ozone oxidative preconditioning, repeated low-dose intraperitoneal administration of ozone, did not exacerbate radiation-induced lung injury, and, on the contrary, it provided protection against radiation-induced lung damage
The random phase approximation
International Nuclear Information System (INIS)
Schuck, P.
1985-01-01
RPA is the adequate theory to describe vibrations of the nucleus of very small amplitudes. These vibrations can either be forced by an external electromagnetic field or can be eigenmodes of the nucleus. In a one dimensional analogue the potential corresponding to such eigenmodes of very small amplitude should be rather stiff otherwise the motion risks to be a large amplitude one and to enter a region where the approximation is not valid. This means that nuclei which are supposedly well described by RPA must have a very stable groundstate configuration (must e.g. be very stiff against deformation). This is usually the case for doubly magic nuclei or close to magic nuclei which are in the middle of proton and neutron shells which develop a very stable groundstate deformation; we take the deformation as an example but there are many other possible degrees of freedom as, for example, compression modes, isovector degrees of freedom, spin degrees of freedom, and many more
The quasilocalized charge approximation
International Nuclear Information System (INIS)
Kalman, G J; Golden, K I; Donko, Z; Hartmann, P
2005-01-01
The quasilocalized charge approximation (QLCA) has been used for some time as a formalism for the calculation of the dielectric response and for determining the collective mode dispersion in strongly coupled Coulomb and Yukawa liquids. The approach is based on a microscopic model in which the charges are quasilocalized on a short-time scale in local potential fluctuations. We review the conceptual basis and theoretical structure of the QLC approach and together with recent results from molecular dynamics simulations that corroborate and quantify the theoretical concepts. We also summarize the major applications of the QLCA to various physical systems, combined with the corresponding results of the molecular dynamics simulations and point out the general agreement and instances of disagreement between the two
An inverse heat transfer problem for optimization of the thermal ...
Indian Academy of Sciences (India)
This paper takes a different approach towards identiﬁcation of the thermal process in machining, using inverse heat transfer problem. Inverse heat transfer method allows the closest possible experimental and analytical approximation of thermal state for a machining process. Based on a temperature measured at any point ...
Discrete inverse scattering theory and the continuum limit
International Nuclear Information System (INIS)
Berryman, J.G.; Greene, R.R.
1978-01-01
The class of satisfactory difference approximations for the Schroedinger equation in discrete inverse scattering theory is shown smaller than previously supposed. A fast algorithm (analogous to the Levinson algorithm for Toeplitz matrices) is found for solving the discrete inverse problem. (Auth.)
Seismic inverse scattering in the downward continuation approach
Stolk, C.C.; de Hoop, M.V.
Seismic data are commonly modeled by a linearization around a smooth background medium in combination with a high frequency approximation. The perturbation of the medium coefficient is assumed to contain the discontinuities. This leads to two inverse problems, first the linearized inverse problem
Directory of Open Access Journals (Sweden)
Wu Ann
2011-01-01
Full Text Available Abstract Background A preconditioning stimulus can trigger a neuroprotective phenotype in the nervous system - a preconditioning nerve lesion causes a significant increase in axonal regeneration, and cerebral preconditioning protects against subsequent ischemia. We hypothesized that a preconditioning nerve lesion induces gene/protein modifications, neuronal changes, and immune activation that may affect pain sensation following subsequent nerve injury. We examined whether a preconditioning lesion affects neuropathic pain and neuroinflammation after peripheral nerve injury. Results We found that a preconditioning crush injury to a terminal branch of the sciatic nerve seven days before partial ligation of the sciatic nerve (PSNL; a model of neuropathic pain induced a significant attenuation of pain hypersensitivity, particularly mechanical allodynia. A preconditioning lesion of the tibial nerve induced a long-term significant increase in paw-withdrawal threshold to mechanical stimuli and paw-withdrawal latency to thermal stimuli, after PSNL. A preconditioning lesion of the common peroneal induced a smaller but significant short-term increase in paw-withdrawal threshold to mechanical stimuli, after PSNL. There was no difference between preconditioned and unconditioned animals in neuronal damage and macrophage and T-cell infiltration into the dorsal root ganglia (DRGs or in astrocyte and microglia activation in the spinal dorsal and ventral horns. Conclusions These results suggest that prior exposure to a mild nerve lesion protects against adverse effects of subsequent neuropathic injury, and that this conditioning-induced inhibition of pain hypersensitivity is not dependent on neuroinflammation in DRGs and spinal cord. Identifying the underlying mechanisms may have important implications for the understanding of neuropathic pain due to nerve injury.
Physics-based preconditioning and the Newton-Krylov method for non-equilibrium radiation diffusion
International Nuclear Information System (INIS)
Mousseau, V.A.; Knoll, D.A.; Rider, W.J.
2000-01-01
An algorithm is presented for the solution of the time dependent reaction-diffusion systems which arise in non-equilibrium radiation diffusion applications. This system of nonlinear equations is solved by coupling three numerical methods, Jacobian-free Newton-Krylov, operator splitting, and multigrid linear solvers. An inexact Newton's method is used to solve the system of nonlinear equations. Since building the Jacobian matrix for problems of interest can be challenging, the authors employ a Jacobian-free implementation of Newton's method, where the action of the Jacobian matrix on a vector is approximated by a first order Taylor series expansion. Preconditioned generalized minimal residual (PGMRES) is the Krylov method used to solve the linear systems that come from the iterations of Newton's method. The preconditioner in this solution method is constructed using a physics-based divide and conquer approach, often referred to as operator splitting. This solution procedure inverts the scalar elliptic systems that make up the preconditioner using simple multigrid methods. The preconditioner also addresses the strong coupling between equations with local 2 x 2 block solves. The intra-cell coupling is applied after the inter-cell coupling has already been addressed by the elliptic solves. Results are presented using this solution procedure that demonstrate its efficiency while incurring minimal memory requirements
Block Preconditioning to Enable Physics-Compatible Implicit Multifluid Plasma Simulations
Phillips, Edward; Shadid, John; Cyr, Eric; Miller, Sean
2017-10-01
Multifluid plasma simulations involve large systems of partial differential equations in which many time-scales ranging over many orders of magnitude arise. Since the fastest of these time-scales may set a restrictively small time-step limit for explicit methods, the use of implicit or implicit-explicit time integrators can be more tractable for obtaining dynamics at time-scales of interest. Furthermore, to enforce properties such as charge conservation and divergence-free magnetic field, mixed discretizations using volume, nodal, edge-based, and face-based degrees of freedom are often employed in some form. Together with the presence of stiff modes due to integrating over fast time-scales, the mixed discretization makes the required linear solves for implicit methods particularly difficult for black box and monolithic solvers. This work presents a block preconditioning strategy for multifluid plasma systems that segregates the linear system based on discretization type and approximates off-diagonal coupling in block diagonal Schur complement operators. By employing multilevel methods for the block diagonal subsolves, this strategy yields algorithmic and parallel scalability which we demonstrate on a range of problems.
International Nuclear Information System (INIS)
Belliard, M.; Grandotto, M.
2003-01-01
In the framework of the two-phase fluid simulations of the steam generators of pressurized water nuclear reactors, we present in this paper a geometric version of a pseudo-Full MultiGrid (pseudo- FMG) Full Approximation Storage (FAS) preconditioning of balance equations in the GENEPI code. In our application, the 3D steady state flow is reached by a transient computation using a semi-implicit fractional step algorithm for the averaged two-phase mixture balance equations (mass, momentum and energy for the secondary flow). Our application, running on workstation clusters, is based on a CEA code-linker and the PVM package. The difficulties to apply the geometric FAS multigrid method to the momentum and mass balance equations are addressed. The use of a sequential pseudo-FMG FAS twogrid method for both energy and mass/momentum balance equations, using dynamic multigrid cycles, leads to perceptibly improvements in the computation convergences. An original parallel red-black pseudo-FMG FAS three-grid algorithm is presented too. The numerical tests (steam generator mockup simulations) underline the sizable increase in speed of convergence of the computations, essentially for the ones involving a large number of freedom degrees (about 100 thousand cells). The two-phase mixture balance equation residuals are quickly reduced: the reached speed-up stands between 2 and 3 following the number of grids. The effects on the convergence behavior of the numerical parameters are investigated
Energy Technology Data Exchange (ETDEWEB)
Vecharynski, Eugene [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Brabec, Jiri [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Shao, Meiyue [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Govind, Niranjan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab.; Yang, Chao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
2017-12-01
We present two efficient iterative algorithms for solving the linear response eigen- value problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into a product eigenvalue problem that is self-adjoint with respect to a K-inner product. This product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. However, the other component of the eigenvector can be easily recovered in a postprocessing procedure. Therefore, the algorithms we present here are more efficient than existing algorithms that try to approximate both components of the eigenvectors simultaneously. The efficiency of the new algorithms is demonstrated by numerical examples.
A Preconditioning Technique for First-Order Primal-Dual Splitting Method in Convex Optimization
Directory of Open Access Journals (Sweden)
Meng Wen
2017-01-01
Full Text Available We introduce a preconditioning technique for the first-order primal-dual splitting method. The primal-dual splitting method offers a very general framework for solving a large class of optimization problems arising in image processing. The key idea of the preconditioning technique is that the constant iterative parameters are updated self-adaptively in the iteration process. We also give a simple and easy way to choose the diagonal preconditioners while the convergence of the iterative algorithm is maintained. The efficiency of the proposed method is demonstrated on an image denoising problem. Numerical results show that the preconditioned iterative algorithm performs better than the original one.
Modeling of uncertainties in statistical inverse problems
International Nuclear Information System (INIS)
Kaipio, Jari
2008-01-01
In all real world problems, the models that tie the measurements to the unknowns of interest, are at best only approximations for reality. While moderate modeling and approximation errors can be tolerated with stable problems, inverse problems are a notorious exception. Typical modeling errors include inaccurate geometry, unknown boundary and initial data, properties of noise and other disturbances, and simply the numerical approximations of the physical models. In principle, the Bayesian approach to inverse problems, in which all uncertainties are modeled as random variables, is capable of handling these uncertainties. Depending on the type of uncertainties, however, different strategies may be adopted. In this paper we give an overview of typical modeling errors and related strategies within the Bayesian framework.
International Nuclear Information System (INIS)
Burkhard, N.R.
1979-01-01
The gravity inversion code applies stabilized linear inverse theory to determine the topography of a subsurface density anomaly from Bouguer gravity data. The gravity inversion program consists of four source codes: SEARCH, TREND, INVERT, and AVERAGE. TREND and INVERT are used iteratively to converge on a solution. SEARCH forms the input gravity data files for Nevada Test Site data. AVERAGE performs a covariance analysis on the solution. This document describes the necessary input files and the proper operation of the code. 2 figures, 2 tables
Seismic waveform inversion best practices: regional, global and exploration test cases
Modrak, Ryan; Tromp, Jeroen
2016-09-01
Reaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence associated with strong nonlinearity, one or two test cases are not enough to reliably inform such decisions. We identify best practices, instead, using four seismic near-surface problems, one regional problem and two global problems. To make meaningful quantitative comparisons between methods, we carry out hundreds of inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that limited-memory BFGS provides computational savings over nonlinear conjugate gradient methods in a wide range of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization and total variation regularization are effective in different contexts. Besides questions of one strategy or another, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details involving the line search and restart conditions have a strong effect on computational cost, regardless of the chosen nonlinear optimization algorithm.
Ensemble Kalman methods for inverse problems
International Nuclear Information System (INIS)
Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M
2013-01-01
The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)
Approximate quantum Markov chains
Sutter, David
2018-01-01
This book is an introduction to quantum Markov chains and explains how this concept is connected to the question of how well a lost quantum mechanical system can be recovered from a correlated subsystem. To achieve this goal, we strengthen the data-processing inequality such that it reveals a statement about the reconstruction of lost information. The main difficulty in order to understand the behavior of quantum Markov chains arises from the fact that quantum mechanical operators do not commute in general. As a result we start by explaining two techniques of how to deal with non-commuting matrices: the spectral pinching method and complex interpolation theory. Once the reader is familiar with these techniques a novel inequality is presented that extends the celebrated Golden-Thompson inequality to arbitrarily many matrices. This inequality is the key ingredient in understanding approximate quantum Markov chains and it answers a question from matrix analysis that was open since 1973, i.e., if Lieb's triple ma...
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2012-05-01
Many of the explicit prestack traveltime relations used in practice are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multifocusing, based on the double square-root (DSR) equation, and the common reflection stack (CRS) approaches. Using the DSR equation, I constructed the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I recasted the eikonal in terms of the reflection angle, and thus, derived expansion based solutions of this eikonal in terms of the difference between the source and receiver velocities in a generally inhomogenous background medium. The zero-order term solution, corresponding to ignoring the lateral velocity variation in estimating the prestack part, is free of singularities and can be used to estimate traveltimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. The higher-order terms include limitations for horizontally traveling waves, however, we can readily enforce stability constraints to avoid such singularities. In fact, another expansion over reflection angle can help us avoid these singularities by requiring the source and receiver velocities to be different. On the other hand, expansions in terms of reflection angles result in singularity free equations. For a homogenous background medium, as a test, the solutions are reasonably accurate to large reflection and dip angles. A Marmousi example demonstrated the usefulness and versatility of the formulation. © 2012 Society of Exploration Geophysicists.
Sharp spatially constrained inversion
DEFF Research Database (Denmark)
Vignoli, Giulio G.; Fiandaca, Gianluca G.; Christiansen, Anders Vest C A.V.C.
2013-01-01
We present sharp reconstruction of multi-layer models using a spatially constrained inversion with minimum gradient support regularization. In particular, its application to airborne electromagnetic data is discussed. Airborne surveys produce extremely large datasets, traditionally inverted...... by using smoothly varying 1D models. Smoothness is a result of the regularization constraints applied to address the inversion ill-posedness. The standard Occam-type regularized multi-layer inversion produces results where boundaries between layers are smeared. The sharp regularization overcomes...... inversions are compared against classical smooth results and available boreholes. With the focusing approach, the obtained blocky results agree with the underlying geology and allow for easier interpretation by the end-user....
International Nuclear Information System (INIS)
Rosenwald, J.-C.
2008-01-01
The lecture addressed the following topics: Optimizing radiotherapy dose distribution; IMRT contributes to optimization of energy deposition; Inverse vs direct planning; Main steps of IMRT; Background of inverse planning; General principle of inverse planning; The 3 main components of IMRT inverse planning; The simplest cost function (deviation from prescribed dose); The driving variable : the beamlet intensity; Minimizing a 'cost function' (or 'objective function') - the walker (or skier) analogy; Application to IMRT optimization (the gradient method); The gradient method - discussion; The simulated annealing method; The optimization criteria - discussion; Hard and soft constraints; Dose volume constraints; Typical user interface for definition of optimization criteria; Biological constraints (Equivalent Uniform Dose); The result of the optimization process; Semi-automatic solutions for IMRT; Generalisation of the optimization problem; Driving and driven variables used in RT optimization; Towards multi-criteria optimization; and Conclusions for the optimization phase. (P.A.)
Inverse source problems for eddy current equations
International Nuclear Information System (INIS)
Rodríguez, Ana Alonso; Valli, Alberto; Camaño, Jessika
2012-01-01
We study the inverse source problem for the eddy current approximation of Maxwell equations. As for the full system of Maxwell equations, we show that a volume current source cannot be uniquely identified by knowledge of the tangential components of the electromagnetic fields on the boundary, and we characterize the space of non-radiating sources. On the other hand, we prove that the inverse source problem has a unique solution if the source is supported on the boundary of a subdomain or if it is the sum of a finite number of dipoles. We address the applicability of this result for the localization of brain activity from electroencephalography and magnetoencephalography measurements. (paper)
Saddlepoint Approximations in Conditional Inference
1990-06-11
Then the inverse transform can be written as (%, Y) = (T, q(T, Z)) for some function q. When the transform is not one to one, the domain should be...general regularity conditions described at the beginning of this section hold and that the solution t1 in (9) exists. Denote the inverse transform by (X, Y...density hn(t 0 l z) are desired. Then the inverse transform (Y, ) = (T, q(T, Z)) exists and the variable v in the cumulant generating function K(u, v
S2SA preconditioning for the Sn equations with strictly non negative spatial discretization
International Nuclear Information System (INIS)
Bruss, D. E.; Morel, J. E.; Ragusa, J. C.
2013-01-01
Preconditioners based upon sweeps and diffusion-synthetic acceleration have been constructed and applied to the zeroth and first spatial moments of the 1-D S n transport equation using a strictly non negative nonlinear spatial closure. Linear and nonlinear preconditioners have been analyzed. The effectiveness of various combinations of these preconditioners are compared. In one dimension, nonlinear sweep preconditioning is shown to be superior to linear sweep preconditioning, and DSA preconditioning using nonlinear sweeps in conjunction with a linear diffusion equation is found to be essentially equivalent to nonlinear sweeps in conjunction with a nonlinear diffusion equation. The ability to use a linear diffusion equation has important implications for preconditioning the S n equations with a strictly non negative spatial discretization in multiple dimensions. (authors)
Rapamycin preconditioning attenuates transient focal cerebral ischemia/reperfusion injury in mice.
Yin, Lele; Ye, Shasha; Chen, Zhen; Zeng, Yaoying
2012-12-01
Rapamycin, an mTOR inhibitor and immunosuppressive agent in clinic, has protective effects on traumatic brain injury and neurodegenerative diseases. But, its effects on transient focal ischemia/reperfusion disease are not very clear. In this study, we examined the effects of rapamycin preconditioning on mice treated with middle cerebral artery occlusion/reperfusion operation (MCAO/R). We found that the rapamycin preconditioning by intrahippocampal injection 20 hr before MCAO/R significantly improved the survival rate and longevity of mice. It also decreased the neurological deficit score, infracted areas and brain edema. In addition, rapamycin preconditioning decreased the production of NF-κB, TNF-α, and Bax, but not Bcl-2, an antiapoptotic protein in the ischemic area. From these results, we may conclude that rapamycin preconditioning attenuate transient focal cerebral ischemia/reperfusion injury and inhibits apoptosis induced by MCAO/R in mice.
Nonlinear adaptive inverse control via the unified model neural network
Jeng, Jin-Tsong; Lee, Tsu-Tian
1999-03-01
In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.
Ischemic preconditioning improves mitochondrial tolerance to experimental calcium overload.
Crestanello, Juan A; Doliba, Nicolai M; Babsky, Andriy M; Doliba, Natalia M; Niibori, Koki; Whitman, Glenn J R; Osbakken, Mary D
2002-04-01
Ca(2+) overload leads to mitochondrial uncoupling, decreased ATP synthesis, and myocardial dysfunction. Pharmacologically opening of mitochondrial K(ATP) channels decreases mitochondrial Ca(2+) uptake, improving mitochondrial function during Ca(2+) overload. Ischemic preconditioning (IPC), by activating mitochondrial K(ATP) channels, may attenuate mitochondrial Ca(2+) overload and improve mitochondrial function during reperfusion. The purpose of these experiments was to study the effect of IPC (1) on mitochondrial function and (2) on mitochondrial tolerance to experimental Ca(2+) overload. Rat hearts (n = 6/group) were subjected to (a) 30 min of equilibration, 25 min of ischemia, and 30 min of reperfusion (Control) or (b) two 5-min episodes of ischemic preconditioning, 25 min of ischemia, and 30 min of reperfusion (IPC). Developed pressure (DP) was measured. Heart mitochondria were isolated at end-Equilibration (end-EQ) and at end-Reperfusion (end-RP). Mitochondrial respiratory function (state 2, oxygen consumption with substrate only; state 3, oxygen consumption stimulated by ADP; state 4, oxygen consumption after cessation of ADP phosphorylation; respiratory control index (RCI, state 3/state 4); rate of oxidative phosphorylation (ADP/Deltat), and ADP:O ratio) was measured with polarography using alpha-ketoglutarate as a substrate in the presence of different Ca(2+) concentrations (0 to 5 x 10(-7) M) to simulate Ca(2+) overload. IPC improved DP at end-RP. IPC did not improve preischemic mitochondrial respiratory function or preischemic mitochondrial response to Ca(2+) loading. IPC improved state 3, ADP/Deltat, and RCI during RP. Low Ca(2+) levels (0.5 and 1 x 10(-7) M) stimulated mitochondrial function in both groups predominantly in IPC. The Control group showed evidence of mitochondrial uncoupling at lower Ca(2+) concentrations (1 x 10(-7) M). IPC preserved state 3 at high Ca(2+) concentrations. The cardioprotective effect of IPC results, in part, from
Nonlinear Preconditioning and its Application in Multicomponent Problems
Liu, Lulu
2015-12-07
The Multiplicative Schwarz Preconditioned Inexact Newton (MSPIN) algorithm is presented as a complement to Additive Schwarz Preconditioned Inexact Newton (ASPIN). At an algebraic level, ASPIN and MSPIN are variants of the same strategy to improve the convergence of systems with unbalanced nonlinearities; however, they have natural complementarity in practice. MSPIN is naturally based on partitioning of degrees of freedom in a nonlinear PDE system by field type rather than by subdomain, where a modest factor of concurrency can be sacrificed for physically motivated convergence robustness. ASPIN, originally introduced for decompositions into subdomains, is natural for high concurrency and reduction of global synchronization. The ASPIN framework, as an option for the outermost solver, successfully handles strong nonlinearities in computational fluid dynamics, but is barely explored for the highly nonlinear models of complex multiphase flow with capillarity, heterogeneity, and complex geometry. In this dissertation, the fully implicit ASPIN method is demonstrated for a finite volume discretization based on incompressible two-phase reservoir simulators in the presence of capillary forces and gravity. Numerical experiments show that the number of global nonlinear iterations is not only scalable with respect to the number of processors, but also significantly reduced compared with the standard inexact Newton method with a backtracking technique. Moreover, the ASPIN method, in contrast with the IMPES method, saves overall execution time because of the savings in timestep size. We consider the additive and multiplicative types of inexact Newton algorithms in the field-split context, and we augment the classical convergence theory of ASPIN for the multiplicative case. Moreover, we provide the convergence analysis of the MSPIN algorithm. Under suitable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be
Key cognitive preconditions for the evolution of language.
Donald, Merlin
2017-02-01
Languages are socially constructed systems of expression, generated interactively in social networks, which can be assimilated by the individual brain as it develops. Languages co-evolved with culture, reflecting the changing complexity of human culture as it acquired the properties of a distributed cognitive system. Two key preconditions set the stage for the evolution of such cultures: a very general ability to rehearse and refine skills (evident early in hominin evolution in toolmaking), and the emergence of material culture as an external (to the brain) memory record that could retain and accumulate knowledge across generations. The ability to practice and rehearse skill provided immediate survival-related benefits in that it expanded the physical powers of early hominins, but the same adaptation also provided the imaginative substrate for a system of "mimetic" expression, such as found in ritual and pantomime, and in proto-words, which performed an expressive function somewhat like the home signs of deaf non-signers. The hominid brain continued to adapt to the increasing importance and complexity of culture as human interactions with material culture became more complex; above all, this entailed a gradual expansion in the integrative systems of the brain, especially those involved in the metacognitive supervision of self-performances. This supported a style of embodied mimetic imagination that improved the coordination of shared activities such as fire tending, but also in rituals and reciprocal mimetic games. The time-depth of this mimetic adaptation, and its role in both the construction and acquisition of languages, explains the importance of mimetic expression in the media, religion, and politics. Spoken language evolved out of voco-mimesis, and emerged long after the more basic abilities needed to refine skill and share intentions, probably coinciding with the common ancestor of sapient humans. Self-monitoring and self-supervised practice were necessary
Opioid-induced preconditioning: recent advances and future perspectives.
