Acceleration of GPU-based Krylov solvers via data transfer reduction

DOE PAGES

Anzt, Hartwig; Tomov, Stanimire; Luszczek, Piotr; ...

2015-04-08

Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well optimized but limited set of linear algebra operations, applications that use them often fail to reduce certain data communications, and hence fail to leverage the full potential of the accelerator. In this study, we target the acceleration of Krylov subspace iterative methods for graphicsmore » processing units, and in particular the Biconjugate Gradient Stabilized solver that significant improvement can be achieved by reformulating the method to reduce data-communications through application-specific kernels instead of using the generic BLAS kernels, e.g. as provided by NVIDIA’s cuBLAS library, and by designing a graphics processing unit specific sparse matrix-vector product kernel that is able to more efficiently use the graphics processing unit’s computing power. Furthermore, we derive a model estimating the performance improvement, and use experimental data to validate the expected runtime savings. Finally, considering that the derived implementation achieves significantly higher performance, we assert that similar optimizations addressing algorithm structure, as well as sparse matrix-vector, are crucial for the subsequent development of high-performance graphics processing units accelerated Krylov subspace iterative methods.« less

Accelerating molecular property calculations with nonorthonormal Krylov space methods

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

Furche, Filipp; Krull, Brandon T.; Nguyen, Brian D.

Here, we formulate Krylov space methods for large eigenvalue problems and linear equation systems that take advantage of decreasing residual norms to reduce the cost of matrix-vector multiplication. The residuals are used as subspace basis without prior orthonormalization, which leads to generalized eigenvalue problems or linear equation systems on the Krylov space. These nonorthonormal Krylov space (nKs) algorithms are favorable for large matrices with irregular sparsity patterns whose elements are computed on the fly, because fewer operations are necessary as the residual norm decreases as compared to the conventional method, while errors in the desired eigenpairs and solution vectors remainmore » small. We consider real symmetric and symplectic eigenvalue problems as well as linear equation systems and Sylvester equations as they appear in configuration interaction and response theory. The nKs method can be implemented in existing electronic structure codes with minor modifications and yields speed-ups of 1.2-1.8 in typical time-dependent Hartree-Fock and density functional applications without accuracy loss. The algorithm can compute entire linear subspaces simultaneously which benefits electronic spectra and force constant calculations requiring many eigenpairs or solution vectors. The nKs approach is related to difference density methods in electronic ground state calculations, and particularly efficient for integral direct computations of exchange-type contractions. By combination with resolution-of-the-identity methods for Coulomb contractions, three- to fivefold speed-ups of hybrid time-dependent density functional excited state and response calculations are achieved.« less

Accelerating molecular property calculations with nonorthonormal Krylov space methods

DOE PAGES

Furche, Filipp; Krull, Brandon T.; Nguyen, Brian D.; ...

2016-05-03

Here, we formulate Krylov space methods for large eigenvalue problems and linear equation systems that take advantage of decreasing residual norms to reduce the cost of matrix-vector multiplication. The residuals are used as subspace basis without prior orthonormalization, which leads to generalized eigenvalue problems or linear equation systems on the Krylov space. These nonorthonormal Krylov space (nKs) algorithms are favorable for large matrices with irregular sparsity patterns whose elements are computed on the fly, because fewer operations are necessary as the residual norm decreases as compared to the conventional method, while errors in the desired eigenpairs and solution vectors remainmore » small. We consider real symmetric and symplectic eigenvalue problems as well as linear equation systems and Sylvester equations as they appear in configuration interaction and response theory. The nKs method can be implemented in existing electronic structure codes with minor modifications and yields speed-ups of 1.2-1.8 in typical time-dependent Hartree-Fock and density functional applications without accuracy loss. The algorithm can compute entire linear subspaces simultaneously which benefits electronic spectra and force constant calculations requiring many eigenpairs or solution vectors. The nKs approach is related to difference density methods in electronic ground state calculations, and particularly efficient for integral direct computations of exchange-type contractions. By combination with resolution-of-the-identity methods for Coulomb contractions, three- to fivefold speed-ups of hybrid time-dependent density functional excited state and response calculations are achieved.« less

Preconditioned conjugate gradient methods for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

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.

Projection methods for line radiative transfer in spherical media.