Peart, Jason N; Gross, Eric R; Gross, Garrett J
2005-01-01
Opioids, named by Acheson for compounds with morphine-like actions despite chemically distinct structures, have received much research interest, particularly for their central nervous system (CNS) actions involved in pain management, resulting in thousands of scientific papers focusing on their effects on the CNS and other organ systems. A more recent area which may have great clinical importance concerns the role of opioids, either endogenous or exogenous compounds, in limiting the pathogenesis of ischemia-reperfusion injury in heart and brain. The role of endogenous opioids in hibernation provides tantalizing evidence for the protective potential of opioids against ischemia or hypoxia. Mammalian hibernation, a distinct energy-conserving state, is associated with depletion of energy stores, intracellular acidosis and hypoxia, similar to those which occur during ischemia. However, despite the potentially detrimental cellular state induced with hibernation, the myocardium remains resilient for many months. What accounts for the hypoxia-tolerant state is of great interest. During hibernation, circulating levels of opioid peptides are increased dramatically, and indeed, are considered a "trigger" of hibernation. Furthermore, administration of opioid antagonists can effectively reverse hibernation in mammals. Therefore, it is not surprising that activation of opioid receptors has been demonstrated to preserve cellular status following a hypoxic insult, such as ischemia-reperfusion in many model systems including the intestine [Zhang, Y., Wu, Y.X., Hao, Y.B., Dun, Y. Yang, S.P., 2001. Role of endogenous opioid peptides in protection of ischemic preconditioning in rat small intestine. Life Sci. 68, 1013-1019], skeletal muscle [Addison, P.D., Neligan, P.C., Ashrafpour, H., Khan, A., Zhong, A., Moses, M., Forrest, C.R., Pang, C.Y., 2003. Noninvasive remote ischemic preconditioning for global protection of skeletal muscle against infarction. Am. J. Physiol. Heart Circ
Wang, Peng-Fei; Xiong, Xiao-Yi; Chen, Jing; Wang, Yan-Chun; Duan, Wei; Yang, Qing-Wu
2015-01-01
Increasing evidence suggests that toll-like receptors (TLRs) play an important role in cerebral ischemia-reperfusion injury. The endogenous ligands released from ischemic neurons activate the TLR signaling pathway, resulting in the production of a large number of inflammatory cytokines, thereby causing secondary inflammation damage following cerebral ischemia. However, the preconditioning for minor cerebral ischemia or the preconditioning with TLR ligands can reduce cerebral ischemic injury b...
Directory of Open Access Journals (Sweden)
Ahmad Sukari Halim
2013-11-01
Full Text Available BackgroundIschemic preconditioning has been shown to improve the outcomes of hypoxic tolerance of the heart, brain, lung, liver, jejunum, skin, and muscle tissues. However, to date, no report of ischemic preconditioning on vascularized bone grafts has been published.MethodsSixteen rabbits were divided into four groups with ischemic times of 2, 6, 14, and 18 hours. Half of the rabbits in each group underwent ischemic preconditioning. The osteomyocutaneous flaps consisted of the tibia bone, from which the overlying muscle and skin were raised. The technique of ischemic preconditioning involved applying a vascular clamp to the pedicle for 3 cycles of 10 minutes each. The rabbits then underwent serial plain radiography and computed tomography imaging on the first, second, fourth, and sixth postoperative weeks. Following this, all of the rabbits were sacrificed and histological examinations were performed.ResultsThe results showed that for clinical analysis of the skin flaps and bone grafts, the preconditioned groups showed better survivability. In the plain radiographs, except for two non-preconditioned rabbits with intraoperative ischemic times of 6 hours, all began to show early callus formation at the fourth week. The computed tomography findings showed more callus formation in the preconditioned groups for all of the ischemic times except for the 18-hour group. The histological findings correlated with the radiological findings. There was no statistical significance in the difference between the two groups.ConclusionsIn conclusion, ischemic preconditioning improved the survivability of skin flaps and increased callus formation during the healing process of vascularized bone grafts.
Rethinking The Going Concern Assumption As A Pre-Condition For Accounting Measurement
Saratiel Wedzerai Musvoto; Daan G Gouws
2011-01-01
This study compares the principles of the going concern concept against the principles of representational measurement to determine if it is possible to establish foundations of accounting measurement with the going concern concept as a precondition. Representational measurement theory is a theory that establishes measurement in social scientific disciplines such as accounting. The going concern assumption is prescribed as one of the preconditions for measuring the attributes of the elements ...
Self-similar factor approximants
International Nuclear Information System (INIS)
Gluzman, S.; Yukalov, V.I.; Sornette, D.
2003-01-01
The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving an improved type of approximants. The derivation is based on the self-similar approximation theory, which presents the passage from one approximant to another as the motion realized by a dynamical system with the property of group self-similarity. The derived approximants, because of their form, are called self-similar factor approximants. These complement the obtained earlier self-similar exponential approximants and self-similar root approximants. The specific feature of self-similar factor approximants is that their control functions, providing convergence of the computational algorithm, are completely defined from the accuracy-through-order conditions. These approximants contain the Pade approximants as a particular case, and in some limit they can be reduced to the self-similar exponential approximants previously introduced by two of us. It is proved that the self-similar factor approximants are able to reproduce exactly a wide class of functions, which include a variety of nonalgebraic functions. For other functions, not pertaining to this exactly reproducible class, the factor approximants provide very accurate approximations, whose accuracy surpasses significantly that of the most accurate Pade approximants. This is illustrated by a number of examples showing the generality and accuracy of the factor approximants even when conventional techniques meet serious difficulties
An, Gary C; Faeder, James R
2009-01-01
preconditioning behavior with increasing LPS at 10, 100, 1000 and 10,000 and a secondary dose of LPS at 10,000 administered at approximately 27h of simulated time. Simulations of 'knockout' versions of the model allowed further examination of the interactions within the signaling cascade. The model demonstrated a dose-dependent TNF response curve to increasing stimulus by LPS. Preconditioning simulations demonstrated a similar dose-dependency of preconditioning doses leading to attenuation of response to subsequent LPS challenge - a 'tolerance' dynamic. These responses match dynamics reported in the literature. Furthermore, the simulated 'knockout' results suggested the existence and need for dual negative feedback control mechanisms, represented by the zinc ring-finger protein A20 and inhibitor kappa B proteins (IkappaB), in order for both effective attenuation of the initial stimulus signal and subsequent preconditioned 'tolerant' behavior. We present an example of detailed, qualitative dynamic knowledge representation using the TLR-4 signaling pathway, its control mechanisms and overall behavior with respect to preconditioning. The intent of this approach is to demonstrate a method of translating the extensive mechanistic knowledge being generated at the basic science level into an executable framework that can provide a means of 'conceptual model verification.' This allows for both the 'checking' of the dynamic consequences of a mechanistic hypothesis and the creation of a modular component of an overall model directed at the engineering goal of biomedical research. It is hoped that this paper will increase the use of knowledge representation and communication in this fashion, and facilitate the concatenation and integration of community-wide knowledge.
Directory of Open Access Journals (Sweden)
Norio Saga
2008-03-01
Full Text Available The purpose of this study was to clarify whether heat preconditioning results in less eccentric exercise-induced muscle damage and muscle soreness, and whether the repeated bout effect is enhanced by heat preconditioning prior to eccentric exercise. Nine untrained male volunteers aged 23 ± 3 years participated in this study. Heat preconditioning included treatment with a microwave hyperthermia unit (150 W, 20 min that was randomly applied to one of the subject's arms (MW; the other arm was used as a control (CON. One day after heat preconditioning, the subjects performed 24 maximal isokinetic eccentric contractions of the elbow flexors at 30°·s-1 (ECC1. One week after ECC1, the subjects repeated the procedure (ECC2. After each bout of exercise, maximal voluntary contraction (MVC, range of motion (ROM of the elbow joint, upper arm circumference, blood creatine kinase (CK activity and muscle soreness were measured. The subjects experienced both conditions at an interval of 3 weeks. MVC and ROM in the MW were significantly higher than those in the CON (p < 0.05 for ECC1; however, the heat preconditioning had no significant effect on upper arm circumference, blood CK activity, or muscle soreness following ECC1 and ECC2. Heat preconditioning may protect human skeletal muscle from eccentric exercise-induced muscle damage after a single bout of eccentric exercise but does not appear to promote the repeated bout effect after a second bout of eccentric exercise
Directory of Open Access Journals (Sweden)
Grace G. Abdukeyum
2016-03-01
Full Text Available Reactive oxygen species paradoxically underpin both ischaemia/reperfusion (I/R damage and ischaemic preconditioning (IPC cardioprotection. Long-chain omega-3 polyunsaturated fatty acids (LCn-3 PUFA are highly susceptible to peroxidation, but are paradoxically cardioprotective. This study tested the hypothesis that LCn-3 PUFA cardioprotection is underpinned by peroxidation, upregulating antioxidant activity to reduce I/R-induced lipid oxidation, and the mechanisms of this nutritional preconditioning contrast to mechanisms of IPC. Rats were fed: fish oil (LCn-3 PUFA; sunflower seed oil (n-6 PUFA; or beef tallow (saturated fat, SF enriched diets for six weeks. Isolated hearts were subject to: 180 min normoxic perfusion; a 30 min coronary occlusion ischaemia protocol then 120 min normoxic reperfusion; or a 3 × 5 min global IPC protocol, 30 min ischaemia, then reperfusion. Dietary LCn-3 PUFA raised basal: membrane docosahexaenoic acid (22:6n-3 DHA; fatty acid peroxidisability index; concentrations of lipid oxidation products; and superoxide dismutase (MnSOD activity (but not CuZnSOD or glutathione peroxidase. Infarct size correlated inversely with basal MnSOD activity (r2 = 0.85 in the ischaemia protocol and positively with I/R-induced lipid oxidation (lipid hydroperoxides (LPO, r2 = 0.475; malondialdehyde (MDA, r2 = 0.583 across ischaemia and IPC protocols. While both dietary fish oil and IPC infarct-reduction were associated with reduced I/R-induced lipid oxidation, fish oil produced nutritional preconditioning by prior LCn-3 PUFA incorporation and increased peroxidisability leading to up-regulated mitochondrial SOD antioxidant activity.
Inverse design of multicomponent assemblies
Piñeros, William D.; Lindquist, Beth A.; Jadrich, Ryan B.; Truskett, Thomas M.
2018-03-01
Inverse design can be a useful strategy for discovering interactions that drive particles to spontaneously self-assemble into a desired structure. Here, we extend an inverse design methodology—relative entropy optimization—to determine isotropic interactions that promote assembly of targeted multicomponent phases, and we apply this extension to design interactions for a variety of binary crystals ranging from compact triangular and square architectures to highly open structures with dodecagonal and octadecagonal motifs. We compare the resulting optimized (self- and cross) interactions for the binary assemblies to those obtained from optimization of analogous single-component systems. This comparison reveals that self-interactions act as a "primer" to position particles at approximately correct coordination shell distances, while cross interactions act as the "binder" that refines and locks the system into the desired configuration. For simpler binary targets, it is possible to successfully design self-assembling systems while restricting one of these interaction types to be a hard-core-like potential. However, optimization of both self- and cross interaction types appears necessary to design for assembly of more complex or open structures.
Prolonged preconditioning with natural honey against myocardial infarction injuries.
Eteraf-Oskouei, Tahereh; Shaseb, Elnaz; Ghaffary, Saba; Najafi, Moslem
2013-07-01
Potential protective effects of prolonged preconditioning with natural honey against myocardial infarction were investigated. Male Wistar rats were pre-treated with honey (1%, 2% and 4%) for 45 days then their hearts were isolated and mounted on a Langendorff apparatus and perfused with a modified Krebs-Henseleit solution during 30 min regional ischemia fallowed by 120 min reperfusion. Two important indexes of ischemia-induced damage (infarction size and arrhythmias) were determined by computerized planimetry and ECG analysis, respectively. Honey (1% and 2%) reduced infarct size from 23±3.1% (control) to 9.7±2.4 and 9.5±2.3%, respectively (Phoney (1%) significantly reduced (PHoney (1% and 2%) also significantly decreased number of ventricular ectopic beats (VEBs). In addition, incidence and duration of reversible ventricular fibrillation (Rev VF) were lowered by honey 2% (Phoney produced significant reduction in the incidences of VT, total and Rev VF, duration and number of VT. The results showed cardioprotective effects of prolonged pre-treatment of rats with honey following myocardial infarction. Maybe, the existence of antioxidants and energy sources (glucose and fructose) in honey composition and improvement of hemodynamic functions may involve in those protective effects.
Sirtinol abrogates late phase of cardiac ischemia preconditioning in rats.
Safari, Fereshteh; Shekarforoosh, Shahnaz; Hashemi, Tahmineh; Namvar Aghdash, Simin; Fekri, Asefeh; Safari, Fatemeh
2017-07-01
The aim of this study was to investigate the effect of sirtinol, as an inhibitor of sirtuin NAD-dependent histone deacetylases, on myocardial ischemia reperfusion injury following early and late ischemia preconditioning (IPC). Rats underwent sustained ischemia and reperfusion (IR) alone or proceeded by early or late IPC. Sirtinol (S) was administered before IPC. Arrhythmias were evaluated based on the Lambeth model. Infarct size (IS) was measured using triphenyltetrazolium chloride staining. The transcription level of antioxidant-coding genes was assessed by real-time PCR. In early and late IPC groups, IS and the number of arrhythmia were significantly decreased (P < 0.05 and P < 0.01 vs IR, respectively). In S + early IPC, incidences of arrhythmia and IS were not different compared with the early IPC group. However, in S + late IPC the IS was different from the late IPC group (P < 0.05). In late IPC but not early IPC, transcription levels of catalase (P < 0.01) and Mn-SOD (P < 0.05) increased, although this upregulation was not significant in the S + late IPC group. Our results are consistent with the notion that different mechanisms are responsible for early and late IPC. In addition, sirtuin NAD-dependent histone deacetylases may be implicated in late IPC-induced cardioprotection.
Linear multifrequency-grey acceleration recast for preconditioned Krylov iterations
International Nuclear Information System (INIS)
Morel, Jim E.; Brian Yang, T.-Y.; Warsa, James S.
2007-01-01
The linear multifrequency-grey acceleration (LMFGA) technique is used to accelerate the iterative convergence of multigroup thermal radiation diffusion calculations in high energy density simulations. Although it is effective and efficient in one-dimensional calculations, the LMFGA method has recently been observed to significantly degrade under certain conditions in multidimensional calculations with large discontinuities in material properties. To address this deficiency, we recast the LMFGA method in terms of a preconditioned system that is solved with a Krylov method (LMFGK). Results are presented demonstrating that the new LMFGK method always requires fewer iterations than the original LMFGA method. The reduction in iteration count increases with both the size of the time step and the inhomogeneity of the problem. However, for reasons later explained, the LMFGK method can cost more per iteration than the LMFGA method, resulting in lower but comparable efficiency in problems with small time steps and weak inhomogeneities. In problems with large time steps and strong inhomogeneities, the LMFGK method is significantly more efficient than the LMFGA method
Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit
Liu, Haixiao; Hu, Zhenhua; Wang, Kun; Tian, Jie; Yang, Xin
2015-03-01
Cerenkov luminescence imaging (CLI) is a novel optical imaging method and has been proved to be a potential substitute of the traditional radionuclide imaging such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). This imaging method inherits the high sensitivity of nuclear medicine and low cost of optical molecular imaging. To obtain the depth information of the radioactive isotope, Cerenkov luminescence tomography (CLT) is established and the 3D distribution of the isotope is reconstructed. However, because of the strong absorption and scatter, the reconstruction of the CLT sources is always converted to an ill-posed linear system which is hard to be solved. In this work, the sparse nature of the light source was taken into account and the preconditioning orthogonal matching pursuit (POMP) method was established to effectively reduce the ill-posedness and obtain better reconstruction accuracy. To prove the accuracy and speed of this algorithm, a heterogeneous numerical phantom experiment and an in vivo mouse experiment were conducted. Both the simulation result and the mouse experiment showed that our reconstruction method can provide more accurate reconstruction result compared with the traditional Tikhonov regularization method and the ordinary orthogonal matching pursuit (OMP) method. Our reconstruction method will provide technical support for the biological application for Cerenkov luminescence.
Deregulation - precondition for distributed energy in the economies in transition
International Nuclear Information System (INIS)
Brendow, K.
2001-01-01
This paper holds that deregulation, i.e. restructuring, competition and privatisation, is the main precondition for a more pronounced development of distributed power (DP) in the economies in transition in central and eastern Europe. This, then, raises the question how far the electricity, gas, steam and heat generating industries have presently moved on their way towards more market-oriented frameworks, competition and private ownership. A good benchmark for measuring progress is the existence (or lack thereof), and nature, of regulatory regimes enabling fair competition among large centralised and small decentralised power, and between wholesale generators and distributors on the one hand and customers or ''autoproducers'' or power merchants on the other. The paper describes the regulatory models applied or contemplated in the winter 2000/2001 in the various countries of central and eastern Europe and identifies fifteen general issues that require attention and solution. With regard to DP, it concludes that a major upswing is unlikely to occur before 2005-2008. While technological options abound, the institutional frameworks for customer-owned competitive DP systems are only being contemplated at present and only rarely put in place.(author)
FALCON Code Simulation for Verification of Fuel Preconditioning Guideline
Energy Technology Data Exchange (ETDEWEB)
Lee, Hee-Hun; Kwon, Oh-Hyun; Kim, Hong-Jin; Kim, Yong-Hwan [KEPCO Nuclear Fuel Co. Ltd., Daejeon (Korea, Republic of)
2015-10-15
The magnitude and rate of power increases are key factors in the PCI failure process. KEPCO NF (KNF) provides operational restrictions called fuel preconditioning guideline (FPG) to mitigate PCI failures. The FPG contains recommended power maneuvering restrictions that should be followed when the KNF supplied fuel is being operated in-reactor. This guideline typically includes controlled power ramp rates, threshold power levels to initiate controlled ramp rates, and restrictions on the operating conditions that impact the potential for PCI failure. The purpose of the FPG is to allow time for stress relaxation to reduce cladding stress buildup during power maneuvers. Two general approaches have been adopted in the development of FPG to mitigate PCI failure in operating commercial reactors. The first approach relies primarily on past operational experience and power ramp test. The second one uses an analytical methodology where a figure-of-merit representative of PCI vulnerability, generally cladding hoop stress, is calculated using a fuel performance code. FALCON simulation can be the identification of a PCI limit parameter, typically cladding hoop stress, which can be used to evaluate a power maneuvering restriction on FPG. The PCI analysis is to assess the cladding hoop stress under various power ramp conditions. Startup ramp rate doesn't affect PCI failure until 50% of rated thermal power.
Preconditioned augmented Lagrangian formulation for nearly incompressible cardiac mechanics.
Campos, Joventino Oliveira; Dos Santos, Rodrigo Weber; Sundnes, Joakim; Rocha, Bernardo Martins
2018-04-01
Computational modeling of the heart is a subject of substantial medical and scientific interest, which may contribute to increase the understanding of several phenomena associated with cardiac physiological and pathological states. Modeling the mechanics of the heart have led to considerable insights, but it still represents a complex and a demanding computational problem, especially in a strongly coupled electromechanical setting. Passive cardiac tissue is commonly modeled as hyperelastic and is characterized by quasi-incompressible, orthotropic, and nonlinear material behavior. These factors are known to be very challenging for the numerical solution of the model. The near-incompressibility is known to cause numerical issues such as the well-known locking phenomenon and ill-conditioning of the stiffness matrix. In this work, the augmented Lagrangian method is used to handle the nearly incompressible condition. This approach can potentially improve computational performance by reducing the condition number of the stiffness matrix and thereby improving the convergence of iterative solvers. We also improve the performance of iterative solvers by the use of an algebraic multigrid preconditioner. Numerical results of the augmented Lagrangian method combined with a preconditioned iterative solver for a cardiac mechanics benchmark suite are presented to show its improved performance. Copyright © 2017 John Wiley & Sons, Ltd.
Action understanding as inverse planning.
Baker, Chris L; Saxe, Rebecca; Tenenbaum, Joshua B
2009-12-01
Humans are adept at inferring the mental states underlying other agents' actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents' behavior based on the principle of rationality: the expectation that agents will plan approximately rationally to achieve their goals, given their beliefs about the world. The mental states that caused an agent's behavior are inferred by inverting this model of rational planning using Bayesian inference, integrating the likelihood of the observed actions with the prior over mental states. This approach formalizes in precise probabilistic terms the essence of previous qualitative approaches to action understanding based on an "intentional stance" [Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press] or a "teleological stance" [Gergely, G., Nádasdy, Z., Csibra, G., & Biró, S. (1995). Taking the intentional stance at 12 months of age. Cognition, 56, 165-193]. In three psychophysical experiments using animated stimuli of agents moving in simple mazes, we assess how well different inverse planning models based on different goal priors can predict human goal inferences. The results provide quantitative evidence for an approximately rational inference mechanism in human goal inference within our simplified stimulus paradigm, and for the flexible nature of goal representations that human observers can adopt. We discuss the implications of our experimental results for human action understanding in real-world contexts, and suggest how our framework might be extended to capture other kinds of mental state inferences, such as inferences about beliefs, or inferring whether an entity is an intentional agent.
Impurity levels: corrections to the effective mass approximation
International Nuclear Information System (INIS)
Bentosela, F.
1977-07-01
Some rigorous results concerning the effective mass approximation used for the calculation of the impurity levels in semiconductors are presented. Each energy level is expressed as an asymptotic series in the inverse of the dielectric constant K, in the case where the impurity potential is 1/μ
Approximation of reliability of direct genomic breeding values
Two methods to efficiently approximate theoretical genomic reliabilities are presented. The first method is based on the direct inverse of the left hand side (LHS) of mixed model equations. It uses the genomic relationship matrix for a small subset of individuals with the highest genomic relationshi...
Sinc-Approximations of Fractional Operators: A Computing Approach
Directory of Open Access Journals (Sweden)
Gerd Baumann
2015-06-01
Full Text Available We discuss a new approach to represent fractional operators by Sinc approximation using convolution integrals. A spin off of the convolution representation is an effective inverse Laplace transform. Several examples demonstrate the application of the method to different practical problems.
International Conference Approximation Theory XV
Schumaker, Larry
2017-01-01
These proceedings are based on papers presented at the international conference Approximation Theory XV, which was held May 22–25, 2016 in San Antonio, Texas. The conference was the fifteenth in a series of meetings in Approximation Theory held at various locations in the United States, and was attended by 146 participants. The book contains longer survey papers by some of the invited speakers covering topics such as compressive sensing, isogeometric analysis, and scaling limits of polynomials and entire functions of exponential type. The book also includes papers on a variety of current topics in Approximation Theory drawn from areas such as advances in kernel approximation with applications, approximation theory and algebraic geometry, multivariate splines for applications, practical function approximation, approximation of PDEs, wavelets and framelets with applications, approximation theory in signal processing, compressive sensing, rational interpolation, spline approximation in isogeometric analysis, a...
DEFF Research Database (Denmark)
Mosegaard, Klaus
2012-01-01
For non-linear inverse problems, the mathematical structure of the mapping from model parameters to data is usually unknown or partly unknown. Absence of information about the mathematical structure of this function prevents us from presenting an analytical solution, so our solution depends on our......-heuristics are inefficient for large-scale, non-linear inverse problems, and that the 'no-free-lunch' theorem holds. We discuss typical objections to the relevance of this theorem. A consequence of the no-free-lunch theorem is that algorithms adapted to the mathematical structure of the problem perform more efficiently than...... pure meta-heuristics. We study problem-adapted inversion algorithms that exploit the knowledge of the smoothness of the misfit function of the problem. Optimal sampling strategies exist for such problems, but many of these problems remain hard. © 2012 Springer-Verlag....
Inverse scale space decomposition
DEFF Research Database (Denmark)
Schmidt, Marie Foged; Benning, Martin; Schönlieb, Carola-Bibiane
2018-01-01
We investigate the inverse scale space flow as a decomposition method for decomposing data into generalised singular vectors. We show that the inverse scale space flow, based on convex and even and positively one-homogeneous regularisation functionals, can decompose data represented...... by the application of a forward operator to a linear combination of generalised singular vectors into its individual singular vectors. We verify that for this decomposition to hold true, two additional conditions on the singular vectors are sufficient: orthogonality in the data space and inclusion of partial sums...... of the subgradients of the singular vectors in the subdifferential of the regularisation functional at zero. We also address the converse question of when the inverse scale space flow returns a generalised singular vector given that the initial data is arbitrary (and therefore not necessarily in the range...
Generalized inverses theory and computations
Wang, Guorong; Qiao, Sanzheng
2018-01-01
This book begins with the fundamentals of the generalized inverses, then moves to more advanced topics. It presents a theoretical study of the generalization of Cramer's rule, determinant representations of the generalized inverses, reverse order law of the generalized inverses of a matrix product, structures of the generalized inverses of structured matrices, parallel computation of the generalized inverses, perturbation analysis of the generalized inverses, an algorithmic study of the computational methods for the full-rank factorization of a generalized inverse, generalized singular value decomposition, imbedding method, finite method, generalized inverses of polynomial matrices, and generalized inverses of linear operators. This book is intended for researchers, postdocs, and graduate students in the area of the generalized inverses with an undergraduate-level understanding of linear algebra.
Some results on inverse scattering
International Nuclear Information System (INIS)
Ramm, A.G.
2008-01-01
A review of some of the author's results in the area of inverse scattering is given. The following topics are discussed: (1) Property C and applications, (2) Stable inversion of fixed-energy 3D scattering data and its error estimate, (3) Inverse scattering with 'incomplete' data, (4) Inverse scattering for inhomogeneous Schroedinger equation, (5) Krein's inverse scattering method, (6) Invertibility of the steps in Gel'fand-Levitan, Marchenko, and Krein inversion methods, (7) The Newton-Sabatier and Cox-Thompson procedures are not inversion methods, (8) Resonances: existence, location, perturbation theory, (9) Born inversion as an ill-posed problem, (10) Inverse obstacle scattering with fixed-frequency data, (11) Inverse scattering with data at a fixed energy and a fixed incident direction, (12) Creating materials with a desired refraction coefficient and wave-focusing properties. (author)
A 2.5-D Diffraction Tomography Inversion Scheme for Ground Penetrating Radar
DEFF Research Database (Denmark)
Meincke, Peter
1999-01-01
A new 2.5-D inversion scheme is derived for ground penetrating radar (GPR) that applies to a monostatic fixed-offset measurement configuration. The inversion scheme, which is based upon the first Born approximation and the pseudo-inverse operator, takes rigorously into account the planar air...
Frequency Domain Multi-parameter Full Waveform Inversion for Acoustic VTI Media
Djebbi, Ramzi
2017-05-26
Multi-parameter full waveform inversion (FWI) for transversely isotropic (TI) media with vertical axis of symmetry (VTI) suffers from the trade-off between the parameters. The trade-off results in the leakage of one parameter\\'s update into the other during the inversion. It affects the accuracy and convergence of the inversion. The sensitivity analyses suggested a parameterisation using the horizontal velocity vh, epsilon and eta to reduce the trade-off for surface recorded seismic data.We test the (vh, epsilon, eta) parameterisation for acoustic VTI media using a scattering integral (SI) based inversion. The data is modeled in frequency domain and the model is updated using a preconditioned conjugate gradient method. We applied the method to the VTI Marmousi II model and in the inversion, we keep eta parameter fixed as the background initial model and we invert simultaneously for both vh and epsilon. The results show the suitability of the parameterisation for multi-parameter VTI acoustic inversion as well as the accuracy of the inversion approach.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-01
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-07
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Three-dimensional inversion of multisource array electromagnetic data
Tartaras, Efthimios
Three-dimensional (3-D) inversion is increasingly important for the correct interpretation of geophysical data sets in complex environments. To this effect, several approximate solutions have been developed that allow the construction of relatively fast inversion schemes. One such method that is fast and provides satisfactory accuracy is the quasi-linear (QL) approximation. It has, however, the drawback that it is source-dependent and, therefore, impractical in situations where multiple transmitters in different positions are employed. I have, therefore, developed a localized form of the QL approximation that is source-independent. This so-called localized quasi-linear (LQL) approximation can have a scalar, a diagonal, or a full tensor form. Numerical examples of its comparison with the full integral equation solution, the Born approximation, and the original QL approximation are given. The objective behind developing this approximation is to use it in a fast 3-D inversion scheme appropriate for multisource array data such as those collected in airborne surveys, cross-well logging, and other similar geophysical applications. I have developed such an inversion scheme using the scalar and diagonal LQL approximation. It reduces the original nonlinear inverse electromagnetic (EM) problem to three linear inverse problems. The first of these problems is solved using a weighted regularized linear conjugate gradient method, whereas the last two are solved in the least squares sense. The algorithm I developed provides the option of obtaining either smooth or focused inversion images. I have applied the 3-D LQL inversion to synthetic 3-D EM data that simulate a helicopter-borne survey over different earth models. The results demonstrate the stability and efficiency of the method and show that the LQL approximation can be a practical solution to the problem of 3-D inversion of multisource array frequency-domain EM data. I have also applied the method to helicopter-borne EM
Angle-domain inverse scattering migration/inversion in isotropic media
Li, Wuqun; Mao, Weijian; Li, Xuelei; Ouyang, Wei; Liang, Quan
2018-07-01
The classical seismic asymptotic inversion can be transformed into a problem of inversion of generalized Radon transform (GRT). In such methods, the combined parameters are linearly attached to the scattered wave-field by Born approximation and recovered by applying an inverse GRT operator to the scattered wave-field data. Typical GRT-style true-amplitude inversion procedure contains an amplitude compensation process after the weighted migration via dividing an illumination associated matrix whose elements are integrals of scattering angles. It is intuitional to some extent that performs the generalized linear inversion and the inversion of GRT together by this process for direct inversion. However, it is imprecise to carry out such operation when the illumination at the image point is limited, which easily leads to the inaccuracy and instability of the matrix. This paper formulates the GRT true-amplitude inversion framework in an angle-domain version, which naturally degrades the external integral term related to the illumination in the conventional case. We solve the linearized integral equation for combined parameters of different fixed scattering angle values. With this step, we obtain high-quality angle-domain common-image gathers (CIGs) in the migration loop which provide correct amplitude-versus-angle (AVA) behavior and reasonable illumination range for subsurface image points. Then we deal with the over-determined problem to solve each parameter in the combination by a standard optimization operation. The angle-domain GRT inversion method keeps away from calculating the inaccurate and unstable illumination matrix. Compared with the conventional method, the angle-domain method can obtain more accurate amplitude information and wider amplitude-preserved range. Several model tests demonstrate the effectiveness and practicability.
Bayesian probability theory and inverse problems
International Nuclear Information System (INIS)
Kopec, S.
1994-01-01
Bayesian probability theory is applied to approximate solving of the inverse problems. In order to solve the moment problem with the noisy data, the entropic prior is used. The expressions for the solution and its error bounds are presented. When the noise level tends to zero, the Bayesian solution tends to the classic maximum entropy solution in the L 2 norm. The way of using spline prior is also shown. (author)
An inverse problem in a parabolic equation
Directory of Open Access Journals (Sweden)
Zhilin Li
1998-11-01
Full Text Available In this paper, an inverse problem in a parabolic equation is studied. An unknown function in the equation is related to two integral equations in terms of heat kernel. One of the integral equations is well-posed while another is ill-posed. A regularization approach for constructing an approximate solution to the ill-posed integral equation is proposed. Theoretical analysis and numerical experiment are provided to support the method.
Forms of Approximate Radiation Transport
Brunner, G
2002-01-01
Photon radiation transport is described by the Boltzmann equation. Because this equation is difficult to solve, many different approximate forms have been implemented in computer codes. Several of the most common approximations are reviewed, and test problems illustrate the characteristics of each of the approximations. This document is designed as a tutorial so that code users can make an educated choice about which form of approximate radiation transport to use for their particular simulation.
Hyperbaric oxygen preconditioning protects against traumatic brain injury at high altitude.
Hu, S L; Hu, R; Li, F; Liu, Z; Xia, Y Z; Cui, G Y; Feng, H
2008-01-01
Recent studies have shown that preconditioning with hyperbaric oxygen (HBO) can reduce ischemic and hemorrhagic brain injury. We investigated effects of HBO preconditioning on traumatic brain injury (TBI) at high altitude and examined the role of matrix metalloproteinase-9 (MMP-9) in such protection. Rats were randomly divided into 3 groups: HBO preconditioning group (HBOP; n = 13), high-altitude group (HA; n = 13), and high-altitude sham operation group (HASO; n = 13). All groups were subjected to head trauma by weight-drop device, except for HASO group. HBOP rats received 5 sessions of HBO preconditioning (2.5 ATA, 100% oxygen, 1 h daily) and then were kept in hypobaric chamber at 0.6 ATA (to simulate pressure at 4000m altitude) for 3 days before operation. HA rats received control pretreatment (1 ATA, room air, 1 h daily), then followed the same procedures as HBOP group. HASO rats were subjected to skull opening only without brain injury. Twenty-four hours after TBI, 7 rats from each group were examined for neurological function and brain water content; 6 rats from each group were killed for analysis by H&E staining and immunohistochemistry. Neurological outcome in HBOP group (0.71 +/- 0.49) was better than HA group (1.57 +/- 0.53; p < 0.05). Preconditioning with HBO significantly reduced percentage of brain water content (86.24 +/- 0.52 vs. 84.60 +/- 0.37; p < 0.01). Brain morphology and structure seen by light microscopy was diminished in HA group, while fewer pathological injuries occurred in HBOP group. Compared to HA group, pretreatment with HBO significantly reduced the number of MMP-9-positive cells (92.25 +/- 8.85 vs. 74.42 +/- 6.27; p < 0.01). HBO preconditioning attenuates TBI in rats at high altitude. Decline in MMP-9 expression may contribute to HBO preconditioning-induced protection of brain tissue against TBI.
Approximation by planar elastic curves
DEFF Research Database (Denmark)
Brander, David; Gravesen, Jens; Nørbjerg, Toke Bjerge
2016-01-01
We give an algorithm for approximating a given plane curve segment by a planar elastic curve. The method depends on an analytic representation of the space of elastic curve segments, together with a geometric method for obtaining a good initial guess for the approximating curve. A gradient......-driven optimization is then used to find the approximating elastic curve....
Inversion assuming weak scattering
DEFF Research Database (Denmark)
Xenaki, Angeliki; Gerstoft, Peter; Mosegaard, Klaus
2013-01-01
due to the complex nature of the field. A method based on linear inversion is employed to infer information about the statistical properties of the scattering field from the obtained cross-spectral matrix. A synthetic example based on an active high-frequency sonar demonstrates that the proposed...
Preconditioning with endoplasmic reticulum stress ameliorates endothelial cell inflammation.
Leonard, Antony; Paton, Adrienne W; El-Quadi, Monaliza; Paton, James C; Fazal, Fabeha
2014-01-01
Endoplasmic Reticulum (ER) stress, caused by disturbance in ER homeostasis, has been implicated in several pathological conditions such as ischemic injury, neurodegenerative disorders, metabolic diseases and more recently in inflammatory conditions. Our present study aims at understanding the role of ER stress in endothelial cell (EC) inflammation, a critical event in the pathogenesis of acute lung injury (ALI). We found that preconditioning human pulmonary artery endothelial cells (HPAEC) to ER stress either by depleting ER chaperone and signaling regulator BiP using siRNA, or specifically cleaving (inactivating) BiP using subtilase cytotoxin (SubAB), alleviates EC inflammation. The two approaches adopted to abrogate BiP function induced ATF4 protein expression and the phosphorylation of eIF2α, both markers of ER stress, which in turn resulted in blunting the activation of NF-κB, and restoring endothelial barrier integrity. Pretreatment of HPAEC with BiP siRNA inhibited thrombin-induced IκBα degradation and its resulting downstream signaling pathway involving NF-κB nuclear translocation, DNA binding, phosphorylation at serine536, transcriptional activation and subsequent expression of adhesion molecules. However, TNFα-mediated NF-κB signaling was unaffected upon BiP knockdown. In an alternative approach, SubAB-mediated inactivation of NF-κB was independent of IκBα degradation. Mechanistic analysis revealed that pretreatment of EC with SubAB interfered with the binding of the liberated NF-κB to the DNA, thereby resulting in reduced expression of adhesion molecules, cytokines and chemokines. In addition, both knockdown and inactivation of BiP stimulated actin cytoskeletal reorganization resulting in restoration of endothelial permeability. Together our studies indicate that BiP plays a central role in EC inflammation and injury via its action on NF-κB activation and regulation of vascular permeability.
Preconditioning of Interplanetary Space Due to Transient CME Disturbances
International Nuclear Information System (INIS)
Temmer, M.; Reiss, M. A.; Hofmeister, S. J.; Veronig, A. M.; Nikolic, L.
2017-01-01
Interplanetary space is characteristically structured mainly by high-speed solar wind streams emanating from coronal holes and transient disturbances such as coronal mass ejections (CMEs). While high-speed solar wind streams pose a continuous outflow, CMEs abruptly disrupt the rather steady structure, causing large deviations from the quiet solar wind conditions. For the first time, we give a quantification of the duration of disturbed conditions (preconditioning) for interplanetary space caused by CMEs. To this aim, we investigate the plasma speed component of the solar wind and the impact of in situ detected interplanetary CMEs (ICMEs), compared to different background solar wind models (ESWF, WSA, persistence model) for the time range 2011–2015. We quantify in terms of standard error measures the deviations between modeled background solar wind speed and observed solar wind speed. Using the mean absolute error, we obtain an average deviation for quiet solar activity within a range of 75.1–83.1 km s −1 . Compared to this baseline level, periods within the ICME interval showed an increase of 18%–32% above the expected background, and the period of two days after the ICME displayed an increase of 9%–24%. We obtain a total duration of enhanced deviations over about three and up to six days after the ICME start, which is much longer than the average duration of an ICME disturbance itself (∼1.3 days), concluding that interplanetary space needs ∼2–5 days to recover from the impact of ICMEs. The obtained results have strong implications for studying CME propagation behavior and also for space weather forecasting.
Preconditioning of Interplanetary Space Due to Transient CME Disturbances
Energy Technology Data Exchange (ETDEWEB)
Temmer, M.; Reiss, M. A.; Hofmeister, S. J.; Veronig, A. M. [Institute of Physics, University of Graz, Universitätsplatz 5/II, A-8010 Graz (Austria); Nikolic, L., E-mail: manuela.temmer@uni-graz.at [Canadian Hazards Information Service, Natural Resources Canada, 2617 Anderson Road, Ottawa, Ontario K1A 0Y3 (Canada)
2017-02-01
Interplanetary space is characteristically structured mainly by high-speed solar wind streams emanating from coronal holes and transient disturbances such as coronal mass ejections (CMEs). While high-speed solar wind streams pose a continuous outflow, CMEs abruptly disrupt the rather steady structure, causing large deviations from the quiet solar wind conditions. For the first time, we give a quantification of the duration of disturbed conditions (preconditioning) for interplanetary space caused by CMEs. To this aim, we investigate the plasma speed component of the solar wind and the impact of in situ detected interplanetary CMEs (ICMEs), compared to different background solar wind models (ESWF, WSA, persistence model) for the time range 2011–2015. We quantify in terms of standard error measures the deviations between modeled background solar wind speed and observed solar wind speed. Using the mean absolute error, we obtain an average deviation for quiet solar activity within a range of 75.1–83.1 km s{sup −1}. Compared to this baseline level, periods within the ICME interval showed an increase of 18%–32% above the expected background, and the period of two days after the ICME displayed an increase of 9%–24%. We obtain a total duration of enhanced deviations over about three and up to six days after the ICME start, which is much longer than the average duration of an ICME disturbance itself (∼1.3 days), concluding that interplanetary space needs ∼2–5 days to recover from the impact of ICMEs. The obtained results have strong implications for studying CME propagation behavior and also for space weather forecasting.
Angiotensin II Removes Kidney Resistance Conferred by Ischemic Preconditioning
Directory of Open Access Journals (Sweden)
Hee-Seong Jang
2014-01-01
Full Text Available Ischemic preconditioning (IPC by ischemia/reperfusion (I/R renders resistance to the kidney. Strong IPC triggers kidney fibrosis, which is involved in angiotensin II (AngII and its type 1 receptor (AT1R signaling. Here, we investigated the role of AngII/AT1R signal pathway in the resistance of IPC kidneys to subsequent I/R injury. IPC of kidneys was generated by 30 minutes of bilateral renal ischemia and 8 days of reperfusion. Sham-operation was performed to generate control (non-IPC mice. To examine the roles of AngII and AT1R in IPC kidneys to subsequent I/R, IPC kidneys were subjected to either 30 minutes of bilateral kidney ischemia or sham-operation following treatment with AngII, losartan (AT1R blocker, or AngII plus losartan. IPC kidneys showed fibrotic changes, decreased AngII, and increased AT1R expression. I/R dramatically increased plasma creatinine concentrations in non-IPC mice, but not in IPC mice. AngII treatment in IPC mice resulted in enhanced morphological damage, oxidative stress, and inflammatory responses, with functional impairment, whereas losartan treatment reversed these effects. However, AngII treatment in non-IPC mice did not change I/R-induced injury. AngII abolished the resistance of IPC kidneys to subsequent I/R via the enhancement of oxidative stress and inflammatory responses, suggesting that the AngII/AT1R signaling pathway is associated with outcome in injury-experienced kidney.
Variational methods for direct/inverse problems of atmospheric dynamics and chemistry
Penenko, Vladimir; Penenko, Alexey; Tsvetova, Elena
2013-04-01
We present a variational approach for solving direct and inverse problems of atmospheric hydrodynamics and chemistry. It is important that the accurate matching of numerical schemes has to be provided in the chain of objects: direct/adjoint problems - sensitivity relations - inverse problems, including assimilation of all available measurement data. To solve the problems we have developed a new enhanced set of cost-effective algorithms. The matched description of the multi-scale processes is provided by a specific choice of the variational principle functionals for the whole set of integrated models. Then all functionals of variational principle are approximated in space and time by splitting and decomposition methods. Such approach allows us to separately consider, for example, the space-time problems of atmospheric chemistry in the frames of decomposition schemes for the integral identity sum analogs of the variational principle at each time step and in each of 3D finite-volumes. To enhance the realization efficiency, the set of chemical reactions is divided on the subsets related to the operators of production and destruction. Then the idea of the Euler's integrating factors is applied in the frames of the local adjoint problem technique [1]-[3]. The analytical solutions of such adjoint problems play the role of integrating factors for differential equations describing atmospheric chemistry. With their help, the system of differential equations is transformed to the equivalent system of integral equations. As a result we avoid the construction and inversion of preconditioning operators containing the Jacobi matrixes which arise in traditional implicit schemes for ODE solution. This is the main advantage of our schemes. At the same time step but on the different stages of the "global" splitting scheme, the system of atmospheric dynamic equations is solved. For convection - diffusion equations for all state functions in the integrated models we have developed the
Calculation of the inverse data space via sparse inversion
Saragiotis, Christos
2011-01-01
The inverse data space provides a natural separation of primaries and surface-related multiples, as the surface multiples map onto the area around the origin while the primaries map elsewhere. However, the calculation of the inverse data is far from trivial as theory requires infinite time and offset recording. Furthermore regularization issues arise during inversion. We perform the inversion by minimizing the least-squares norm of the misfit function by constraining the $ell_1$ norm of the solution, being the inverse data space. In this way a sparse inversion approach is obtained. We show results on field data with an application to surface multiple removal.
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander
2014-01-06
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander; Matthies, Hermann G.
2014-01-01
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inverse problems and uncertainty quantification
Litvinenko, Alexander
2013-12-18
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)— the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics
Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.
2003-09-01
Multiconjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wave-front control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10-2 Hz, i.e., 4-5 orders of magnitude lower than the typical 103 Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.
Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.
Gilles, Luc; Ellerbroek, Brent L; Vogel, Curtis R
2003-09-10
Multiconjugate adaptive optics (MCAO) systems with 10(4)-10(5) degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 10(4) actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10(-2) Hz, i.e., 4-5 orders of magnitude lower than the typical 10(3) Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.
Perturbation of eigenvalues of preconditioned Navier-Stokes operators
Energy Technology Data Exchange (ETDEWEB)
Elman, H.C. [Univ. of Maryland, College Park, MD (United States)
1996-12-31
We study the sensitivity of algebraic eigenvalue problems associated with matrices arising from linearization and discretization of the steady-state Navier-Stokes equations. In particular, for several choices of preconditioners applied to the system of discrete equations, we derive upper bounds on perturbations of eigenvalues as functions of the viscosity and discretization mesh size. The bounds suggest that the sensitivity of the eigenvalues is at worst linear in the inverse of the viscosity and quadratic in the inverse of the mesh size, and that scaling can be used to decrease the sensitivity in some cases. Experimental results supplement these results and confirm the relatively mild dependence on viscosity. They also indicate a dependence on the mesh size of magnitude smaller than the analysis suggests.
Exact constants in approximation theory
Korneichuk, N
1991-01-01
This book is intended as a self-contained introduction for non-specialists, or as a reference work for experts, to the particular area of approximation theory that is concerned with exact constants. The results apply mainly to extremal problems in approximation theory, which in turn are closely related to numerical analysis and optimization. The book encompasses a wide range of questions and problems: best approximation by polynomials and splines; linear approximation methods, such as spline-approximation; optimal reconstruction of functions and linear functionals. Many of the results are base
International Conference Approximation Theory XIV
Schumaker, Larry
2014-01-01
This volume developed from papers presented at the international conference Approximation Theory XIV, held April 7–10, 2013 in San Antonio, Texas. The proceedings contains surveys by invited speakers, covering topics such as splines on non-tensor-product meshes, Wachspress and mean value coordinates, curvelets and shearlets, barycentric interpolation, and polynomial approximation on spheres and balls. Other contributed papers address a variety of current topics in approximation theory, including eigenvalue sequences of positive integral operators, image registration, and support vector machines. This book will be of interest to mathematicians, engineers, and computer scientists working in approximation theory, computer-aided geometric design, numerical analysis, and related approximation areas.
Bispectral Inversion: The Construction of a Time Series from Its Bispectrum
1988-04-13
take the inverse transform . Since the goal is to compute a time series given its bispectrum, it would also be nice to stay entirely in the frequency...domain and be able to go directly from the bispectrum to the Fourier transform of the time series without the need to inverse transform continuous...the picture. The approximations arise from representing the bicovariance, which is the inverse transform of a continuous function, by the inverse disrte
The impact of approximations and arbitrary choices on geophysical images
Valentine, Andrew P.; Trampert, Jeannot
2016-01-01
Whenever a geophysical image is to be constructed, a variety of choices must be made. Some, such as those governing data selection and processing, or model parametrization, are somewhat arbitrary: there may be little reason to prefer one choice over another. Others, such as defining the theoretical framework within which the data are to be explained, may be more straightforward: typically, an `exact' theory exists, but various approximations may need to be adopted in order to make the imaging problem computationally tractable. Differences between any two images of the same system can be explained in terms of differences between these choices. Understanding the impact of each particular decision is essential if images are to be interpreted properly-but little progress has been made towards a quantitative treatment of this effect. In this paper, we consider a general linearized inverse problem, applicable to a wide range of imaging situations. We write down an expression for the difference between two images produced using similar inversion strategies, but where different choices have been made. This provides a framework within which inversion algorithms may be analysed, and allows us to consider how image effects may arise. In this paper, we take a general view, and do not specialize our discussion to any specific imaging problem or setup (beyond the restrictions implied by the use of linearized inversion techniques). In particular, we look at the concept of `hybrid inversion', in which highly accurate synthetic data (typically the result of an expensive numerical simulation) is combined with an inverse operator constructed based on theoretical approximations. It is generally supposed that this offers the benefits of using the more complete theory, without the full computational costs. We argue that the inverse operator is as important as the forward calculation in determining the accuracy of results. We illustrate this using a simple example, based on imaging the
Directory of Open Access Journals (Sweden)
Eugene V. Golanov
2017-09-01
Full Text Available Excitation of intrinsic neurons of cerebellar fastigial nucleus (FN renders brain tolerant to local and global ischemia. This effect reaches a maximum 72 h after the stimulation and lasts over 10 days. Comparable neuroprotection is observed following sublethal global brain ischemia, a phenomenon known as preconditioning. We hypothesized that FN may participate in the mechanisms of ischemic preconditioning as a part of the intrinsic neuroprotective mechanism. To explore potential significance of FN neurons in brain ischemic tolerance we lesioned intrinsic FN neurons with excitotoxin ibotenic acid five days before exposure to 20 min four-vessel occlusion (4-VO global ischemia while analyzing neuronal damage in Cornu Ammoni area 1 (CA1 hippocampal area one week later. In FN-lesioned animals, loss of CA1 cells was higher by 22% compared to control (phosphate buffered saline (PBS-injected animals. Moreover, lesion of FN neurons increased morbidity following global ischemia by 50%. Ablation of FN neurons also reversed salvaging effects of five-minute ischemic preconditioning on CA1 neurons and morbidity, while ablation of cerebellar dentate nucleus neurons did not change effect of ischemic preconditioning. We conclude that FN is an important part of intrinsic neuroprotective system, which participates in ischemic preconditioning and may participate in naturally occurring neuroprotection, such as “diving response”.
Hejranfar, Kazem; Parseh, Kaveh
2017-09-01
The preconditioned characteristic boundary conditions based on the artificial compressibility (AC) method are implemented at artificial boundaries for the solution of two- and three-dimensional incompressible viscous flows in the generalized curvilinear coordinates. The compatibility equations and the corresponding characteristic variables (or the Riemann invariants) are mathematically derived and then applied as suitable boundary conditions in a high-order accurate incompressible flow solver. The spatial discretization of the resulting system of equations is carried out by the fourth-order compact finite-difference (FD) scheme. In the preconditioning applied here, the value of AC parameter in the flow field and also at the far-field boundary is automatically calculated based on the local flow conditions to enhance the robustness and performance of the solution algorithm. The code is fully parallelized using the Concurrency Runtime standard and Parallel Patterns Library (PPL) and its performance on a multi-core CPU is analyzed. The incompressible viscous flows around a 2-D circular cylinder, a 2-D NACA0012 airfoil and also a 3-D wavy cylinder are simulated and the accuracy and performance of the preconditioned characteristic boundary conditions applied at the far-field boundaries are evaluated in comparison to the simplified boundary conditions and the non-preconditioned characteristic boundary conditions. It is indicated that the preconditioned characteristic boundary conditions considerably improve the convergence rate of the solution of incompressible flows compared to the other boundary conditions and the computational costs are significantly decreased.
Super-low dose endotoxin pre-conditioning exacerbates sepsis mortality.
Chen, Keqiang; Geng, Shuo; Yuan, Ruoxi; Diao, Na; Upchurch, Zachary; Li, Liwu
2015-04-01
Sepsis mortality varies dramatically in individuals of variable immune conditions, with poorly defined mechanisms. This phenomenon complements the hypothesis that innate immunity may adopt rudimentary memory, as demonstrated in vitro with endotoxin priming and tolerance in cultured monocytes. However, previous in vivo studies only examined the protective effect of endotoxin tolerance in the context of sepsis. In sharp contrast, we report herein that pre-conditionings with super-low or low dose endotoxin lipopolysaccharide (LPS) cause strikingly opposite survival outcomes. Mice pre-conditioned with super-low dose LPS experienced severe tissue damage, inflammation, increased bacterial load in circulation, and elevated mortality when they were subjected to cecal-ligation and puncture (CLP). This is in opposite to the well-reported protective phenomenon with CLP mice pre-conditioned with low dose LPS. Mechanistically, we demonstrated that super-low and low dose LPS differentially modulate the formation of neutrophil extracellular trap (NET) in neutrophils. Instead of increased ERK activation and NET formation in neutrophils pre-conditioned with low dose LPS, we observed significantly reduced ERK activation and compromised NET generation in neutrophils pre-conditioned with super-low dose LPS. Collectively, our findings reveal a novel mechanism potentially responsible for the dynamic programming of innate immunity in vivo as it relates to sepsis risks.
Super-low Dose Endotoxin Pre-conditioning Exacerbates Sepsis Mortality
Directory of Open Access Journals (Sweden)
Keqiang Chen
2015-04-01
Full Text Available Sepsis mortality varies dramatically in individuals of variable immune conditions, with poorly defined mechanisms. This phenomenon complements the hypothesis that innate immunity may adopt rudimentary memory, as demonstrated in vitro with endotoxin priming and tolerance in cultured monocytes. However, previous in vivo studies only examined the protective effect of endotoxin tolerance in the context of sepsis. In sharp contrast, we report herein that pre-conditioning with super-low or low dose endotoxin lipopolysaccharide (LPS cause strikingly opposite survival outcomes. Mice pre-conditioned with super-low dose LPS experienced severe tissue damage, inflammation, increased bacterial load in circulation, and elevated mortality when they were subjected to cecal-ligation and puncture (CLP. This is in contrast to the well-reported protective phenomenon with CLP mice pre-conditioned with low dose LPS. Mechanistically, we demonstrated that super-low and low dose LPS differentially modulate the formation of neutrophil extracellular trap (NET in neutrophils. Instead of increased ERK activation and NET formation in neutrophils pre-conditioned with low dose LPS, we observed significantly reduced ERK activation and compromised NET generation in neutrophils pre-conditioned with super-low dose LPS. Collectively, our findings reveal a mechanism potentially responsible for the dynamic programming of innate immunity in vivo as it relates to sepsis risks.
Rehni, Ashish K; Singh, Thakur Gurjeet
2012-10-01
The present study has been designed to investigate the potential role of CCR-2 chemokine receptor in ischemic preconditioning as well as postconditioning induced reversal of ischemia-reperfusion injury in mouse brain. Bilateral carotid artery occlusion of 17 min followed by reperfusion for 24h was employed in present study to produce ischemia and reperfusion induced cerebral injury in mice. Cerebral infarct size was measured using triphenyltetrazolium chloride staining. Memory was evaluated using elevated plus-maze test and Morris water maze test. Rota rod test was employed to assess motor incoordination. Bilateral carotid artery occlusion followed by reperfusion produced cerebral infarction and impaired memory and motor co-ordination. Three preceding episodes of bilateral carotid artery occlusion for 1 min and reperfusion of 1 min were employed to elicit ischemic preconditioning of brain, while three episodes of bilateral carotid artery occlusion for 10s and reperfusion of 10s immediately after the completion of were employed to elicit ischemic postconditioning of brain. Both prior ischemic preconditioning as well as ischemic postconditioning immediately after global cerebral ischemia prevented markedly ischemia-reperfusion-induced cerebral injury as measured in terms of infarct size, loss of memory and motor coordination. RS 102895, a selective CCR-2 chemokine receptor antagonist, attenuated the neuroprotective effect of both the ischemic preconditioning as well as postconditioning. It is concluded that the neuroprotective effect of both ischemic preconditioning as well as ischemic postconditioning may involve the activation of CCR-2 chemokine receptors. Copyright © 2012 Elsevier Ltd. All rights reserved.
The role of adenosine in preconditioning by brief pressure overload in rats.
Huang, Cheng-Hsiung; Tsai, Shen-Kou; Chiang, Shu-Chiung; Lai, Chang-Chi; Weng, Zen-Chung
2015-08-01
Brief pressure overload of the left ventricle reduced myocardial infarct (MI) size in rabbits has been previously reported. Its effects in other species are not known. This study investigates effects of pressure overload and the role of adenosine in rats in this study. MI was induced by 40-minute occlusion of the left anterior descending coronary artery followed by 3-hour reperfusion. MI size was determined by triphenyl tetrazolium chloride staining. Brief pressure overload was induced by two 10-minute episodes of partial snaring of the ascending aorta. Systolic left ventricular pressure was raised 50% above the baseline value. Ischemic preconditioning was elicited by two 10-minute coronary artery occlusions. The MI size (mean ± standard deviation), expressed as percentage of area at risk, was significantly reduced in the pressure overload group as well as in the ischemic preconditioning group (17.4 ± 3.0% and 18.2 ± 1.5% vs. 26.6 ± 2.4% in the control group, p overload and ischemic preconditioning (18.3 ± 1.5% and 18.2 ± 2.0%, respectively, p overload of the left ventricle preconditioned rat myocardium against infarction. Because SPT did not significantly alter MI size reduction, our results did not support a role of adenosine in preconditioning by pressure overload in rats. Copyright © 2013. Published by Elsevier B.V.
Use of a preconditioned Bi-conjugate gradient method for hybrid plasma stability analysis
International Nuclear Information System (INIS)
Mikic, Z.; Morse, E.C.
1985-01-01
The numerical stability analysis of compact toroidal plasmas using implicit time differencing requires the solution of a set of coupled, 2-dimensional, elliptic partial differential equations for the field quantities at every timestep. When the equations are spatially finite-differenced and written in matrix form, the resulting matrix is large, sparse, complex, non-Hermitian, and indefinite. The use of the preconditioned bi-conjugate gradient method for solving these equations is discussed. The effect of block-diagonal preconditioning and incomplete block-LU preconditionig on the convergence of the method is investigated. For typical matrices arising in our studies, the eigenvalue spectra of the original and preconditioned matrices are calculated as an illustration of the effectiveness of the preconditioning. We show that the preconditioned bi-conjugate gradient method coverages more rapidly than the conjugate gradient method applied to the normal equations, and that it is an effective iterative method for the class of non-Hermitian, indefinite problems of interest
Energy Technology Data Exchange (ETDEWEB)
Lebrun, D.
1997-05-22
The aim of the dissertation is the linearized inversion of multicomponent seismic data for 3D elastic horizontally stratified media, using Born approximation. A Jacobian matrix is constructed; it will be used to model seismic data from elastic parameters. The inversion technique, relying on single value decomposition (SVD) of the Jacobian matrix, is described. Next, the resolution of inverted elastic parameters is quantitatively studies. A first use of the technique is shown in the frame of an evaluation of a sea bottom acquisition (synthetic data). Finally, a real data set acquired with conventional marine technique is inverted. (author) 70 refs.
Approximate truncation robust computed tomography—ATRACT
International Nuclear Information System (INIS)
Dennerlein, Frank; Maier, Andreas
2013-01-01
We present an approximate truncation robust algorithm to compute tomographic images (ATRACT). This algorithm targets at reconstructing volumetric images from cone-beam projections in scenarios where these projections are highly truncated in each dimension. It thus facilitates reconstructions of small subvolumes of interest, without involving prior knowledge about the object. Our method is readily applicable to medical C-arm imaging, where it may contribute to new clinical workflows together with a considerable reduction of x-ray dose. We give a detailed derivation of ATRACT that starts from the conventional Feldkamp filtered-backprojection algorithm and that involves, as one component, a novel original formula for the inversion of the two-dimensional Radon transform. Discretization and numerical implementation are discussed and reconstruction results from both, simulated projections and first clinical data sets are presented. (paper)
Electrochemically driven emulsion inversion
Johans, Christoffer; Kontturi, Kyösti
2007-09-01
It is shown that emulsions stabilized by ionic surfactants can be inverted by controlling the electrical potential across the oil-water interface. The potential dependent partitioning of sodium dodecyl sulfate (SDS) was studied by cyclic voltammetry at the 1,2-dichlorobenzene|water interface. In the emulsion the potential control was achieved by using a potential-determining salt. The inversion of a 1,2-dichlorobenzene-in-water (O/W) emulsion stabilized by SDS was followed by conductometry as a function of added tetrapropylammonium chloride. A sudden drop in conductivity was observed, indicating the change of the continuous phase from water to 1,2-dichlorobenzene, i.e. a water-in-1,2-dichlorobenzene emulsion was formed. The inversion potential is well in accordance with that predicted by the hydrophilic-lipophilic deviation if the interfacial potential is appropriately accounted for.
Electron dose map inversion based on several algorithms
International Nuclear Information System (INIS)
Li Gui; Zheng Huaqing; Wu Yican; Fds Team
2010-01-01
The reconstruction to the electron dose map in radiation therapy was investigated by constructing the inversion model of electron dose map with different algorithms. The inversion model of electron dose map based on nonlinear programming was used, and this model was applied the penetration dose map to invert the total space one. The realization of this inversion model was by several inversion algorithms. The test results with seven samples show that except the NMinimize algorithm, which worked for just one sample, with great error,though,all the inversion algorithms could be realized to our inversion model rapidly and accurately. The Levenberg-Marquardt algorithm, having the greatest accuracy and speed, could be considered as the first choice in electron dose map inversion.Further tests show that more error would be created when the data close to the electron range was used (tail error). The tail error might be caused by the approximation of mean energy spectra, and this should be considered to improve the method. The time-saving and accurate algorithms could be used to achieve real-time dose map inversion. By selecting the best inversion algorithm, the clinical need in real-time dose verification can be satisfied. (authors)
DEFF Research Database (Denmark)
Gale, A.S.; Surlyk, Finn; Anderskouv, Kresten
2013-01-01
Evidence from regional stratigraphical patterns in Santonian−Campanian chalk is used to infer the presence of a very broad channel system (5 km across) with a depth of at least 50 m, running NNW−SSE across the eastern Isle of Wight; only the western part of the channel wall and fill is exposed. W......−Campanian chalks in the eastern Isle of Wight, involving penecontemporaneous tectonic inversion of the underlying basement structure, are rejected....
Reactivity in inverse micelles
International Nuclear Information System (INIS)
Brochette, Pascal
1987-01-01
This research thesis reports the study of the use of micro-emulsions of water in oil as reaction support. Only the 'inverse micelles' domain of the ternary mixing (water/AOT/isooctane) has been studied. The main addressed issues have been: the micro-emulsion disturbance in presence of reactants, the determination of reactant distribution and the resulting kinetic theory, the effect of the interface on electron transfer reactions, and finally protein solubilization [fr
International Nuclear Information System (INIS)
Steinhauer, L.C.; Romea, R.D.; Kimura, W.D.
1997-01-01
A new method for laser acceleration is proposed based upon the inverse process of transition radiation. The laser beam intersects an electron-beam traveling between two thin foils. The principle of this acceleration method is explored in terms of its classical and quantum bases and its inverse process. A closely related concept based on the inverse of diffraction radiation is also presented: this concept has the significant advantage that apertures are used to allow free passage of the electron beam. These concepts can produce net acceleration because they do not satisfy the conditions in which the Lawson-Woodward theorem applies (no net acceleration in an unbounded vacuum). Finally, practical aspects such as damage limits at optics are employed to find an optimized set of parameters. For reasonable assumptions an acceleration gradient of 200 MeV/m requiring a laser power of less than 1 GW is projected. An interesting approach to multi-staging the acceleration sections is also presented. copyright 1997 American Institute of Physics
Intersections, ideals, and inversion
International Nuclear Information System (INIS)
Vasco, D.W.
1998-01-01
Techniques from computational algebra provide a framework for treating large classes of inverse problems. In particular, the discretization of many types of integral equations and of partial differential equations with undetermined coefficients lead to systems of polynomial equations. The structure of the solution set of such equations may be examined using algebraic techniques.. For example, the existence and dimensionality of the solution set may be determined. Furthermore, it is possible to bound the total number of solutions. The approach is illustrated by a numerical application to the inverse problem associated with the Helmholtz equation. The algebraic methods are used in the inversion of a set of transverse electric (TE) mode magnetotelluric data from Antarctica. The existence of solutions is demonstrated and the number of solutions is found to be finite, bounded from above at 50. The best fitting structure is dominantly one dimensional with a low crustal resistivity of about 2 ohm-m. Such a low value is compatible with studies suggesting lower surface wave velocities than found in typical stable cratons
Intersections, ideals, and inversion
Energy Technology Data Exchange (ETDEWEB)
Vasco, D.W.
1998-10-01
Techniques from computational algebra provide a framework for treating large classes of inverse problems. In particular, the discretization of many types of integral equations and of partial differential equations with undetermined coefficients lead to systems of polynomial equations. The structure of the solution set of such equations may be examined using algebraic techniques.. For example, the existence and dimensionality of the solution set may be determined. Furthermore, it is possible to bound the total number of solutions. The approach is illustrated by a numerical application to the inverse problem associated with the Helmholtz equation. The algebraic methods are used in the inversion of a set of transverse electric (TE) mode magnetotelluric data from Antarctica. The existence of solutions is demonstrated and the number of solutions is found to be finite, bounded from above at 50. The best fitting structure is dominantly onedimensional with a low crustal resistivity of about 2 ohm-m. Such a low value is compatible with studies suggesting lower surface wave velocities than found in typical stable cratons.
Trimming and procrastination as inversion techniques
Backus, George E.
1996-12-01
By examining the processes of truncating and approximating the model space (trimming it), and by committing to neither the objectivist nor the subjectivist interpretation of probability (procrastinating), we construct a formal scheme for solving linear and non-linear geophysical inverse problems. The necessary prior information about the correct model xE can be either a collection of inequalities or a probability measure describing where xE was likely to be in the model space X before the data vector y0 was measured. The results of the inversion are (1) a vector z0 that estimates some numerical properties zE of xE; (2) an estimate of the error δz = z0 - zE. As y0 is finite dimensional, so is z0, and hence in principle inversion cannot describe all of xE. The error δz is studied under successively more specialized assumptions about the inverse problem, culminating in a complete analysis of the linear inverse problem with a prior quadratic bound on xE. Our formalism appears to encompass and provide error estimates for many of the inversion schemes current in geomagnetism, and would be equally applicable in geodesy and seismology if adequate prior information were available there. As an idealized example we study the magnetic field at the core-mantle boundary, using satellite measurements of field elements at sites assumed to be almost uniformly distributed on a single spherical surface. Magnetospheric currents are neglected and the crustal field is idealized as a random process with rotationally invariant statistics. We find that an appropriate data compression diagonalizes the variance matrix of the crustal signal and permits an analytic trimming of the idealized problem.
Some results in Diophantine approximation
DEFF Research Database (Denmark)
Pedersen, Steffen Højris
the basic concepts on which the papers build. Among other it introduces metric Diophantine approximation, Mahler’s approach on algebraic approximation, the Hausdorff measure, and properties of the formal Laurent series over Fq. The introduction ends with a discussion on Mahler’s problem when considered......This thesis consists of three papers in Diophantine approximation, a subbranch of number theory. Preceding these papers is an introduction to various aspects of Diophantine approximation and formal Laurent series over Fq and a summary of each of the three papers. The introduction introduces...
Limitations of shallow nets approximation.
Lin, Shao-Bo
2017-10-01
In this paper, we aim at analyzing the approximation abilities of shallow networks in reproducing kernel Hilbert spaces (RKHSs). We prove that there is a probability measure such that the achievable lower bound for approximating by shallow nets can be realized for all functions in balls of reproducing kernel Hilbert space with high probability, which is different with the classical minimax approximation error estimates. This result together with the existing approximation results for deep nets shows the limitations for shallow nets and provides a theoretical explanation on why deep nets perform better than shallow nets. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hypoxic preconditioning induces neuroprotective stanniocalcin-1 in brain via IL-6 signaling
DEFF Research Database (Denmark)
Westberg, Johan A; Serlachius, Martina; Lankila, Petri
2007-01-01
BACKGROUND AND PURPOSE: Exposure of animals for a few hours to moderate hypoxia confers relative protection against subsequent ischemic brain damage. This phenomenon, known as hypoxic preconditioning, depends on new RNA and protein synthesis, but its molecular mechanisms are poorly understood...... originally reported expression of mammalian STC-1 in brain neurons and showed that STC-1 guards neurons against hypercalcemic and hypoxic damage. METHODS: We treated neural Paju cells with IL-6 and measured the induction of STC-1 mRNA. In addition, we quantified the effect of hypoxic preconditioning on Stc-1...... mRNA levels in brains of wild-type and IL-6 deficient mice. Furthermore, we monitored the Stc-1 response in brains of wild-type and transgenic mice, overexpressing IL-6 in the astroglia, before and after induced brain injury. RESULTS: Hypoxic preconditioning induced an upregulated expression of Stc...
Nitroglycerine and sodium trioxodinitrate: from the discovery to the preconditioning effect.
Pagliaro, Pasquale; Gattullo, Donatella; Penna, Claudia
2013-10-01
The history began in the 19th century with Ascanio Sobrero (1812-1888), the discoverer of glycerol trinitrate (nitroglycerine, NTG), and with Angelo Angeli (1864-1931), the discoverer of sodium trioxodinitrate (Angeli's salt). It is likely that Angeli and Sobrero never met, but their two histories will join each other more than a century later. In fact, it has been discovered that both NTG and Angeli's salt are able to induce a preconditioning effect. As NTG has a long history as an antianginal drug its newly discovered property as a preconditioning agent has also been tested in humans. Angeli's salt properties as a preconditioning and inotropic agent have only been tested in animals so far.
Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures
Noor, Ahmed K.; Peters, Jeanne M.
1987-01-01
An efficient preconditioned conjugate gradient (PCG) technique and a computational procedure are presented for the analysis of symmetric anisotropic structures. The technique is based on selecting the preconditioning matrix as the orthotropic part of the global stiffness matrix of the structure, with all the nonorthotropic terms set equal to zero. This particular choice of the preconditioning matrix results in reducing the size of the analysis model of the anisotropic structure to that of the corresponding orthotropic structure. The similarities between the proposed PCG technique and a reduction technique previously presented by the authors are identified and exploited to generate from the PCG technique direct measures for the sensitivity of the different response quantities to the nonorthotropic (anisotropic) material coefficients of the structure. The effectiveness of the PCG technique is demonstrated by means of a numerical example of an anisotropic cylindrical panel.
DEFF Research Database (Denmark)
Vlassaks, Evi; Brudek, Tomasz; Pakkenberg, Bente
2014-01-01
the effects of perinatal asphyxia and fetal asphyctic preconditioning on the inflammatory cytokine response in the cerebellum. Fetal asphyxia was induced at embryonic day 17 by clamping the uterine vasculature for 30 min. At term birth, global perinatal asphyxia was induced by placing the uterine horns...... was decreased 96 h postfetal asphyxia. When applied as preconditioning stimulus, fetal asphyxia attenuates the cerebellar cytokine response. These results indicate that sublethal fetal asphyxia may protect the cerebellum from perinatal asphyxia-induced damage via inhibition of inflammation.......Asphyctic brain injury is a major cause of neuronal inflammation in the perinatal period. Fetal asphyctic preconditioning has been shown to modulate the cerebral inflammatory cytokine response, hereby protecting the brain against asphyctic injury at birth. This study was designated to examine...
Analysis of a Lipid/Polymer Membrane for Bitterness Sensing with a Preconditioning Process
Directory of Open Access Journals (Sweden)
Rui Yatabe
2015-09-01
Full Text Available It is possible to evaluate the taste of foods or medicines using a taste sensor. The taste sensor converts information on taste into an electrical signal using several lipid/polymer membranes. A lipid/polymer membrane for bitterness sensing can evaluate aftertaste after immersion in monosodium glutamate (MSG, which is called “preconditioning”. However, we have not yet analyzed the change in the surface structure of the membrane as a result of preconditioning. Thus, we analyzed the change in the surface by performing contact angle and surface zeta potential measurements, Fourier transform infrared spectroscopy (FTIR, X-ray photon spectroscopy (XPS and gas cluster ion beam time-of-flight secondary ion mass spectrometry (GCIB-TOF-SIMS. After preconditioning, the concentrations of MSG and tetradodecylammonium bromide (TDAB, contained in the lipid membrane were found to be higher in the surface region than in the bulk region. The effect of preconditioning was revealed by the above analysis methods.
Testing earthquake source inversion methodologies
Page, Morgan T.; Mai, Paul Martin; Schorlemmer, Danijel
2011-01-01
Source Inversion Validation Workshop; Palm Springs, California, 11-12 September 2010; Nowadays earthquake source inversions are routinely performed after large earthquakes and represent a key connection between recorded seismic and geodetic data
High-Order Calderón Preconditioned Time Domain Integral Equation Solvers
Valdes, Felipe
2013-05-01
Two high-order accurate Calderón preconditioned time domain electric field integral equation (TDEFIE) solvers are presented. In contrast to existing Calderón preconditioned time domain solvers, the proposed preconditioner allows for high-order surface representations and current expansions by using a novel set of fully-localized high-order div-and quasi curl-conforming (DQCC) basis functions. Numerical results demonstrate that the linear systems of equations obtained using the proposed basis functions converge rapidly, regardless of the mesh density and of the order of the current expansion. © 1963-2012 IEEE.
PBMC: Pre-conditioned Backward Monte Carlo code for radiative transport in planetary atmospheres
García Muñoz, A.; Mills, F. P.
2017-08-01
PBMC (Pre-Conditioned Backward Monte Carlo) solves the vector Radiative Transport Equation (vRTE) and can be applied to planetary atmospheres irradiated from above. The code builds the solution by simulating the photon trajectories from the detector towards the radiation source, i.e. in the reverse order of the actual photon displacements. In accounting for the polarization in the sampling of photon propagation directions and pre-conditioning the scattering matrix with information from the scattering matrices of prior (in the BMC integration order) photon collisions, PBMC avoids the unstable and biased solutions of classical BMC algorithms for conservative, optically-thick, strongly-polarizing media such as Rayleigh atmospheres.
High-Order Calderón Preconditioned Time Domain Integral Equation Solvers
Valdes, Felipe; Ghaffari-Miab, Mohsen; Andriulli, Francesco P.; Cools, Kristof; Michielssen,
2013-01-01
Two high-order accurate Calderón preconditioned time domain electric field integral equation (TDEFIE) solvers are presented. In contrast to existing Calderón preconditioned time domain solvers, the proposed preconditioner allows for high-order surface representations and current expansions by using a novel set of fully-localized high-order div-and quasi curl-conforming (DQCC) basis functions. Numerical results demonstrate that the linear systems of equations obtained using the proposed basis functions converge rapidly, regardless of the mesh density and of the order of the current expansion. © 1963-2012 IEEE.
Ohmichi, Yuya
2017-07-01
In this letter, we propose a simple and efficient framework of dynamic mode decomposition (DMD) and mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal decomposition (POD) to DMD and mode selection algorithms. By performing the preconditioning step, the DMD and mode selection can be performed with low memory consumption and therefore can be applied to large datasets. Additionally, we propose a simple mode selection algorithm based on a greedy method. The proposed framework is applied to the analysis of three-dimensional flow around a circular cylinder.
Impact of pre-conditioning on the qualification of safety-related equipment
International Nuclear Information System (INIS)
Isgro, J.R.
1982-01-01
This paper shares some recent experiences on the effects of preconditioning on the qualification of safety-related equipment not located in a harsh environment. Environmental and seismic qualification testing programs were conducted following the guidelines of IEEE 323-1974, IEEE 344-1975 and appropriate IEEE daughter standards, where available. The examples that follow will illustrate the degree of pre-conditioning of safety-related equipment qualified to the requirements of IEEE-323-1974, and its effect on the outcome of the qualification program
Preconditions for Emergence of Lithuanian Clusters: from Informal Cooperation to Its Legitimation
Directory of Open Access Journals (Sweden)
Grumadaitė Kristina
2017-06-01
Full Text Available This paper reveals preconditions for the emergence of clusters as self-organisation based industrial systems in a context, in which cooperation traditions are insufficiently developed. These preconditions reflect the principles of the emergence of self-organising complex adaptive systems that are analysed in the complexity theory. Those principles are based on the initiation of non-equilibrium and its purposeful direction into the creation of a new order. This paper highlights the main external and internal tensions that influence informal or formal clustering of enterprises, while various change agents perform different roles making self-organising processes to occur.
Improving the making ready process - Exploring the preconditions to work tasks in construction
DEFF Research Database (Denmark)
Lindhard, Søren; Wandahl, Søren
2012-01-01
preconditions have been revealed. The seven first is basically corresponding to the ones presented by Koskela (1999), while the last two are new and extends the existing knowledge. The preconditions are as follows: 1) Construction design and management. 2) Components and materials are present. 3) Workers...... are present. 4) Equipment and machinery are present. 5) Sufficient space for conduction. 6) Previous activities must be completed. 7) Climate conditions must be in order. 8) Safe working conditions in relation to national “Health and Safety at Work Act ” have to be present, 9) Known working conditions. Often...... productivity....
PRECONDITIONED BI-CONJUGATE GRADIENT METHOD FOR RADIATIVE TRANSFER IN SPHERICAL MEDIA
International Nuclear Information System (INIS)
Anusha, L. S.; Nagendra, K. N.; Paletou, F.; Leger, L.
2009-01-01
A robust numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is proposed for the solution of the radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These are iterative methods based on the construction of a set of bi-orthogonal vectors. The application of the Pre-BiCG method in some benchmark tests shows that the method is quite versatile, and can handle difficult problems that may arise in astrophysical radiative transfer theory.
Spherical Approximation on Unit Sphere
Directory of Open Access Journals (Sweden)
Eman Samir Bhaya
2018-01-01
Full Text Available In this paper we introduce a Jackson type theorem for functions in LP spaces on sphere And study on best approximation of functions in spaces defined on unit sphere. our central problem is to describe the approximation behavior of functions in spaces for by modulus of smoothness of functions.
Weber, Nina C.; Toma, Octavian; Awan, Saqib; Frässdorf, Jan; Preckel, Benedikt; Schlack, Wolfgang
2005-01-01
BACKGROUND: For nitrous oxide, a preconditioning effect on the heart has yet not been investigated. This is important because nitrous oxide is commonly used in combination with volatile anesthetics, which are known to precondition the heart. The authors aimed to clarify (1) whether nitrous oxide
Comparison of the mass preconditioned HMC and the DD-HMC algorithm for two-flavour QCD
Marinkovic, Marina
2010-01-01
Mass preconditioned HMC and DD-HMC are among the most popular algorithms to simulate Wilson fermions. We present a comparison of the performance of the two algorithms for realistic quark masses and lattice sizes. In particular, we use the locally deflated solver of the DD-HMC environment also for the mass preconditioned simulations.
Bredeweg, Steef W.; Zijlstra, Sjouke; Bessem, Bram; Buist, Ida
Objectives There is no consensus on the aetiology and prevention of running-related injuries in runners. Preconditioning studies among different athlete populations show positive effects on the incidence of sports injuries. Hypothesis A 4-week preconditioning programme in novice runners will reduce
Inverse scattering with supersymmetric quantum mechanics
International Nuclear Information System (INIS)
Baye, Daniel; Sparenberg, Jean-Marc
2004-01-01
The application of supersymmetric quantum mechanics to the inverse scattering problem is reviewed. The main difference with standard treatments of the inverse problem lies in the simple and natural extension to potentials with singularities at the origin and with a Coulomb behaviour at infinity. The most general form of potentials which are phase-equivalent to a given potential is discussed. The use of singular potentials allows adding or removing states from the bound spectrum without contradicting the Levinson theorem. Physical applications of phase-equivalent potentials in nuclear reactions and in three-body systems are described. Derivation of a potential from the phase shift at fixed orbital momentum can also be performed with the supersymmetric inversion by using a Bargmann-type approximation of the scattering matrix or phase shift. A unique singular potential without bound states can be obtained from any phase shift. A limited number of bound states depending on the singularity can then be added. This inversion procedure is illustrated with nucleon-nucleon scattering
Multiscale Phase Inversion of Seismic Data
Fu, Lei
2017-12-02
We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive to the unmodeled physics of wave propagation and a poor starting model than standard full waveform inversion (FWI). To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. The input data are also filtered into different narrow frequency bands for the MPI implementation. At low frequencies, we show that MPI with windowed reflections approximates wave equation inversion of the reflection traveltimes, except no traveltime picking is needed. Numerical results with synthetic acoustic data show that MPI is more robust than conventional multiscale FWI when the initial model is far from the true model. Results from synthetic viscoacoustic and elastic data show that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data shows that MPI is more robust and produces modestly more accurate results than FWI for this data set.
Approximate circuits for increased reliability
Hamlet, Jason R.; Mayo, Jackson R.
2015-08-18
Embodiments of the invention describe a Boolean circuit having a voter circuit and a plurality of approximate circuits each based, at least in part, on a reference circuit. The approximate circuits are each to generate one or more output signals based on values of received input signals. The voter circuit is to receive the one or more output signals generated by each of the approximate circuits, and is to output one or more signals corresponding to a majority value of the received signals. At least some of the approximate circuits are to generate an output value different than the reference circuit for one or more input signal values; however, for each possible input signal value, the majority values of the one or more output signals generated by the approximate circuits and received by the voter circuit correspond to output signal result values of the reference circuit.
Inverse planning and optimization: a comparison of solutions
Energy Technology Data Exchange (ETDEWEB)
Ringor, Michael [School of Health Sciences, Purdue University, West Lafayette, IN (United States); Papiez, Lech [Department of Radiation Oncology, Indiana University, Indianapolis, IN (United States)
1998-09-01
The basic problem in radiation therapy treatment planning is to determine an appropriate set of treatment parameters that would induce an effective dose distribution inside a patient. One can approach this task as an inverse problem, or as an optimization problem. In this presentation, we compare both approaches. The inverse problem is presented as a dose reconstruction problem similar to tomography reconstruction. We formulate the optimization problem as linear and quadratic programs. Explicit comparisons are made between the solutions obtained by inversion and those obtained by optimization for the case in which scatter and attenuation are ignored (the NS-NA approximation)
Theory of the inverse Faraday effect in metals
International Nuclear Information System (INIS)
Hertel, Riccardo
2006-01-01
An analytic expression is given for the inverse Faraday effect, i.e., for the magnetization occurring in a transparent medium exposed to a circularly polarized high-frequency electromagnetic wave. Using a microscopic approach based on the Drude approximation of a free-electron gas, the magnetization of the medium due to the inverse Faraday effect is identified as the result of microscopic solenoidal currents generated by the electromagnetic wave. In contrast to the better known phenomenological derivation, this microscopic treatment provides important information on the frequency dependence of the inverse Faraday effect
Displacement Parameter Inversion for a Novel Electromagnetic Underground Displacement Sensor
Directory of Open Access Journals (Sweden)
Nanying Shentu
2014-05-01
Full Text Available Underground displacement monitoring is an effective method to explore deep into rock and soil masses for execution of subsurface displacement measurements. It is not only an important means of geological hazards prediction and forecasting, but also a forefront, hot and sophisticated subject in current geological disaster monitoring. In previous research, the authors had designed a novel electromagnetic underground horizontal displacement sensor (called the H-type sensor by combining basic electromagnetic induction principles with modern sensing techniques and established a mutual voltage measurement theoretical model called the Equation-based Equivalent Loop Approach (EELA. Based on that work, this paper presents an underground displacement inversion approach named “EELA forward modeling-approximate inversion method”. Combining the EELA forward simulation approach with the approximate optimization inversion theory, it can deduce the underground horizontal displacement through parameter inversion of the H-type sensor. Comprehensive and comparative studies have been conducted between the experimentally measured and theoretically inversed values of horizontal displacement under counterpart conditions. The results show when the measured horizontal displacements are in the 0–100 mm range, the horizontal displacement inversion discrepancy is generally tested to be less than 3 mm under varied tilt angles and initial axial distances conditions, which indicates that our proposed parameter inversion method can predict underground horizontal displacement measurements effectively and robustly for the H-type sensor and the technique is applicable for practical geo-engineering applications.
National Research Council Canada - National Science Library
Hatch, Andrew G; Smith, Ralph C; De, Tathagata; Salapaka, Murti V
2005-01-01
.... In this paper, we illustrate the construction of inverse filters, based on homogenized energy models, which can be used to approximately linearize the piezoceramic transducer behavior for linear...
Introduction to Schroedinger inverse scattering
International Nuclear Information System (INIS)
Roberts, T.M.
1991-01-01
Schroedinger inverse scattering uses scattering coefficients and bound state data to compute underlying potentials. Inverse scattering has been studied extensively for isolated potentials q(x), which tend to zero as vertical strokexvertical stroke→∞. Inverse scattering for isolated impurities in backgrounds p(x) that are periodic, are Heaviside steps, are constant for x>0 and periodic for x<0, or that tend to zero as x→∞ and tend to ∞ as x→-∞, have also been studied. This paper identifies literature for the five inverse problems just mentioned, and for four other inverse problems. Heaviside-step backgrounds are discussed at length. (orig.)
Approximate Dynamic Programming: Combining Regional and Local State Following Approximations.
Deptula, Patryk; Rosenfeld, Joel A; Kamalapurkar, Rushikesh; Dixon, Warren E
2018-06-01
An infinite-horizon optimal regulation problem for a control-affine deterministic system is solved online using a local state following (StaF) kernel and a regional model-based reinforcement learning (R-MBRL) method to approximate the value function. Unlike traditional methods such as R-MBRL that aim to approximate the value function over a large compact set, the StaF kernel approach aims to approximate the value function in a local neighborhood of the state that travels within a compact set. In this paper, the value function is approximated using a state-dependent convex combination of the StaF-based and the R-MBRL-based approximations. As the state enters a neighborhood containing the origin, the value function transitions from being approximated by the StaF approach to the R-MBRL approach. Semiglobal uniformly ultimately bounded (SGUUB) convergence of the system states to the origin is established using a Lyapunov-based analysis. Simulation results are provided for two, three, six, and ten-state dynamical systems to demonstrate the scalability and performance of the developed method.
Directory of Open Access Journals (Sweden)
Yuhei Harada
2016-02-01
Full Text Available A taste sensor that uses lipid/polymer membranes can evaluate aftertastes felt by humans using Change in membrane Potential caused by Adsorption (CPA measurements. The sensor membrane for evaluating bitterness, which is caused by acidic bitter substances such as iso-alpha acid contained in beer, needs an immersion process in monosodium glutamate (MSG solution, called “MSG preconditioning”. However, what happens to the lipid/polymer membrane during MSG preconditioning is not clear. Therefore, we carried out three experiments to investigate the changes in the lipid/polymer membrane caused by the MSG preconditioning, i.e., measurements of the taste sensor, measurements of the amount of the bitterness substance adsorbed onto the membrane and measurements of the contact angle of the membrane surface. The CPA values increased as the preconditioning process progressed, and became stable after 3 d of preconditioning. The response potentials to the reference solution showed the same tendency of the CPA value change during the preconditioning period. The contact angle of the lipid/polymer membrane surface decreased after 7 d of MSG preconditioning; in short, the surface of the lipid/polymer membrane became hydrophilic during MSG preconditioning. The amount of adsorbed iso-alpha acid was increased until 5 d preconditioning, and then it decreased. In this study, we revealed that the CPA values increased with the progress of MSG preconditioning in spite of the decrease of the amount of iso-alpha acid adsorbed onto the lipid/polymer membrane, and it was indicated that the CPA values increase because the sensor sensitivity was improved by the MSG preconditioning.
The efficiency of Flory approximation
International Nuclear Information System (INIS)
Obukhov, S.P.
1984-01-01
The Flory approximation for the self-avoiding chain problem is compared with a conventional perturbation theory expansion. While in perturbation theory each term is averaged over the unperturbed set of configurations, the Flory approximation is equivalent to the perturbation theory with the averaging over the stretched set of configurations. This imposes restrictions on the integration domain in higher order terms and they can be treated self-consistently. The accuracy δν/ν of Flory approximation for self-avoiding chain problems is estimated to be 2-5% for 1 < d < 4. (orig.)
Ionogram inversion for a tilted ionosphere
International Nuclear Information System (INIS)
Wright, J.W.
1990-01-01
Digital ionosondes such as the Dynasonde disclose that the ionosphere is seldom horizontal even when it is plane stratified to a good approximation. The local magnetic dip does not then determine correctly the radiowave propagation angle for inversion of the ionogram to a plasma density profile. The measured echo direction of arrival can be used together with the known dip for an improved propagation angle. The effects are small for simple one-parameter laminae but become important when differential (ordinary, extraordinary) retardations are used to aid correction for valley and starting ambiguities. The resulting profile describes the plasma distribution along the direction of observation, rather than the vertical; it thus conveys information about horizontal gradients. Observations suggest that advantages in inversion methods may be practicable for application to modern ionosonde recordings, by which local lateral structure can be described in greater detail. 20 refs
Voxel inversion of airborne electromagnetic data for improved model integration
Fiandaca, Gianluca; Auken, Esben; Kirkegaard, Casper; Vest Christiansen, Anders
2014-05-01
Inversion of electromagnetic data has migrated from single site interpretations to inversions including entire surveys using spatial constraints to obtain geologically reasonable results. Though, the model space is usually linked to the actual observation points. For airborne electromagnetic (AEM) surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space, and the geophysical information has to be relocated for integration in (hydro)geological models. We have developed a new geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the soil properties is computed everywhere by means of an interpolation function (e.g. inverse distance or kriging). Given this definition of the voxel model space, the 1D forward responses of the AEM data are computed as follows: 1) a 1D model subdivision, in terms of model thicknesses, is defined for each 1D data set, creating "virtual" layers. 2) the "virtual" 1D models at the sounding positions are finalized by interpolating the soil properties (the resistivity) in the center of the "virtual" layers. 3) the forward response is computed in 1D for each "virtual" model. We tested the new inversion scheme on an AEM survey carried out with the SkyTEM system close to Odder, in Denmark. The survey comprises 106054 dual mode AEM soundings, and covers an area of approximately 13 km X 16 km. The voxel inversion was carried out on a structured grid of 260 X 325 X 29 xyz nodes (50 m xy spacing), for a total of 2450500 inversion parameters. A classical spatially constrained inversion (SCI) was carried out on the same data set, using 106054
Plasma diagnostics by Abel inversion in hyperbolic geometry
International Nuclear Information System (INIS)
Alhasi, A.S.; Elliott, J.A.
1992-01-01
Plasma confined in the UMIST linear quadrupole adopts a configuration with approximately hyperbolic symmetry. The normal diagnostic is a Langmuir probe, but we have developed an alternative method using optical emission tomography based upon an analytic Abel inversion. Plasma radiance is obtained as a function of a parameter identifying magnetic flux surfaces. The inversion algorithm has been tested using artificial data. Experimentally, the results show that ionizing collisions cause the confined plasma distribution to broaden as the plasma travels through the confining field. This is shown to be a consequence of the approximate incompressibility of the E x B flow. (author)
Inverse Faraday Effect Revisited
Mendonça, J. T.; Ali, S.; Davies, J. R.
2010-11-01
The inverse Faraday effect is usually associated with circularly polarized laser beams. However, it was recently shown that it can also occur for linearly polarized radiation [1]. The quasi-static axial magnetic field by a laser beam propagating in plasma can be calculated by considering both the spin and the orbital angular momenta of the laser pulse. A net spin is present when the radiation is circularly polarized and a net orbital angular momentum is present if there is any deviation from perfect rotational symmetry. This orbital angular momentum has recently been discussed in the plasma context [2], and can give an additional contribution to the axial magnetic field, thus enhancing or reducing the inverse Faraday effect. As a result, this effect that is usually attributed to circular polarization can also be excited by linearly polarized radiation, if the incident laser propagates in a Laguerre-Gauss mode carrying a finite amount of orbital angular momentum.[4pt] [1] S. ALi, J.R. Davies and J.T. Mendonca, Phys. Rev. Lett., 105, 035001 (2010).[0pt] [2] J. T. Mendonca, B. Thidé, and H. Then, Phys. Rev. Lett. 102, 185005 (2009).
Approximate Implicitization Using Linear Algebra
Directory of Open Access Journals (Sweden)
Oliver J. D. Barrowclough
2012-01-01
Full Text Available We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point implementation in computer-aided geometric design (CAGD systems. We unify the approaches under the names of commonly known polynomial basis functions and consider various theoretical and practical aspects of the algorithms. We offer new methods for a least squares approach to approximate implicitization using orthogonal polynomials, which tend to be faster and more numerically stable than some existing algorithms. We propose several simple propositions relating the properties of the polynomial bases to their implicit approximation properties.
Rollout sampling approximate policy iteration
Dimitrakakis, C.; Lagoudakis, M.G.
2008-01-01
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a
Weighted approximation with varying weight
Totik, Vilmos
1994-01-01
A new construction is given for approximating a logarithmic potential by a discrete one. This yields a new approach to approximation with weighted polynomials of the form w"n"(" "= uppercase)P"n"(" "= uppercase). The new technique settles several open problems, and it leads to a simple proof for the strong asymptotics on some L p(uppercase) extremal problems on the real line with exponential weights, which, for the case p=2, are equivalent to power- type asymptotics for the leading coefficients of the corresponding orthogonal polynomials. The method is also modified toyield (in a sense) uniformly good approximation on the whole support. This allows one to deduce strong asymptotics in some L p(uppercase) extremal problems with varying weights. Applications are given, relating to fast decreasing polynomials, asymptotic behavior of orthogonal polynomials and multipoint Pade approximation. The approach is potential-theoretic, but the text is self-contained.
Framework for sequential approximate optimization
Jacobs, J.H.; Etman, L.F.P.; Keulen, van F.; Rooda, J.E.
2004-01-01
An object-oriented framework for Sequential Approximate Optimization (SAO) isproposed. The framework aims to provide an open environment for thespecification and implementation of SAO strategies. The framework is based onthe Python programming language and contains a toolbox of Python
Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.
1988-11-01
Many physical problems require the solution of coupled partial differential equations on three-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES3 allows each spatial operator to have 7, 15, 19, or 27 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect induces which is vectorizable on some of the newer scientific computers.
Late preconditioning is blocked by racemic ketamine, but not by S(+)-ketamine
Müllenheim, J.; Rulands, R.; Wietschorke, T.; Frässdorf, J.; Preckel, B.; Schlack, W.
2001-01-01
Racemic ketamine blocks K(ATP) channels in isolated cells and abolishes short-term cardioprotection against prolonged ischemia. We investigated the effects of racemic ketamine and S(+)-ketamine on ischemic late preconditioning (LPC) in the rabbit heart in vivo. A coronary occluder was chronically
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution method s * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Kolb, Alexander L; Corridon, Peter R; Zhang, Shijun; Xu, Weimin; Witzmann, Frank A; Collett, Jason A; Rhodes, George J; Winfree, Seth; Bready, Devin; Pfeffenberger, Zechariah J; Pomerantz, Jeremy M; Hato, Takashi; Nagami, Glenn T; Molitoris, Bruce A; Basile, David P; Atkinson, Simon J; Bacallao, Robert L
2018-04-01
Ischemic preconditioning confers organ-wide protection against subsequent ischemic stress. A substantial body of evidence underscores the importance of mitochondria adaptation as a critical component of cell protection from ischemia. To identify changes in mitochondria protein expression in response to ischemic preconditioning, we isolated mitochondria from ischemic preconditioned kidneys and sham-treated kidneys as a basis for comparison. The proteomic screen identified highly upregulated proteins, including NADP+-dependent isocitrate dehydrogenase 2 (IDH2), and we confirmed the ability of this protein to confer cellular protection from injury in murine S3 proximal tubule cells subjected to hypoxia. To further evaluate the role of IDH2 in cell protection, we performed detailed analysis of the effects of Idh2 gene delivery on kidney susceptibility to ischemia-reperfusion injury. Gene delivery of IDH2 before injury attenuated the injury-induced rise in serum creatinine ( P <0.05) observed in controls and increased the mitochondria membrane potential ( P <0.05), maximal respiratory capacity ( P <0.05), and intracellular ATP levels ( P <0.05) above those in controls. This communication shows that gene delivery of Idh2 can confer organ-wide protection against subsequent ischemia-reperfusion injury and mimics ischemic preconditioning. Copyright © 2018 by the American Society of Nephrology.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www. science direct.com/ science /article/pii/S0377042716301492?via%3Dihub
On the Eigenvalues and Eigenvectors of Block Triangular Preconditioned Block Matrices
Pestana, Jennifer
2014-01-01
Block lower triangular matrices and block upper triangular matrices are popular preconditioners for 2×2 block matrices. In this note we show that a block lower triangular preconditioner gives the same spectrum as a block upper triangular preconditioner and that the eigenvectors of the two preconditioned matrices are related. © 2014 Society for Industrial and Applied Mathematics.
GPU acceleration of preconditioned solvers for ill-conditioned linear systems
Gupta, R.
2015-01-01
In this work we study the implementations of deflation and preconditioning techniques for solving ill-conditioned linear systems using iterative methods. Solving such systems can be a time-consuming process because of the jumps in the coefficients due to large difference in material properties. We
Comparison results on preconditioned SOR-type iterative method for Z-matrices linear systems
Wang, Xue-Zhong; Huang, Ting-Zhu; Fu, Ying-Ding
2007-09-01
In this paper, we present some comparison theorems on preconditioned iterative method for solving Z-matrices linear systems, Comparison results show that the rate of convergence of the Gauss-Seidel-type method is faster than the rate of convergence of the SOR-type iterative method.
Solving large test-day models by iteration on data and preconditioned conjugate gradient.
Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A
1999-12-01
A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Preßler, Anna-Lena; Könen, Tanja; Hasselhorn, Marcus; Krajewski, Kristin
2014-01-01
The aim of the present study was to empirically disentangle the interdependencies of the impact of nonverbal intelligence, working memory capacities, and phonological processing skills on early reading decoding and spelling within a latent variable approach. In a sample of 127 children, these cognitive preconditions were assessed before the onset…
Lotgering, F.K.; Bishai, J.M.; Struijk, P.C.; Blood, A.B.; Hunter, C.J.; Oberg, K.C.; Power, G.G.; Longo, L.D.
2004-01-01
OBJECTIVE: To determine to what extent a series of five 1-minute total umbilical cord occlusions, intended to induce ischemic preconditioning (IP), affects the physiologic responses to a 10-minute total umbilical cord occlusion (damaging insult [DI]) 1 hour later and provides cardio- and
Chabory, A.; Hon, de B.P.; Schilders, W.H.A.; Tijhuis, A.G.
2008-01-01
Finite-difference techniques are very popular and versatile numerical tools in computational electromagnetics. In this paper, we propose a preconditioned finite-difference frequency-domain method (FDFD) to model periodic structures in 2D and 3D. The preconditioner follows from a modal decoupling
Chabory, A.; Hon, de B.P.; Schilders, W.H.A.; Tijhuis, A.G.
2008-01-01
Finite-difference techniques are very popular and versatile numerical tools in computational electromagnetics. In this paper, we propose a preconditioned finite-difference frequency-domain method (FDFD) to model periodic structures in 2D and 3D. The preconditioner follows from a modal decoupling
Impact of remote ischemic preconditioning on wound healing in small bowel anastomoses
Holzner, Philipp Anton; Kulemann, Birte; Kuesters, Simon; Timme, Sylvia; Hoeppner, Jens; Hopt, Ulrich Theodor; Marjanovic, Goran
2011-01-01
AIM: To investigate the influence of remote ischemic preconditioning (RIPC) on anastomotic integrity. METHODS: Sixty male Wistar rats were randomized to six groups. The control group (n = 10) had an end-to-end ileal anastomosis without RIPC. The preconditioned groups (n = 34) varied in time of ischemia and time of reperfusion. One group received the amino acid L-arginine before constructing the anastomosis (n = 9). On postoperative day 4, the rats were re-laparotomized, and bursting pressure, hydroxyproline concentration, intra-abdominal adhesions, and a histological score concerning the mucosal ischemic injury were collected. The data are given as median (range). RESULTS: On postoperative day 4, median bursting pressure was 124 mmHg (60-146 mmHg) in the control group. The experimental groups did not show a statistically significant difference (P > 0.05). Regarding the hydroxyproline concentration, we did not find any significant variation in the experimental groups. We detected significantly less mucosal injury in the RIPC groups. Furthermore, we assessed more extensive intra-abdominal adhesions in the preconditioned groups than in the control group. CONCLUSION: RIPC directly before performing small bowel anastomosis does not affect anastomotic stability in the early period, as seen in ischemic preconditioning. PMID:21455330
The effect of preconditioning cells under osmotic stress on high alcohol production
Directory of Open Access Journals (Sweden)
Logotetis Stilijanos
2013-01-01
Full Text Available This paper focuses on the research into the influence of salt on physiology of the yeast, Saccharomyces cerevisiae. Specifically, the work focused on how NaCl affected the growth, viability and fermentation performance of this yeast in laboratory-scale experiments. One of the main findings of the research presented involved the influence of salt “preconditioning” of yeasts which represents a method of pre-culturing of cells in the presence of salt in an attempt to improve subsequent fermentation performance. Such an approach resulted in preconditioned yeasts having an improved capability to ferment high-sugar containing media (up to 60% w/v of glucose with increased cell viability and with increased levels of produced ethanol (higher than 20% in vol.. Salt-preconditioning was most likely influencing the stress-tolerance of yeasts by inducing the synthesis of key metabolites such as trehalose and glycerol which act to improve cells’ ability to withstand osmostress and ethanol toxicity. The industrial-scale trials using salt-preconditioned yeasts verified the benefit of the physiological engineering approach to practical fermentations. Overall, this research has demonstrated that a relatively simple method designed to adapt yeast cells physiologically - by salt-preconditioning - can have distinct advantages for alcohol fermentation processes.
Impact of ischemic preconditioning on functional sympatholysis during handgrip exercise in humans.
Horiuchi, M.; Endo, J.; Thijssen, D.H.J.
2015-01-01
Repeated bouts of ischemia followed by reperfusion, known as ischemic preconditioning (IPC), is found to improve exercise performance. As redistribution of blood from the inactive areas to active skeletal muscles during exercise (i.e., functional sympatholysis) is important for exercise performance,
Kast, Brigitte; Schori, Christian; Grimm, Christian
2016-05-01
Hypoxic preconditioning protects photoreceptors against light-induced degeneration preserving retinal morphology and function. Although hypoxia inducible transcription factors 1 and 2 (HIF1, HIF2) are the main regulators of the hypoxic response, photoreceptor protection does not depend on HIF1 in rods. Here we used rod-specific Hif2a single and Hif1a;Hif2a double knockout mice to investigate the potential involvement of HIF2 in rods for protection after hypoxic preconditioning. To identify potential HIF2 target genes in rods we determined the retinal transcriptome of hypoxic control and rod-specific Hif2a knockouts by RNA sequencing. We show that rods do not need HIF2 for hypoxia-induced increased survival after light exposure. The transcriptomic analysis revealed a number of genes that are potentially regulated by HIF2 in rods; among those were Htra1, Timp3 and Hmox1, candidates that are interesting due to their connection to human degenerative diseases of the retina. We conclude that neither HIF1 nor HIF2 are required in photoreceptors for protection by hypoxic preconditioning. We hypothesize that HIF transcription factors may be needed in other cells to produce protective factors acting in a paracrine fashion on photoreceptor cells. Alternatively, hypoxic preconditioning induces a rod-intrinsic response that is independent of HIF transcription factors. Copyright © 2015 Elsevier Ltd. All rights reserved.
An M-step preconditioned conjugate gradient method for parallel computation
Adams, L.
1983-01-01
This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.
On the use of rigid body modes in the deflated preconditioned conjugate gradient method
Jönsthövel, T.B.; Van Gijzen, M.B.; Vuik, C.; Scarpas, A.
2011-01-01
Large discontinuities in material properties, such as encountered in composite materials, lead to ill-conditioned systems of linear equations. These discontinuities give rise to small eigenvalues that may negatively affect the convergence of iterative solution methods such as the Preconditioned
Hosseini, S.M.; Wilson, W.; Ito, K.; Donkelaar, van C.C.
2014-01-01
It is known that initial loading curves of soft biological tissues are substantially different from subsequent loadings. The later loading curves are generally used for assessing the mechanical properties of a tissue, and the first loading cycles, referred to as preconditioning, are omitted.
Verkade, P.J.; Meijel, B. van; Brink, C.; Os-Medendorp, H. van; Koekkoek, B.; Francke, A.L.
2010-01-01
Background: Case management programmes for home-dwelling people with dementia and their informal carers exist in multiple forms and shapes. The aim of this research was to identify the essential components of case management for people with dementia as well as the preconditions for an effective
Czech Academy of Sciences Publication Activity Database
Kouhia, R.; Tůma, Miroslav; Mäkinen, J.; Fedoroff, A.; Marjamäki, H.
108-109, October (2012), s. 110-117 ISSN 0045-7949 R&D Projects: GA ČR(CZ) GAP108/11/0853 Institutional research plan: CEZ:AV0Z10300504 Keywords : non-linear eigenvalue problem * equilibrium equations * critical points * preconditioned iterations Subject RIV: BA - General Mathematics Impact factor: 1.509, year: 2012
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www.sciencedirect.com/science/article/pii/S0377042716301492?via%3Dihub
Approximate deconvolution models of turbulence analysis, phenomenology and numerical analysis
Layton, William J
2012-01-01
This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly used turbulence models – as well as some disadvantages. Our goal in this book is to provide a clear and complete mathematical development of ADMs, while pointing out the difficulties that remain. In order to do so, we present the analytical theory of ADMs, along with its connections, motivations and complements in the phenomenology of and algorithms for ADMs.
Parallelized preconditioned model building algorithm for matrix factorization
Kaya, Kamer; Birbil, İlker; Birbil, Ilker; Öztürk, Mehmet Kaan; Ozturk, Mehmet Kaan; Gohari, Amir
2017-01-01
Matrix factorization is a common task underlying several machine learning applications such as recommender systems, topic modeling, or compressed sensing. Given a large and possibly sparse matrix A, we seek two smaller matrices W and H such that their product is as close to A as possible. The objective is minimizing the sum of square errors in the approximation. Typically such problems involve hundreds of thousands of unknowns, so an optimizer must be exceptionally efficient. In this study, a...
Joo, Jin Deok; Kim, Mihwa; D'Agati, Vivette D; Lee, H Thomas
2006-11-01
Acute as well as delayed ischemic preconditioning (IPC) provides protection against cardiac and neuronal ischemia reperfusion (IR) injury. This study determined whether delayed preconditioning occurs in the kidney and further elucidated the mechanisms of renal IPC in mice. Mice were subjected to IPC (four cycles of 5 min of ischemia and reperfusion) and then to 30 min of renal ischemia either 15 min (acute IPC) or 24 h (delayed IPC) later. Both acute and delayed renal IPC provided powerful protection against renal IR injury. Inhibition of Akt but not extracellular signal-regulated kinase phosphorylation prevented the protection that was afforded by acute IPC. Neither extracellular signal-regulated kinase nor Akt inhibition prevented protection that was afforded by delayed renal IPC. Pretreatment with an antioxidant, N-(2-mercaptopropionyl)-glycine, to scavenge free radicals prevented the protection that was provided by acute but not delayed renal IPC. Inhibition of protein kinase C or pertussis toxin-sensitive G-proteins attenuated protection from both acute and delayed renal IPC. Delayed renal IPC increased inducible nitric oxide synthase (iNOS) as well as heat-shock protein 27 synthesis, and the renal protective effects of delayed preconditioning were attenuated by a selective inhibitor of iNOS (l-N(6)[1-iminoethyl]lysine). Moreover, delayed IPC was not observed in iNOS knockout mice. Both acute and delayed IPC were independent of A(1) adenosine receptors (AR) as a selective A(1)AR antagonist failed to block preconditioning and acute and delayed preconditioning occurred in mice that lacked A(1)AR. Therefore, this study demonstrated that acute or delayed IPC provides renal protection against IR injury in mice but involves distinct signaling pathways.
Numerical Inversion for the Multiple Fractional Orders in the Multiterm TFDE
Directory of Open Access Journals (Sweden)
Chunlong Sun
2017-01-01
Full Text Available The fractional order in a fractional diffusion model is a key parameter which characterizes the anomalous diffusion behaviors. This paper deals with an inverse problem of determining the multiple fractional orders in the multiterm time-fractional diffusion equation (TFDE for short from numerics. The homotopy regularization algorithm is applied to solve the inversion problem using the finite data at one interior point in the space domain. The inversion fractional orders with random noisy data give good approximations to the exact order demonstrating the efficiency of the inversion algorithm and numerical stability of the inversion problem.
Directory of Open Access Journals (Sweden)
Markus Spiliotis
Full Text Available Inverse fusion PCR cloning (IFPC is an easy, PCR based three-step cloning method that allows the seamless and directional insertion of PCR products into virtually all plasmids, this with a free choice of the insertion site. The PCR-derived inserts contain a vector-complementary 5'-end that allows a fusion with the vector by an overlap extension PCR, and the resulting amplified insert-vector fusions are then circularized by ligation prior transformation. A minimal amount of starting material is needed and experimental steps are reduced. Untreated circular plasmid, or alternatively bacteria containing the plasmid, can be used as templates for the insertion, and clean-up of the insert fragment is not urgently required. The whole cloning procedure can be performed within a minimal hands-on time and results in the generation of hundreds to ten-thousands of positive colonies, with a minimal background.
International Nuclear Information System (INIS)
Hicks, H.R.; Dory, R.A.; Holmes, J.A.
1983-01-01
We illustrate in some detail a 2D inverse-equilibrium solver that was constructed to analyze tokamak configurations and stellarators (the latter in the context of the average method). To ensure that the method is suitable not only to determine equilibria, but also to provide appropriately represented data for existing stability codes, it is important to be able to control the Jacobian, tilde J is identical to delta(R,Z)/delta(rho, theta). The form chosen is tilde J = J 0 (rho)R/sup l/rho where rho is a flux surface label, and l is an integer. The initial implementation is for a fixed conducting-wall boundary, but the technique can be extended to a free-boundary model
Nuclear Hartree-Fock approximation testing and other related approximations
International Nuclear Information System (INIS)
Cohenca, J.M.
1970-01-01
Hartree-Fock, and Tamm-Dancoff approximations are tested for angular momentum of even-even nuclei. Wave functions, energy levels and momenta are comparatively evaluated. Quadripole interactions are studied following the Elliott model. Results are applied to Ne 20 [pt
Transmuted Generalized Inverse Weibull Distribution
Merovci, Faton; Elbatal, Ibrahim; Ahmed, Alaa
2013-01-01
A generalization of the generalized inverse Weibull distribution so-called transmuted generalized inverse Weibull dis- tribution is proposed and studied. We will use the quadratic rank transmutation map (QRTM) in order to generate a flexible family of probability distributions taking generalized inverse Weibull distribution as the base value distribution by introducing a new parameter that would offer more distributional flexibility. Various structural properties including explicit expression...
Solving of L0 norm constrained EEG inverse problem.
Xu, Peng; Lei, Xu; Hu, Xiao; Yao, Dezhong
2009-01-01
l(0) norm is an effective constraint used to solve EEG inverse problem for a sparse solution. However, due to the discontinuous and un-differentiable properties, it is an open issue to solve the l(0) norm constrained problem, which is usually instead solved by using some alternative functions like l(1) norm to approximate l(0) norm. In this paper, a continuous and differentiable function having the same form as the transfer function of Butterworth low-pass filter is introduced to approximate l(0) norm constraint involved in EEG inverse problem. The new approximation based approach was compared with l(1) norm and LORETA solutions on a realistic head model using simulated sources. The preliminary results show that this alternative approximation to l(0) norm is promising for the estimation of EEG sources with sparse distribution.
Shearlets and Optimally Sparse Approximations
DEFF Research Database (Denmark)
Kutyniok, Gitta; Lemvig, Jakob; Lim, Wang-Q
2012-01-01
Multivariate functions are typically governed by anisotropic features such as edges in images or shock fronts in solutions of transport-dominated equations. One major goal both for the purpose of compression as well as for an efficient analysis is the provision of optimally sparse approximations...... optimally sparse approximations of this model class in 2D as well as 3D. Even more, in contrast to all other directional representation systems, a theory for compactly supported shearlet frames was derived which moreover also satisfy this optimality benchmark. This chapter shall serve as an introduction...... to and a survey about sparse approximations of cartoon-like images by band-limited and also compactly supported shearlet frames as well as a reference for the state-of-the-art of this research field....
Diophantine approximation and Dirichlet series
Queffélec, Hervé
2013-01-01
This self-contained book will benefit beginners as well as researchers. It is devoted to Diophantine approximation, the analytic theory of Dirichlet series, and some connections between these two domains, which often occur through the Kronecker approximation theorem. Accordingly, the book is divided into seven chapters, the first three of which present tools from commutative harmonic analysis, including a sharp form of the uncertainty principle, ergodic theory and Diophantine approximation to be used in the sequel. A presentation of continued fraction expansions, including the mixing property of the Gauss map, is given. Chapters four and five present the general theory of Dirichlet series, with classes of examples connected to continued fractions, the famous Bohr point of view, and then the use of random Dirichlet series to produce non-trivial extremal examples, including sharp forms of the Bohnenblust-Hille theorem. Chapter six deals with Hardy-Dirichlet spaces, which are new and useful Banach spaces of anal...
Approximations to camera sensor noise
Jin, Xiaodan; Hirakawa, Keigo
2013-02-01
Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.
Rational approximations for tomographic reconstructions
International Nuclear Information System (INIS)
Reynolds, Matthew; Beylkin, Gregory; Monzón, Lucas
2013-01-01
We use optimal rational approximations of projection data collected in x-ray tomography to improve image resolution. Under the assumption that the object of interest is described by functions with jump discontinuities, for each projection we construct its rational approximation with a small (near optimal) number of terms for a given accuracy threshold. This allows us to augment the measured data, i.e., double the number of available samples in each projection or, equivalently, extend (double) the domain of their Fourier transform. We also develop a new, fast, polar coordinate Fourier domain algorithm which uses our nonlinear approximation of projection data in a natural way. Using augmented projections of the Shepp–Logan phantom, we provide a comparison between the new algorithm and the standard filtered back-projection algorithm. We demonstrate that the reconstructed image has improved resolution without additional artifacts near sharp transitions in the image. (paper)
Tsuruta, S; Misztal, I; Strandén, I
2001-05-01
Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is
A preconditioned inexact newton method for nonlinear sparse electromagnetic imaging
Desmal, Abdulla
2015-03-01
A nonlinear inversion scheme for the electromagnetic microwave imaging of domains with sparse content is proposed. Scattering equations are constructed using a contrast-source (CS) formulation. The proposed method uses an inexact Newton (IN) scheme to tackle the nonlinearity of these equations. At every IN iteration, a system of equations, which involves the Frechet derivative (FD) matrix of the CS operator, is solved for the IN step. A sparsity constraint is enforced on the solution via thresholded Landweber iterations, and the convergence is significantly increased using a preconditioner that levels the FD matrix\\'s singular values associated with contrast and equivalent currents. To increase the accuracy, the weight of the regularization\\'s penalty term is reduced during the IN iterations consistently with the scheme\\'s quadratic convergence. At the end of each IN iteration, an additional thresholding, which removes small \\'ripples\\' that are produced by the IN step, is applied to maintain the solution\\'s sparsity. Numerical results demonstrate the applicability of the proposed method in recovering sparse and discontinuous dielectric profiles with high contrast values.
Approximate reasoning in physical systems
International Nuclear Information System (INIS)
Mutihac, R.
1991-01-01
The theory of fuzzy sets provides excellent ground to deal with fuzzy observations (uncertain or imprecise signals, wavelengths, temperatures,etc.) fuzzy functions (spectra and depth profiles) and fuzzy logic and approximate reasoning. First, the basic ideas of fuzzy set theory are briefly presented. Secondly, stress is put on application of simple fuzzy set operations for matching candidate reference spectra of a spectral library to an unknown sample spectrum (e.g. IR spectroscopy). Thirdly, approximate reasoning is applied to infer an unknown property from information available in a database (e.g. crystal systems). Finally, multi-dimensional fuzzy reasoning techniques are suggested. (Author)
Face Recognition using Approximate Arithmetic
DEFF Research Database (Denmark)
Marso, Karol
Face recognition is image processing technique which aims to identify human faces and found its use in various diﬀerent ﬁelds for example in security. Throughout the years this ﬁeld evolved and there are many approaches and many diﬀerent algorithms which aim to make the face recognition as eﬀective...... processing applications the results do not need to be completely precise and use of the approximate arithmetic can lead to reduction in terms of delay, space and power consumption. In this paper we examine possible use of approximate arithmetic in face recognition using Eigenfaces algorithm....
Weston, Brian; Nourgaliev, Robert; Delplanque, Jean-Pierre
2017-11-01
We present a new block-based Schur complement preconditioner for simulating all-speed compressible flow with phase change. The conservation equations are discretized with a reconstructed Discontinuous Galerkin method and integrated in time with fully implicit time discretization schemes. The resulting set of non-linear equations is converged using a robust Newton-Krylov framework. Due to the stiffness of the underlying physics associated with stiff acoustic waves and viscous material strength effects, we solve for the primitive-variables (pressure, velocity, and temperature). To enable convergence of the highly ill-conditioned linearized systems, we develop a physics-based preconditioner, utilizing approximate block factorization techniques to reduce the fully-coupled 3×3 system to a pair of reduced 2×2 systems. We demonstrate that our preconditioned Newton-Krylov framework converges on very stiff multi-physics problems, corresponding to large CFL and Fourier numbers, with excellent algorithmic and parallel scalability. Results are shown for the classic lid-driven cavity flow problem as well as for 3D laser-induced phase change. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Directory of Open Access Journals (Sweden)
Fan Yuxin
2014-12-01
Full Text Available A fluid–structure interaction method combining a nonlinear finite element algorithm with a preconditioning finite volume method is proposed in this paper to simulate parachute transient dynamics. This method uses a three-dimensional membrane–cable fabric model to represent a parachute system at a highly folded configuration. The large shape change during parachute inflation is computed by the nonlinear Newton–Raphson iteration and the linear system equation is solved by the generalized minimal residual (GMRES method. A membrane wrinkling algorithm is also utilized to evaluate the special uniaxial tension state of membrane elements on the parachute canopy. In order to avoid large time expenses during structural nonlinear iteration, the implicit Hilber–Hughes–Taylor (HHT time integration method is employed. For the fluid dynamic simulations, the Roe and HLLC (Harten–Lax–van Leer contact scheme has been modified and extended to compute flow problems at all speeds. The lower–upper symmetric Gauss–Seidel (LU-SGS approximate factorization is applied to accelerate the numerical convergence speed. Finally, the test model of a highly folded C-9 parachute is simulated at a prescribed speed and the results show similar characteristics compared with experimental results and previous literature.
Refined isogeometric analysis for a preconditioned conjugate gradient solver
Garcia, Daniel
2018-02-12
Starting from a highly continuous Isogeometric Analysis (IGA) discretization, refined Isogeometric Analysis (rIGA) introduces C0 hyperplanes that act as separators for the direct LU factorization solver. As a result, the total computational cost required to solve the corresponding system of equations using a direct LU factorization solver dramatically reduces (up to a factor of 55) Garcia et al. (2017). At the same time, rIGA enriches the IGA spaces, thus improving the best approximation error. In this work, we extend the complexity analysis of rIGA to the case of iterative solvers. We build an iterative solver as follows: we first construct the Schur complements using a direct solver over small subdomains (macro-elements). We then assemble those Schur complements into a global skeleton system. Subsequently, we solve this system iteratively using Conjugate Gradients (CG) with an incomplete LU (ILU) preconditioner. For a 2D Poisson model problem with a structured mesh and a uniform polynomial degree of approximation, rIGA achieves moderate savings with respect to IGA in terms of the number of Floating Point Operations (FLOPs) and computational time (in seconds) required to solve the resulting system of linear equations. For instance, for a mesh with four million elements and polynomial degree p=3, the iterative solver is approximately 2.6 times faster (in time) when applied to the rIGA system than to the IGA one. These savings occur because the skeleton rIGA system contains fewer non-zero entries than the IGA one. The opposite situation occurs for 3D problems, and as a result, 3D rIGA discretizations provide no gains with respect to their IGA counterparts when considering iterative solvers.
Calculation of the inverse data space via sparse inversion
Saragiotis, Christos; Doulgeris, Panagiotis C.; Verschuur, Dirk Jacob Eric
2011-01-01
The inverse data space provides a natural separation of primaries and surface-related multiples, as the surface multiples map onto the area around the origin while the primaries map elsewhere. However, the calculation of the inverse data is far from
Inverse feasibility problems of the inverse maximum flow problems
Indian Academy of Sciences (India)
199–209. c Indian Academy of Sciences. Inverse feasibility problems of the inverse maximum flow problems. ADRIAN DEACONU. ∗ and ELEONOR CIUREA. Department of Mathematics and Computer Science, Faculty of Mathematics and Informatics, Transilvania University of Brasov, Brasov, Iuliu Maniu st. 50,. Romania.
Tian, Shan; Zhu, Fengping; Hu, Ruiping; Tian, Song; Chen, Xingxing; Lou, Dan; Cao, Bing; Chen, Qiulei; Li, Bai; Li, Fang; Bai, Yulong; Wu, Yi; Zhu, Yulian
2018-01-01
Exercise preconditioning is a simple and effective way to prevent ischemia. This paper further provided the mechanism in hemodynamic aspects at the cellular level. To study the anti-apoptotic effects of fluid mechanics preconditioning, Cultured rats brain microvascular endothelial cells were given fluid intervention in a parallel plate flow chamber before oxygen glucose deprivation. It showed that fluid mechanics preconditioning could inhibit the apoptosis of endothelial cells, and this process might be mediated by the shear stress activation of Tie-2 on cells membrane surface and Bcl-2 on the mitochondria surface. Copyright © 2017 Elsevier B.V. All rights reserved.
Approximate Reanalysis in Topology Optimization
DEFF Research Database (Denmark)
Amir, Oded; Bendsøe, Martin P.; Sigmund, Ole
2009-01-01
In the nested approach to structural optimization, most of the computational effort is invested in the solution of the finite element analysis equations. In this study, the integration of an approximate reanalysis procedure into the framework of topology optimization of continuum structures...
Approximate Matching of Hierarchial Data
DEFF Research Database (Denmark)
Augsten, Nikolaus
-grams of a tree are all its subtrees of a particular shape. Intuitively, two trees are similar if they have many pq-grams in common. The pq-gram distance is an efficient and effective approximation of the tree edit distance. We analyze the properties of the pq-gram distance and compare it with the tree edit...
Approximation of Surfaces by Cylinders
DEFF Research Database (Denmark)
Randrup, Thomas
1998-01-01
We present a new method for approximation of a given surface by a cylinder surface. It is a constructive geometric method, leading to a monorail representation of the cylinder surface. By use of a weighted Gaussian image of the given surface, we determine a projection plane. In the orthogonal...
Approximation properties of haplotype tagging
Directory of Open Access Journals (Sweden)
Dreiseitl Stephan
2006-01-01
Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns, disease association studies are facilitated by identifying SNPs that allow the unique identification of such patterns. This process, known as haplotype tagging, is formulated as a combinatorial optimization problem and analyzed in terms of complexity and approximation properties. Results It is shown that the tagging problem is NP-hard but approximable within 1 + ln((n2 - n/2 for n haplotypes but not approximable within (1 - ε ln(n/2 for any ε > 0 unless NP ⊂ DTIME(nlog log n. A simple, very easily implementable algorithm that exhibits the above upper bound on solution quality is presented. This algorithm has running time O((2m - p + 1 ≤ O(m(n2 - n/2 where p ≤ min(n, m for n haplotypes of size m. As we show that the approximation bound is asymptotically tight, the algorithm presented is optimal with respect to this asymptotic bound. Conclusion The haplotype tagging problem is hard, but approachable with a fast, practical, and surprisingly simple algorithm that cannot be significantly improved upon on a single processor machine. Hence, significant improvement in computatational efforts expended can only be expected if the computational effort is distributed and done in parallel.
All-Norm Approximation Algorithms
Azar, Yossi; Epstein, Leah; Richter, Yossi; Woeginger, Gerhard J.; Penttonen, Martti; Meineche Schmidt, Erik
2002-01-01
A major drawback in optimization problems and in particular in scheduling problems is that for every measure there may be a different optimal solution. In many cases the various measures are different ℓ p norms. We address this problem by introducing the concept of an All-norm ρ-approximation
Truthful approximations to range voting
DEFF Research Database (Denmark)
Filos-Ratsika, Aris; Miltersen, Peter Bro
We consider the fundamental mechanism design problem of approximate social welfare maximization under general cardinal preferences on a finite number of alternatives and without money. The well-known range voting scheme can be thought of as a non-truthful mechanism for exact social welfare...
On badly approximable complex numbers
DEFF Research Database (Denmark)
Esdahl-Schou, Rune; Kristensen, S.
We show that the set of complex numbers which are badly approximable by ratios of elements of , where has maximal Hausdorff dimension. In addition, the intersection of these sets is shown to have maximal dimension. The results remain true when the sets in question are intersected with a suitably...
Approximate reasoning in decision analysis
Energy Technology Data Exchange (ETDEWEB)
Gupta, M M; Sanchez, E
1982-01-01
The volume aims to incorporate the recent advances in both theory and applications. It contains 44 articles by 74 contributors from 17 different countries. The topics considered include: membership functions; composite fuzzy relations; fuzzy logic and inference; classifications and similarity measures; expert systems and medical diagnosis; psychological measurements and human behaviour; approximate reasoning and decision analysis; and fuzzy clustering algorithms.
Rational approximation of vertical segments
Salazar Celis, Oliver; Cuyt, Annie; Verdonk, Brigitte
2007-08-01
In many applications, observations are prone to imprecise measurements. When constructing a model based on such data, an approximation rather than an interpolation approach is needed. Very often a least squares approximation is used. Here we follow a different approach. A natural way for dealing with uncertainty in the data is by means of an uncertainty interval. We assume that the uncertainty in the independent variables is negligible and that for each observation an uncertainty interval can be given which contains the (unknown) exact value. To approximate such data we look for functions which intersect all uncertainty intervals. In the past this problem has been studied for polynomials, or more generally for functions which are linear in the unknown coefficients. Here we study the problem for a particular class of functions which are nonlinear in the unknown coefficients, namely rational functions. We show how to reduce the problem to a quadratic programming problem with a strictly convex objective function, yielding a unique rational function which intersects all uncertainty intervals and satisfies some additional properties. Compared to rational least squares approximation which reduces to a nonlinear optimization problem where the objective function may have many local minima, this makes the new approach attractive.
Pythagorean Approximations and Continued Fractions
Peralta, Javier
2008-01-01
In this article, we will show that the Pythagorean approximations of [the square root of] 2 coincide with those achieved in the 16th century by means of continued fractions. Assuming this fact and the known relation that connects the Fibonacci sequence with the golden section, we shall establish a procedure to obtain sequences of rational numbers…
Ultrafast Approximation for Phylogenetic Bootstrap
Bui Quang Minh, [No Value; Nguyen, Thi; von Haeseler, Arndt
Nonparametric bootstrap has been a widely used tool in phylogenetic analysis to assess the clade support of phylogenetic trees. However, with the rapidly growing amount of data, this task remains a computational bottleneck. Recently, approximation methods such as the RAxML rapid bootstrap (RBS) and
Mathematical properties of numerical inversion for jet calibrations
Energy Technology Data Exchange (ETDEWEB)
Cukierman, Aviv [Physics Department, Stanford University, Stanford, CA 94305 (United States); SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025 (United States); Nachman, Benjamin, E-mail: bnachman@cern.ch [Physics Department, Stanford University, Stanford, CA 94305 (United States); SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025 (United States); Physics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94704 (United States)
2017-06-21
Numerical inversion is a general detector calibration technique that is independent of the underlying spectrum. This procedure is formalized and important statistical properties are presented, using high energy jets at the Large Hadron Collider as an example setting. In particular, numerical inversion is inherently biased and common approximations to the calibrated jet energy tend to over-estimate the resolution. Analytic approximations to the closure and calibrated resolutions are demonstrated to effectively predict the full forms under realistic conditions. Finally, extensions of numerical inversion are presented which can reduce the inherent biases. These methods will be increasingly important to consider with degraded resolution at low jet energies due to a much higher instantaneous luminosity in the near future.
Sbarouni, Eftihia; Iliodromitis, Efstathios K; Zoga, Anastasia; Vlachou, Georgia; Andreadou, Ioanna; Kremastinos, Dimitrios Th
2006-08-01
We have previously shown that estrogen administered in ovariectomized female rabbits significantly reduce myocardial infarct size. We now investigated whether the phytoestrogen genistein similarly protects ischemic myocardium and whether this is associated with its antioxidant properties. In addition, we examined whether genistein abolishes preconditioning, since at high doses, it inhibits tyrosine kinase. We studied five groups of New Zealand white female rabbits. Group A (n = 12) were normal controls, group B (n = 14) were ovariectomized 4 weeks prior to the experiment, group C (n = 10) were ovariectomized and treated with genistein (0.2 mg kg(-1) day(-1) subcutaneously) for 4 weeks before the experiment, group D (n = 12) had intact gonads and were treated with genistein (0.2 mg kg(-1) day(-1) subcutaneously) for 4 weeks before the experiment and group E (n = 8) were ovariectomized 4 weeks prior to the experiment and treated with a single dose of genistein (0.2 mg kg(-1) day(-1) subcutaneously) just prior to the experiment. All animals underwent 30 min of heart ischemia and 120 min of reperfusion, with (subgroup I) or without (subgroup II) preconditioning. Malondialdehyde (MDA) concentration just before the experiment was determined. We found significant differences between the groups-p protect ischemic myocardium in either ovariectomized or non-ovariectomized animals-BII vs CII and AII vs DII, p = NS. There was no significant difference between the preconditioned animals, with intact gonads or ovariectomized (AI vs BI, p = NS), ovariectomized with or without genistein (BI vs CI, p = NS) and non-ovariectomized whether treated with genistein or not (AI vs DI, p = NS). A single dose of genistein did not offer any protection (EII vs BII, p = NS), nor did it modify the preconditioning effect (EI vs BI, p = NS). We found no significant difference in MDA plasma levels between the groups. Genistein, at this dose, does not reduce infarct size per se nor abolishes the
Confidence Intervals for Asbestos Fiber Counts: Approximate Negative Binomial Distribution.
Bartley, David; Slaven, James; Harper, Martin
2017-03-01
The negative binomial distribution is adopted for analyzing asbestos fiber counts so as to account for both the sampling errors in capturing only a finite number of fibers and the inevitable human variation in identifying and counting sampled fibers. A simple approximation to this distribution is developed for the derivation of quantiles and approximate confidence limits. The success of the approximation depends critically on the use of Stirling's expansion to sufficient order, on exact normalization of the approximating distribution, on reasonable perturbation of quantities from the normal distribution, and on accurately approximating sums by inverse-trapezoidal integration. Accuracy of the approximation developed is checked through simulation and also by comparison to traditional approximate confidence intervals in the specific case that the negative binomial distribution approaches the Poisson distribution. The resulting statistics are shown to relate directly to early research into the accuracy of asbestos sampling and analysis. Uncertainty in estimating mean asbestos fiber concentrations given only a single count is derived. Decision limits (limits of detection) and detection limits are considered for controlling false-positive and false-negative detection assertions and are compared to traditional limits computed assuming normal distributions. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.
Face inversion increases attractiveness.
Leder, Helmut; Goller, Juergen; Forster, Michael; Schlageter, Lena; Paul, Matthew A
2017-07-01
Assessing facial attractiveness is a ubiquitous, inherent, and hard-wired phenomenon in everyday interactions. As such, it has highly adapted to the default way that faces are typically processed: viewing faces in upright orientation. By inverting faces, we can disrupt this default mode, and study how facial attractiveness is assessed. Faces, rotated at 90 (tilting to either side) and 180°, were rated on attractiveness and distinctiveness scales. For both orientations, we found that faces were rated more attractive and less distinctive than upright faces. Importantly, these effects were more pronounced for faces rated low in upright orientation, and smaller for highly attractive faces. In other words, the less attractive a face was, the more it gained in attractiveness by inversion or rotation. Based on these findings, we argue that facial attractiveness assessments might not rely on the presence of attractive facial characteristics, but on the absence of distinctive, unattractive characteristics. These unattractive characteristics are potentially weighed against an individual, attractive prototype in assessing facial attractiveness. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Inverse problem in hydrogeology
Carrera, Jesús; Alcolea, Andrés; Medina, Agustín; Hidalgo, Juan; Slooten, Luit J.
2005-03-01
The state of the groundwater inverse problem is synthesized. Emphasis is placed on aquifer characterization, where modelers have to deal with conceptual model uncertainty (notably spatial and temporal variability), scale dependence, many types of unknown parameters (transmissivity, recharge, boundary conditions, etc.), nonlinearity, and often low sensitivity of state variables (typically heads and concentrations) to aquifer properties. Because of these difficulties, calibration cannot be separated from the modeling process, as it is sometimes done in other fields. Instead, it should be viewed as one step in the process of understanding aquifer behavior. In fact, it is shown that actual parameter estimation methods do not differ from each other in the essence, though they may differ in the computational details. It is argued that there is ample room for improvement in groundwater inversion: development of user-friendly codes, accommodation of variability through geostatistics, incorporation of geological information and different types of data (temperature, occurrence and concentration of isotopes, age, etc.), proper accounting of uncertainty, etc. Despite this, even with existing codes, automatic calibration facilitates enormously the task of modeling. Therefore, it is contended that its use should become standard practice. L'état du problème inverse des eaux souterraines est synthétisé. L'accent est placé sur la caractérisation de l'aquifère, où les modélisateurs doivent jouer avec l'incertitude des modèles conceptuels (notamment la variabilité spatiale et temporelle), les facteurs d'échelle, plusieurs inconnues sur différents paramètres (transmissivité, recharge, conditions aux limites, etc.), la non linéarité, et souvent la sensibilité de plusieurs variables d'état (charges hydrauliques, concentrations) des propriétés de l'aquifère. A cause de ces difficultés, le calibrage ne peut êtreséparé du processus de modélisation, comme c'est le
Zhang, Dongliang
2013-01-01
To increase the illumination of the subsurface and to eliminate the dependency of FWI on the source wavelet, we propose multiples waveform inversion (MWI) that transforms each hydrophone into a virtual point source with a time history equal to that of the recorded data. These virtual sources are used to numerically generate downgoing wavefields that are correlated with the backprojected surface-related multiples to give the migration image. Since the recorded data are treated as the virtual sources, knowledge of the source wavelet is not required, and the subsurface illumination is greatly enhanced because the entire free surface acts as an extended source compared to the radiation pattern of a traditional point source. Numerical tests on the Marmousi2 model show that the convergence rate and the spatial resolution of MWI is, respectively, faster and more accurate then FWI. The potential pitfall with this method is that the multiples undergo more than one roundtrip to the surface, which increases attenuation and reduces spatial resolution. This can lead to less resolved tomograms compared to conventional FWI. The possible solution is to combine both FWI and MWI in inverting for the subsurface velocity distribution.
An interpretation of signature inversion
International Nuclear Information System (INIS)
Onishi, Naoki; Tajima, Naoki
1988-01-01
An interpretation in terms of the cranking model is presented to explain why signature inversion occurs for positive γ of the axially asymmetric deformation parameter and emerges into specific orbitals. By introducing a continuous variable, the eigenvalue equation can be reduced to a one dimensional Schroedinger equation by means of which one can easily understand the cause of signature inversion. (author)
Inverse problems for Maxwell's equations
Romanov, V G
1994-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Algebraic properties of generalized inverses
Cvetković‐Ilić, Dragana S
2017-01-01
This book addresses selected topics in the theory of generalized inverses. Following a discussion of the “reverse order law” problem and certain problems involving completions of operator matrices, it subsequently presents a specific approach to solving the problem of the reverse order law for {1} -generalized inverses. Particular emphasis is placed on the existence of Drazin invertible completions of an upper triangular operator matrix; on the invertibility and different types of generalized invertibility of a linear combination of operators on Hilbert spaces and Banach algebra elements; on the problem of finding representations of the Drazin inverse of a 2x2 block matrix; and on selected additive results and algebraic properties for the Drazin inverse. In addition to the clarity of its content, the book discusses the relevant open problems for each topic discussed. Comments on the latest references on generalized inverses are also included. Accordingly, the book will be useful for graduate students, Ph...
Parameterization analysis and inversion for orthorhombic media
Masmoudi, Nabil
2018-05-01
Accounting for azimuthal anisotropy is necessary for the processing and inversion of wide-azimuth and wide-aperture seismic data because wave speeds naturally depend on the wave propagation direction. Orthorhombic anisotropy is considered the most effective anisotropic model that approximates the azimuthal anisotropy we observe in seismic data. In the framework of full wave form inversion (FWI), the large number of parameters describing orthorhombic media exerts a considerable trade-off and increases the non-linearity of the inversion problem. Choosing a suitable parameterization for the model, and identifying which parameters in that parameterization could be well resolved, are essential to a successful inversion. In this thesis, I derive the radiation patterns for different acoustic orthorhombic parameterization. Analyzing the angular dependence of the scattering of the parameters of different parameterizations starting with the conventionally used notation, I assess the potential trade-off between the parameters and the resolution in describing the data and inverting for the parameters. In order to build practical inversion strategies, I suggest new parameters (called deviation parameters) for a new parameterization style in orthorhombic media. The novel parameters denoted ∈d, ƞd and δd are dimensionless and represent a measure of deviation between the vertical planes in orthorhombic anisotropy. The main feature of the deviation parameters consists of keeping the scattering of the vertical transversely isotropic (VTI) parameters stationary with azimuth. Using these scattering features, we can condition FWI to invert for the parameters which the data are sensitive to, at different stages, scales, and locations in the model. With this parameterization, the data are mainly sensitive to the scattering of 3 parameters (out of six that describe an acoustic orthorhombic medium): the horizontal velocity in the x1 direction, ∈1 which provides scattering mainly near
APPROXIMATION AND INVERSION OF A COMPLEX METEOROLOGICAL SYSTEM VIA LOCAL LINEAR FILTERS. (R825381)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
Seismic Imaging and Velocity Analysis Using a Pseudo Inverse to the Extended Born Approximation
Alali, Abdullah A.
2018-01-01
the correct model. The most commonly used technique is differential semblance optimization (DSO), which depends on applying an image extension and penalizing the energy in the non-physical extension. However, studies show that the conventional DSO gradient
Beyond the random phase approximation
DEFF Research Database (Denmark)
Olsen, Thomas; Thygesen, Kristian S.
2013-01-01
We assess the performance of a recently proposed renormalized adiabatic local density approximation (rALDA) for ab initio calculations of electronic correlation energies in solids and molecules. The method is an extension of the random phase approximation (RPA) derived from time-dependent density...... functional theory and the adiabatic connection fluctuation-dissipation theorem and contains no fitted parameters. The new kernel is shown to preserve the accurate description of dispersive interactions from RPA while significantly improving the description of short-range correlation in molecules, insulators......, and metals. For molecular atomization energies, the rALDA is a factor of 7 better than RPA and a factor of 4 better than the Perdew-Burke-Ernzerhof (PBE) functional when compared to experiments, and a factor of 3 (1.5) better than RPA (PBE) for cohesive energies of solids. For transition metals...
Hydrogen: Beyond the Classic Approximation
International Nuclear Information System (INIS)
Scivetti, Ivan
2003-01-01
The classical nucleus approximation is the most frequently used approach for the resolution of problems in condensed matter physics.However, there are systems in nature where it is necessary to introduce the nuclear degrees of freedom to obtain a correct description of the properties.Examples of this, are the systems with containing hydrogen.In this work, we have studied the resolution of the quantum nuclear problem for the particular case of the water molecule.The Hartree approximation has been used, i.e. we have considered that the nuclei are distinguishable particles.In addition, we have proposed a model to solve the tunneling process, which involves the resolution of the nuclear problem for configurations of the system away from its equilibrium position
Approximation errors during variance propagation
International Nuclear Information System (INIS)
Dinsmore, Stephen
1986-01-01
Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given
Valdé s, Felipe; Andriulli, Francesco P.; Bagci, Hakan; Michielssen, Eric
2011-01-01
A new regularized single source equation for analyzing scattering from homogeneous penetrable objects is presented. The proposed equation is a linear combination of a Calderón-preconditioned single source electric field integral equation and a
Hill, Mary C.
1990-01-01
This report documents PCG2 : a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model . PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options : modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers . Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.
WKB approximation in atomic physics
International Nuclear Information System (INIS)
Karnakov, Boris Mikhailovich
2013-01-01
Provides extensive coverage of the Wentzel-Kramers-Brillouin approximation and its applications. Presented as a sequence of problems with highly detailed solutions. Gives a concise introduction for calculating Rydberg states, potential barriers and quasistationary systems. This book has evolved from lectures devoted to applications of the Wentzel-Kramers-Brillouin- (WKB or quasi-classical) approximation and of the method of 1/N -expansion for solving various problems in atomic and nuclear physics. The intent of this book is to help students and investigators in this field to extend their knowledge of these important calculation methods in quantum mechanics. Much material is contained herein that is not to be found elsewhere. WKB approximation, while constituting a fundamental area in atomic physics, has not been the focus of many books. A novel method has been adopted for the presentation of the subject matter, the material is presented as a succession of problems, followed by a detailed way of solving them. The methods introduced are then used to calculate Rydberg states in atomic systems and to evaluate potential barriers and quasistationary states. Finally, adiabatic transition and ionization of quantum systems are covered.
Deja, Marek A; Wiaderkiewicz, Ryszard; Czekaj, Piotr; Czech, Ewa; Malinowski, Marcin; Machej, Leszek; Węglarzy, Andrzej; Kowalówka, Adam; Piekarska, Magda; Szurlej, Bartosz; Latusek, Tomasz
2018-01-01
Remote preconditioning has been shown to be a potent protective phenomenon in many animals. Several studies aimed to demonstrate it was feasible in humans by trying to show its protective effect during cardiac surgery. Of these, some small studies and one larger trial were positive while two other bigger studies showed no effectiveness of remote preconditioning as assessed by levels of postoperatively released cardiac markers. Recently, two large clinical trials also failed to prove the benefit of remote preconditioning in cardiac surgery. No study showed that remote preconditioning actually increases resistance of human myocardium to standardised ischaemic and reperfusion stimulus in experimental settings. In animal studies, remote preconditioning was shown to improve mitochondrial function and structure, but such data on human myocardium are scarce. The aim of the study is to determine whether remote preconditioning protects human myocardium against ischaemia-reperfusion injury in both in vivo and in vitro conditions. The trial is designed as a single-centre, double-blinded, sham-controlled trial of 120 patients. We randomise (1:1) patients referred for coronary artery bypass grafting for stable coronary artery disease to remote preconditioning or "sham" intervention. The remote preconditioning is obtained by three cycles of 5 min inflation and 5 min deflation of a blood pressure cuff on the right arm. Postoperative course including myocardial enzymes profile will be analysed. Moreover, in the in-vitro arm the clinically preconditioned myocardium will be assessed for function, mitochondria structure, and mitochondria-dependent apoptosis. The informed consent of all patients is obtained before enrolment into the study by the investigator. The study conforms to the spirit and the letter of the declaration of Helsinki. In case the effect of remote preconditioning is not measurable in ex-vivo assessment, any future attempt at implementing this phenomenon in clinical
Ghosh, A
1988-08-01
Lanczos and conjugate gradient algorithms are important in computational linear algebra. In this paper, a parallel pipelined realization of these algorithms on a ring of optical linear algebra processors is described. The flow of data is designed to minimize the idle times of the optical multiprocessor and the redundancy of computations. The effects of optical round-off errors on the solutions obtained by the optical Lanczos and conjugate gradient algorithms are analyzed, and it is shown that optical preconditioning can improve the accuracy of these algorithms substantially. Algorithms for optical preconditioning and results of numerical experiments on solving linear systems of equations arising from partial differential equations are discussed. Since the Lanczos algorithm is used mostly with sparse matrices, a folded storage scheme to represent sparse matrices on spatial light modulators is also described.
Parallelization of the preconditioned IDR solver for modern multicore computer systems
Bessonov, O. A.; Fedoseyev, A. I.
2012-10-01
This paper present the analysis, parallelization and optimization approach for the large sparse matrix solver CNSPACK for modern multicore microprocessors. CNSPACK is an advanced solver successfully used for coupled solution of stiff problems arising in multiphysics applications such as CFD, semiconductor transport, kinetic and quantum problems. It employs iterative IDR algorithm with ILU preconditioning (user chosen ILU preconditioning order). CNSPACK has been successfully used during last decade for solving problems in several application areas, including fluid dynamics and semiconductor device simulation. However, there was a dramatic change in processor architectures and computer system organization in recent years. Due to this, performance criteria and methods have been revisited, together with involving the parallelization of the solver and preconditioner using Open MP environment. Results of the successful implementation for efficient parallelization are presented for the most advances computer system (Intel Core i7-9xx or two-processor Xeon 55xx/56xx).
The Conceptual Preconditions of Studying Collective Professional Mobility of Management Personnel
Directory of Open Access Journals (Sweden)
Doronin Andrii V.
2016-08-01
Full Text Available The preconditions and problems of developing the concept of the study and transformation of collective professional mobility of management personnel are generalized. The necessity of specifying the content and structure of the scientific and methodological concept of «paradigm» is justified. The possibility of using philosophy and economic theory to determine the initial ideas on the development of technique for studying collective professional mobility of management personnel are analyzed; contradictions, which resolution would create a constructive theoretical basis of such a study are revealed. The need to focus on the interdisciplinary approach in the development of the conceptual preconditions of studying collective professional mobility is substantiated. The versions of the world view allowing to ensure productive discussions of representatives of various scientific disciplines at the phenomenological stage of building a new paradigm are developed.
Luo, Yukun; Fang, Jun; Fan, Lin; Lin, Chaogui; Chen, Zhaoyang; Chen, Lianglong
2012-10-01
To investigate the role of connexin 43-formed hemichannels in cell volume regulation induced by simulated ischemia/reperfusion (SI/R). Mouse cardiomyocytes isolated on a Langendorff apparatus with enzyme solution were aliquoted into control, SI/R and SI/R +octanol groups. Calcein-AM was used to stain the cells and the cell volume was measured with confocal microscope by stack scanning. Trypan blue was used to measure the cell viability after the treatments. Calcein-AM staining and cofocal microscopy yielded stable and reproducible results for cell volume measurement. Mouse cardiomyocytes subjected to simulated SI/R showed obvious cell swelling as compared with the control cells [(126∓6)% vs 100%, Poctanol preconditioning significantly attenuated the cell swelling [(113∓6)%, Poctanol preconditioning obviously reduced the viability of the cells with SI/R challenge [(31∓2)%, Poctanol can alleviate the cell swelling to enhance the viability of the cardiomyocytes following SI/R.
Energy Technology Data Exchange (ETDEWEB)
Mirrione, M.M.; Mirrione, M.M.; Konomosa, D.K.; Ioradanis, G.; Dewey, S.L.; Agzzid, A.; Heppnerd, F.L.; Tsirka, St.E.
2010-04-01
Activated microglia have been associated with neurodegeneration in patients and in animal models of Temporal Lobe Epilepsy (TLE), however their precise functions as neurotoxic or neuroprotective is a topic of significant investigation. To explore this, we examined the effects of pilocarpine-induced seizures in transgenic mice where microglia/macrophages were conditionally ablated. We found that unilateral ablation of microglia from the dorsal hippocampus did not alter acute seizure sensitivity. However, when this procedure was coupled with lipopolysaccharide (LPS) preconditioning (1 mg/kg given 24 h prior to acute seizure), we observed a significant pro-convulsant phenomenon. This effect was associated with lower metabolic activation in the ipsilateral hippocampus during acute seizures, and could be attributed to activity in the mossy fiber pathway. These findings reveal that preconditioning with LPS 24 h prior to seizure induction may have a protective effect which is abolished by unilateral hippocampal microglia/macrophage ablation.
Parallelized preconditioned BiCGStab solution of sparse linear system equations in F-COBRA-TF
International Nuclear Information System (INIS)
Geemert, Rene van; Glück, Markus; Riedmann, Michael; Gabriel, Harry
2011-01-01
Recently, the in-house development of a preconditioned and parallelized BiCGStab solver has been pursued successfully in AREVA’s advanced sub-channel code F-COBRA-TF. This solver can be run either in a sequential computation mode on a single CPU, or in a parallel computation mode on multiple parallel CPUs. The developed procedure enables the computation of several thousands of successive sparse linear system solutions in F-COBRA-TF with acceptable wall clock run times. The current paper provides general information about F-COBRA-TF in terms of modeling capabilities and application areas, and points out where the relevance arises for the efficient iterative solution of sparse linear systems. Furthermore, the preconditioning and parallelization strategies in the developed BiCGStab iterative solution approach are discussed. The paper is concluded with a number of verification examples. (author)
International Nuclear Information System (INIS)
Chen, G.S.
1997-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used. TFQMR (transpose free quasi-minimal residual algorithm), CGS (conjuage gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These sub-routines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. (author)
Directory of Open Access Journals (Sweden)
Yi ZHANG
2014-12-01
Full Text Available Objective To evaluate the protective effects of endoplasmic reticulum stress preconditioning induced by 2-deoxyglucose (2-DG on hippocampal neurons of rats with status epilepticus (SE and the possible mechanism. Methods Ninety Sprague-Dawley (SD rats were randomly enrolled into preconditioning group (N = 30, SE group (N = 30 and control group (N = 30. Each group was divided into 6 subsets (N = 5 according to six time points (before seizure, 6 h, 12 h, 1 d, 2 d and 7 d after seizure. The preconditioning group was administered 2-DG intraperitoneally with a dose of 150 mg/kg for 7 days, and the lithium-pilocarpine induced SE rat model was established on both preconditioning group and SE group. The rats were sacrificed at the above six time points, and the brains were removed to make paraffin sections. Nissl staining was performed by toluidine blue to evaluate the hippocampal neuronal damage after seizure, and the number of survival neurons in hippocampal CA1 and CA3 regions of the rats were counted. Immunohistochemical staining was performed to detect the expressions of glucose regulated protein 78 (GRP78 and X-box binding protein 1 (XBP-1 in hippocampal CA3 region of the rats. Results The number of survival neurons in preconditioning group was much more than that in SE group at 7 d after seizure (t = 5.353, P = 0.000, and was more obvious in CA1 region. There was no significant hippocampal neuronal damage in control group. The expressions of GRP78 and XBP-1 in CA3 region of hippocampus in SE group at 6 h after seizure were significantly higher than that in control group (P = 0.000, and then kept increasing until reaching the peak at 2 d (P = 0.000, for all. The expressions of GRP78 and XBP-1 in hippocampal CA3 region in preconditioning group were significantly higher than that in control group before seizure (P = 0.000, for all. The level of GRP78 maintained the highest at 24 h and 2 d after seizure (P = 0.000, for all, while the XBP-1 level
International Nuclear Information System (INIS)
Kimura, W.D.
1993-01-01
The final report describes work performed to investigate inverse Cherenkov acceleration (ICA) as a promising method for laser particle acceleration. In particular, an improved configuration of ICA is being tested in a experiment presently underway on the Accelerator Test Facility (ATF). In the experiment, the high peak power (∼ 10 GW) linearly polarized ATF CO 2 laser beam is converted to a radially polarized beam. This is beam is focused with an axicon at the Cherenkov angle onto the ATF 50-MeV e-beam inside a hydrogen gas cell, where the gas acts as the phase matching medium of the interaction. An energy gain of ∼12 MeV is predicted assuming a delivered laser peak power of 5 GW. The experiment is divided into two phases. The Phase I experiments, which were completed in the spring of 1992, were conducted before the ATF e-beam was available and involved several successful tests of the optical systems. Phase II experiments are with the e-beam and laser beam, and are still in progress. The ATF demonstrated delivery of the e-beam to the experiment in Dec. 1992. A preliminary ''debugging'' run with the e-beam and laser beam occurred in May 1993. This revealed the need for some experimental modifications, which have been implemented. The second run is tentatively scheduled for October or November 1993. In parallel to the experimental efforts has been ongoing theoretical work to support the experiment and investigate improvement and/or offshoots. One exciting offshoot has been theoretical work showing that free-space laser acceleration of electrons is possible using a radially-polarized, axicon-focused laser beam, but without any phase-matching gas. The Monte Carlo code used to model the ICA process has been upgraded and expanded to handle different types of laser beam input profiles
Tissier, Renaud; Souktani, Rachid; Parent de Curzon, Olivier; Lellouche, Nicolas; Henry, Patrick; Giudicelli, Jean-François; Berdeaux, Alain; Ghaleh, Bijan
2001-01-01
The goal of this study was to investigate the effects of the delayed pharmacological preconditioning produced by an adenosine A1-receptor agonist (A1-DPC) against ventricular arrhythmias induced by ischaemia and reperfusion, compared to those of ischaemia-induced delayed preconditioning (I-DPC).Eighty-nine instrumented conscious rabbits underwent a 2 consecutive days protocol. On day 1, rabbits were randomly divided into four groups: ‘Control' (saline, i.v.), ‘I-DPC' (six 4-min coronary arter...
HATAZAKI, S.; BELLVER-ESTELLES, C.; JIMENEZ-MATEOS, E. M.; MELLER, R.; BONNER, C.; MURPHY, N.; MATSUSHIMA, S.; TAKI, W.; PREHN, J. H. M.; SIMON, R. P.; HENSHALL, D. C.
2007-01-01
A neuroprotected state can be acquired by preconditioning brain with a stimulus that is subthreshold for damage (tolerance). Acquisition of tolerance involves coordinate, bi-directional changes to gene expression levels and the re-programmed phenotype is determined by the preconditioning stimulus. While best studied in ischemic brain there is evidence brief seizures can confer tolerance against prolonged seizures (status epilepticus). Presently, we developed a model of epileptic preconditioni...
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.; Zander, Elmar; Rosić, Bojana V.; Litvinenko, Alexander; Pajonk, Oliver
2016-01-01
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Introduction to the mathematics of inversion in remote sensing and indirect measurements
Twomey, S
2013-01-01
Developments in Geomathematics, 3: Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements focuses on the application of the mathematics of inversion in remote sensing and indirect measurements, including vectors and matrices, eigenvalues and eigenvectors, and integral equations. The publication first examines simple problems involving inversion, theory of large linear systems, and physical and geometric aspects of vectors and matrices. Discussions focus on geometrical view of matrix operations, eigenvalues and eigenvectors, matrix products, inverse of a matrix, transposition and rules for product inversion, and algebraic elimination. The manuscript then tackles the algebraic and geometric aspects of functions and function space and linear inversion methods, as well as the algebraic and geometric nature of constrained linear inversion, least squares solution, approximation by sums of functions, and integral equations. The text examines information content of indirect sensing m...
Support Minimized Inversion of Acoustic and Elastic Wave Scattering
Safaeinili, Ali
Inversion of limited data is common in many areas of NDE such as X-ray Computed Tomography (CT), Ultrasonic and eddy current flaw characterization and imaging. In many applications, it is common to have a bias toward a solution with minimum (L^2)^2 norm without any physical justification. When it is a priori known that objects are compact as, say, with cracks and voids, by choosing "Minimum Support" functional instead of the minimum (L^2)^2 norm, an image can be obtained that is equally in agreement with the available data, while it is more consistent with what is most probably seen in the real world. We have utilized a minimum support functional to find a solution with the smallest volume. This inversion algorithm is most successful in reconstructing objects that are compact like voids and cracks. To verify this idea, we first performed a variational nonlinear inversion of acoustic backscatter data using minimum support objective function. A full nonlinear forward model was used to accurately study the effectiveness of the minimized support inversion without error due to the linear (Born) approximation. After successful inversions using a full nonlinear forward model, a linearized acoustic inversion was developed to increase speed and efficiency in imaging process. The results indicate that by using minimum support functional, we can accurately size and characterize voids and/or cracks which otherwise might be uncharacterizable. An extremely important feature of support minimized inversion is its ability to compensate for unknown absolute phase (zero-of-time). Zero-of-time ambiguity is a serious problem in the inversion of the pulse-echo data. The minimum support inversion was successfully used for the inversion of acoustic backscatter data due to compact scatterers without the knowledge of the zero-of-time. The main drawback to this type of inversion is its computer intensiveness. In order to make this type of constrained inversion available for common use, work
Preconditions of commercial use in tourism of individual´s death
TŮMOVÁ, Blanka
2008-01-01
This bachelor thesis deals with the processing the theme Dark Tourism introducing an unusual and so far not very well-known type of tourism in the Czech Republic. The concept Dark Tourism (also known as Thanatourism) refers to visiting sites which offer a presentation of death or suffering and it is identified with visitations to places where tragedies or historically noteworthy death has occurred and that continue to impact our lives. This thesis researches preconditions of commercial use in...
Nehra, Sarita; Bhardwaj, Varun; Bansal, Anju; Saraswat, Deepika
2017-09-26
Chronic hypobaric hypoxia (cHH) mediated cardiac insufficiencies are associated with pathological damage. Sustained redox stress and work load are major causative agents of cardiac insufficiencies under cHH. Despite the advancements made in pharmacological (anti-oxidants, vasodilators) and non-pharmacological therapeutics (acclimatization strategies and schedules), only partial success has been achieved in improving cardiac acclimatization to cHH. This necessitates the need for potent combinatorial therapies to improve cardiac acclimatization at high altitudes. We hypothesize that a combinatorial therapy comprising preconditioning to mild aerobic treadmill exercise and supplementation with nanocurcumin formulation (NCF) consisting of nanocurcumin (NC) and pyrroloquinoline quinone (PQQ) might improve cardiac adaptation at high altitudes. Adult Sprague-Dawley rats pre-conditioned to treadmill exercise and supplemented with NCF were exposed to cHH (7620 m altitude corresponding to pO2~8% at 28±2°C, relative humidity 55%±1%) for 3 weeks. The rat hearts were analyzed for changes in markers of oxidative stress (free radical leakage, lipid peroxidation, manganese-superoxide dismutase [MnSOD] activity), cardiac injury (circulating cardiac troponin I [TnI] and T [cTnT], myocardial creatine kinase [CK-MB]), metabolic damage (lactate dehydrogenase [LDH] and acetyl-coenzyme A levels, lactate and pyruvate levels) and bio-energetic insufficiency (ATP, p-AMPKα). Significant modulations (p≤0.05) in cardiac redox status, metabolic damage, cardiac injury and bio-energetics were observed in rats receiving both NCF supplementation and treadmill exercise-preconditioning compared with rats receiving only one of the treatments. The combinatorial therapeutic strategy showed a tremendous improvement in cardiac acclimatization to cHH compared to either exercise-preconditioning or NCF supplementation alone which was evident from the effective modulation in redox, metabolic, contractile
International Nuclear Information System (INIS)
Chen, G.S.; Yang, D.Y.
1998-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used: TFQMR (transpose free quasi-minimal residual algorithm) CGS (conjugate gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These subroutines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. The reasons to choose the generalized conjugate gradient methods are that the methods have better residual (equivalent to error) control procedures in the computation and have better convergent rate. The pointwise incomplete LU factorization ILU, modified pointwise incomplete LU factorization MILU, block incomplete factorization BILU and modified blockwise incomplete LU factorization MBILU are the preconditioning techniques used in the several testing problems. In Bi-CGSTAB, CGS, TFQMR and QMRCGSTAB method, we find that either CGS or Bi-CGSTAB method combined with preconditioner MBILU is the most efficient algorithm in these methods in the several testing problems. The numerical solution of flux by preconditioned CGS and Bi-CGSTAB methods has the same result as those from Cray computer, obtained by either the point successive relaxation method or the line successive relaxation method combined with Gaussian elimination
2014-01-07
this can have a disastrous effect on convergence rate. Even if steady state is obtained for low Mach number flows (after many iterations ), the results...rally lead do a diagonally dominant left-hand-side matrix, which causes stability problems for implicit Gauss - Seidel schemes. For this reason, matrix... convergence at the stagnation point. The iterations for each airfoil is also reported in Fig. 2. Without preconditioning, dramatic efficiency problems are seen
Czech Academy of Sciences Publication Activity Database
Vejchodský, Tomáš; Šolín, Pavel
2008-01-01
Roč. 218, č. 1 (2008), s. 192-200 ISSN 0377-0427 R&D Projects: GA AV ČR IAA100760702; GA ČR GA102/05/0629; GA ČR(CZ) GA102/07/0496 Institutional research plan: CEZ:AV0Z10190503; CEZ:AV0Z20570509 Keywords : static condensation of internal degrees of freedom * orthogonalization * ILU preconditioning Subject RIV: BA - General Mathematics Impact factor: 1.048, year: 2008
Directory of Open Access Journals (Sweden)
A K Voronkov
2012-06-01
Full Text Available The article focuses on analyses of preconditions for development of international relations between UAE and African countries including geographical location of the UAE, naval and ship building skills of the Persian gulf Arabs, participation of both Eastern Africa and Persian Gulf in the Indian ocean trade as well as influence on its development of external factors such as Islamic expansion and colonial policies of Britain and Portugal.
Kostyuchenko V.; Malinovskaya A.; Mamonova A.
2018-01-01
Introduction. The worldwide expansion of digital technologies and the development of the cyber economy led to emergence of a new digital assets – the cryptographic currency that rapidly growing popularity. The phenomenon of cryptocurrency is relatively new and little investigated. Purpose. The purpose of the article is to substantiate the preconditions for the introduction of accounting and taxation of transactions with cryptic currencies in Ukraine. Results. The article considers the...
Xue, Yuquan; Xu, Zhibin; Chen, Haiwen; Gan, Weimin; Chong, Tie
2017-07-01
To evaluate whether low energy shock wave preconditioning could reduce renal ischemic reperfusion injury caused by renal artery occlusion. The right kidneys of 64 male Sprague Dawley rats were removed to establish an isolated kidney model. The rats were then divided into four treatment groups: Group 1 was the sham treatment group; Group 2, received only low-energy (12 kv, 1 Hz, 200 times) shock wave preconditioning; Group 3 received the same low-energy shock wave preconditioning as Group 2, and then the left renal artery was occluded for 45 minutes; and Group 4 had the left renal artery occluded for 45 minutes. At 24 hours and one-week time points after reperfusion, serum inducible nitric oxide synthase (iNOS), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), creatinine (Cr), and cystatin C (Cys C) levels were measured, malondialdehyde (MDA) in kidney tissue was detected, and changes in nephric morphology were evaluated by light and electron microscopy. Twenty-four hours after reperfusion, serum iNOS, NGAL, Cr, Cys C, and MDA levels in Group 3 were significantly lower than those in Group 4; light and electron microscopy showed that the renal tissue injury in Group 3 was significantly lighter than that in Group 4. One week after reperfusion, serum NGAL, KIM-1, and Cys C levels in Group 3 were significantly lower than those in Group 4. Low-energy shock wave preconditioning can reduce renal ischemic reperfusion injury caused by renal artery occlusion in an isolated kidney rat model.
Hladkykh Dmytro M.
2017-01-01
The article is aimed at studying the preconditions for introduction, the main problems and prospects for implementation of the inflation targeting regime in Ukraine. In 2014, the country got into a crisis that affected at once the currency market, the banking system and the real sector, resulting in devaluations, bank failures, decreasing GDP, growing prices. One of the responses to the financial challenges was the transition to inflationary targeting, which led to a slowdown in inflation in ...
Zhu, Xiaoling; Yin, Jinbo; Li, Liaoliao; Ma, Lei; Tan, Hongying; Deng, Jiao; Chen, Shaoyang; Zuo, Zhiyi
2013-01-01
Electroacupuncture has been shown to induce a preconditioning effect in the brain. The mechanisms for this protection are not fully elucidated. We hypothesize that this protection is mediated by excitatory amino acid transporters (EAATs) that have been shown to be neuroprotective. To test this hypothesis, two-month old male Sprague-Dawley rats and EAAT type 3 (EAAT3) knockout mice received or did not receive 30-min electroacupuncture once a day for 5 consecutive days. They were subjected to a...
Directory of Open Access Journals (Sweden)
Kraemer Robert
2011-11-01
Full Text Available Abstract Background Therapeutic strategies aiming to reduce ischemia/reperfusion injury by conditioning tissue tolerance against ischemia appear attractive not only from a scientific perspective, but also in clinics. Although previous studies indicate that remote ischemic intermittent preconditioning (RIPC is a systemic phenomenon, only a few studies have focused on the elucidation of its mechanisms of action especially in the clinical setting. Therefore, the aim of this study is to evaluate the acute microcirculatory effects of remote ischemic preconditioning on a distinct cutaneous location at the lower extremity which is typically used as a harvesting site for free flap reconstructive surgery in a human in-vivo setting. Methods Microcirculatory data of 27 healthy subjects (25 males, age 24 ± 4 years, BMI 23.3 were evaluated continuously at the anterolateral aspect of the left thigh during RIPC using combined Laser-Doppler and photospectrometry (Oxygen-to-see, Lea Medizintechnik, Germany. After baseline microcirculatory measurement, remote ischemia was induced using a tourniquet on the contralateral upper arm for three cycles of 5 min. Results After RIPC, tissue oxygen saturation and capillary blood flow increased up to 29% and 35% during the third reperfusion phase versus baseline measurement, respectively (both p = 0.001. Postcapillary venous filling pressure decreased statistically significant by 16% during second reperfusion phase (p = 0.028. Conclusion Remote intermittent ischemic preconditioning affects cutaneous tissue oxygen saturation, arterial capillary blood flow and postcapillary venous filling pressure at a remote cutaneous location of the lower extremity. To what extent remote preconditioning might ameliorate reperfusion injury in soft tissue trauma or free flap transplantation further clinical trials have to evaluate. Trial registration ClinicalTrials.gov: NCT01235286
The precondition of social mobility in Ignalina NPP and its area
International Nuclear Information System (INIS)
Mikshys, A.
1998-01-01
In the paper some preconditions of social mobility in the northern Lithuania (Ignalina nuclear power plant) and in its area are analyzed. The results of the sociological research reveal the desire of some part of the inhabitants of the nuclear power plant area to change their social status and the place of residence. The difficult social and demographically situation in this region as significant is noted. The author proposes some mean for the normalization of this situation. (author)
Preconditioning of two-by-two block matrix systems with square matrix blocks, with applications
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe
2017-01-01
Roč. 62, č. 6 (2017), s. 537-559 ISSN 0862-7940. [SNA´17 - Seminar on numerical analysis. Ostrava, 30.01.2017-03.02.2017] Institutional support: RVO:68145535 Keywords : preconditioning * Schur complement * transformation * optimal control * implicit time integration Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 0.618, year: 2016 http://articles.math.cas.cz/10.21136/AM.2017.0222-17/?type=F
Linear GPR inversion for lossy soil and a planar air-soil interface
DEFF Research Database (Denmark)
Meincke, Peter
2001-01-01
A three-dimensional inversion scheme for fixed-offset ground penetrating radar (GPR) is derived that takes into account the loss in the soil and the planar air-soil interface. The forward model of this inversion scheme is based upon the first Born approximation and the dyadic Green function...
Potentials of the inverse scattering problem in the three-nucleon problem
International Nuclear Information System (INIS)
Pushkash, A.M.; Simenog, I.V.; Shapoval, D.V.
1993-01-01
Possibilities of using the method of the inverse scattering problem for describing simultaneously the two-nucleon and the low-energy three-nucleon data in the S-interaction approximation are examined. 20 refs., 3 figs., 1 tab
On the joint inversion of SGG and SST data from the GOCE mission
Directory of Open Access Journals (Sweden)
P. Ditmar
2003-01-01
Full Text Available The computation of spherical harmonic coefficients of the Earth’s gravity field from satellite-to-satellite tracking (SST data and satellite gravity gradiometry (SGG data is considered. As long as the functional model related to SST data contains nuisance parameters (e.g. unknown initial state vectors, assembling of the corresponding normal matrix must be supplied with the back-substitution operation, so that the nuisance parameters are excluded from consideration. The traditional back-substitution algorithm, however, may result in large round-off errors. Hence an alternative approach, back-substitution at the level of the design matrix, is implemented. Both a stand-alone inversion of either type of data and a joint inversion of both types are considered. The conclusion drawn is that the joint inversion results in a much better model of the Earth’s gravity field than a standalone inversion. Furthermore, two numerical techniques for solving the joint system of normal equations are compared: (i the Cholesky method based on an explicit computation of the normal matrix, and (ii the pre-conditioned conjugate gradient method (PCCG, for which an explicit computation of the entire normal matrix is not needed. The comparison shows that the PCCG method is much faster than the Cholesky method.Key words. Earth’s gravity field, GOCE, satellite-tosatellite tracking, satellite gravity gradiometry, backsubstitution
He, Zhijie; Lu, Hongyang; Yang, Xiaojiao; Zhang, Li; Wu, Yi; Niu, Wenxiu; Ding, Li; Wang, Guili; Tong, Shanbao; Jia, Jie
2018-01-01
Exercise preconditioning induces neuroprotective effects during cerebral ischemia and reperfusion, which involves the recovery of cerebral blood flow (CBF). Mechanisms underlying the neuroprotective effects of re-established CBF following ischemia and reperfusion are unclear. The present study investigated CBF in hyper-early stage of reperfusion by laser speckle contrast imaging, a full-field high-resolution optical imaging technique. Rats with or without treadmill training were subjected to middle cerebral artery occlusion followed by reperfusion. CBF in arteries, veins, and capillaries in hyper-early stage of reperfusion (1, 2, and 3 h after reperfusion) and in subacute stage (24 h after reperfusion) were measured. Neurological scoring and 2,3,5-triphenyltetrazolium chloride staining were further applied to determine the neuroprotective effects of exercise preconditioning. In hyper-early stage of reperfusion, CBF in the rats with exercise preconditioning was reduced significantly in arteries and veins, respectively, compared to rats with no exercise preconditioning. Capillary CBF remained stable in the hyper-early stage of reperfusion, though it increased significantly 24 h after reperfusion in the rats with exercise preconditioning. As a neuroprotective strategy, exercise preconditioning reduced the blood perfusion of arteries and veins in the hyper-early stage of reperfusion, which indicated intervention-induced neuroprotective hypoperfusion after reperfusion onset.