NASA Astrophysics Data System (ADS)

Anusha, L. S.; Nagendra, K. N.

An efficient numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is presented for the solution of radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These methods are based on projections on the subspaces of the n dimensional Euclidean space mathbb {R}n called Krylov subspaces. The methods are shown to be faster in terms of convergence rate compared to the contemporary iterative methods such as Jacobi, Gauss-Seidel and Successive Over Relaxation (SOR).

Krylov Deferred Correction Accelerated Method of Lines Transpose for Parabolic Problems

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

Jia, Jun; Jingfang, Huang

2008-01-01

In this paper, a new class of numerical methods for the accurate and efficient solutions of parabolic partial differential equations is presented. Unlike traditional method of lines (MoL), the new {\\bf \\it Krylov deferred correction (KDC) accelerated method of lines transpose (MoL^T)} first discretizes the temporal direction using Gaussian type nodes and spectral integration, and symbolically applies low-order time marching schemes to form a preconditioned elliptic system, which is then solved iteratively using Newton-Krylov techniques such as Newton-GMRES or Newton-BiCGStab method. Each function evaluation in the Newton-Krylov method is simply one low-order time-stepping approximation of the error by solving amore » decoupled system using available fast elliptic equation solvers. Preliminary numerical experiments show that the KDC accelerated MoL^T technique is unconditionally stable, can be spectrally accurate in both temporal and spatial directions, and allows optimal time-step sizes in long-time simulations.« less

Implementation of the block-Krylov boundary flexibility method of component synthesis

NASA Technical Reports Server (NTRS)

Carney, Kelly S.; Abdallah, Ayman A.; Hucklebridge, Arthur A.

1993-01-01

A method of dynamic substructuring is presented which utilizes a set of static Ritz vectors as a replacement for normal eigenvectors in component mode synthesis. This set of Ritz vectors is generated in a recurrence relationship, which has the form of a block-Krylov subspace. The initial seed to the recurrence algorithm is based on the boundary flexibility vectors of the component. This algorithm is not load-dependent, is applicable to both fixed and free-interface boundary components, and results in a general component model appropriate for any type of dynamic analysis. This methodology was implemented in the MSC/NASTRAN normal modes solution sequence using DMAP. The accuracy is found to be comparable to that of component synthesis based upon normal modes. The block-Krylov recurrence algorithm is a series of static solutions and so requires significantly less computation than solving the normal eigenspace problem.

Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations

NASA Technical Reports Server (NTRS)

Elman, Howard C.

1996-01-01

Discretization of the Stokes equations produces a symmetric indefinite system of linear equations. For stable discretizations, a variety of numerical methods have been proposed that have rates of convergence independent of the mesh size used in the discretization. In this paper, we compare the performance of four such methods: variants of the Uzawa, preconditioned conjugate gradient, preconditioned conjugate residual, and multigrid methods, for solving several two-dimensional model problems. The results indicate that where it is applicable, multigrid with smoothing based on incomplete factorization is more efficient than the other methods, but typically by no more than a factor of two. The conjugate residual method has the advantage of being both independent of iteration parameters and widely applicable.

Improvements in Block-Krylov Ritz Vectors and the Boundary Flexibility Method of Component Synthesis

NASA Technical Reports Server (NTRS)

Carney, Kelly Scott

1997-01-01

A method of dynamic substructuring is presented which utilizes a set of static Ritz vectors as a replacement for normal eigenvectors in component mode synthesis. This set of Ritz vectors is generated in a recurrence relationship, proposed by Wilson, which has the form of a block-Krylov subspace. The initial seed to the recurrence algorithm is based upon the boundary flexibility vectors of the component. Improvements have been made in the formulation of the initial seed to the Krylov sequence, through the use of block-filtering. A method to shift the Krylov sequence to create Ritz vectors that will represent the dynamic behavior of the component at target frequencies, the target frequency being determined by the applied forcing functions, has been developed. A method to terminate the Krylov sequence has also been developed. Various orthonormalization schemes have been developed and evaluated, including the Cholesky/QR method. Several auxiliary theorems and proofs which illustrate issues in component mode synthesis and loss of orthogonality in the Krylov sequence have also been presented. The resulting methodology is applicable to both fixed and free- interface boundary components, and results in a general component model appropriate for any type of dynamic analysis. The accuracy is found to be comparable to that of component synthesis based upon normal modes, using fewer generalized coordinates. In addition, the block-Krylov recurrence algorithm is a series of static solutions and so requires significantly less computation than solving the normal eigenspace problem. The requirement for less vectors to form the component, coupled with the lower computational expense of calculating these Ritz vectors, combine to create a method more efficient than traditional component mode synthesis.

Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions

DTIC Science & Technology

2012-03-22

with performance profiles, Math. Program., 91 (2002), pp. 201–213. [6] P. DRINEAS, R. KANNAN, AND M. W. MAHONEY , Fast Monte Carlo algorithms for matrices...computing invariant subspaces of non-Hermitian matri- ces, Numer. Math., 25 ( 1975 /76), pp. 123–136. [25] , Matrix algorithms Vol. II: Eigensystems

Application of linear multifrequency-grey acceleration to preconditioned Krylov iterations for thermal radiation transport

DOE PAGES

Till, Andrew T.; Warsa, James S.; Morel, Jim E.

2018-06-15

The thermal radiative transfer (TRT) equations comprise a radiation equation coupled to the material internal energy equation. Linearization of these equations produces effective, thermally-redistributed scattering through absorption-reemission. In this paper, we investigate the effectiveness and efficiency of Linear-Multi-Frequency-Grey (LMFG) acceleration that has been reformulated for use as a preconditioner to Krylov iterative solution methods. We introduce two general frameworks, the scalar flux formulation (SFF) and the absorption rate formulation (ARF), and investigate their iterative properties in the absence and presence of true scattering. SFF has a group-dependent state size but may be formulated without inner iterations in the presence ofmore » scattering, while ARF has a group-independent state size but requires inner iterations when scattering is present. We compare and evaluate the computational cost and efficiency of LMFG applied to these two formulations using a direct solver for the preconditioners. Finally, this work is novel because the use of LMFG for the radiation transport equation, in conjunction with Krylov methods, involves special considerations not required for radiation diffusion.« less

Numerical simulations of microwave heating of liquids: enhancements using Krylov subspace methods

NASA Astrophysics Data System (ADS)

Lollchund, M. R.; Dookhitram, K.; Sunhaloo, M. S.; Boojhawon, R.

2013-04-01

In this paper, we compare the performances of three iterative solvers for large sparse linear systems arising in the numerical computations of incompressible Navier-Stokes (NS) equations. These equations are employed mainly in the simulation of microwave heating of liquids. The emphasis of this work is on the application of Krylov projection techniques such as Generalized Minimal Residual (GMRES) to solve the Pressure Poisson Equations that result from discretisation of the NS equations. The performance of the GMRES method is compared with the traditional Gauss-Seidel (GS) and point successive over relaxation (PSOR) techniques through their application to simulate the dynamics of water housed inside a vertical cylindrical vessel which is subjected to microwave radiation. It is found that as the mesh size increases, GMRES gives the fastest convergence rate in terms of computational times and number of iterations.

Algebraic multigrid preconditioning within parallel finite-element solvers for 3-D electromagnetic modelling problems in geophysics

NASA Astrophysics Data System (ADS)

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

Parallel iterative methods for sparse linear and nonlinear equations

NASA Technical Reports Server (NTRS)

Saad, Youcef

1989-01-01

As three-dimensional models are gaining importance, iterative methods will become almost mandatory. Among these, preconditioned Krylov subspace methods have been viewed as the most efficient and reliable, when solving linear as well as nonlinear systems of equations. There has been several different approaches taken to adapt iterative methods for supercomputers. Some of these approaches are discussed and the methods that deal more specifically with general unstructured sparse matrices, such as those arising from finite element methods, are emphasized.

Recovery Discontinuous Galerkin Jacobian-Free Newton-Krylov Method for All-Speed Flows

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

HyeongKae Park; Robert Nourgaliev; Vincent Mousseau

2008-07-01

A novel numerical algorithm (rDG-JFNK) for all-speed fluid flows with heat conduction and viscosity is introduced. The rDG-JFNK combines the Discontinuous Galerkin spatial discretization with the implicit Runge-Kutta time integration under the Jacobian-free Newton-Krylov framework. We solve fully-compressible Navier-Stokes equations without operator-splitting of hyperbolic, diffusion and reaction terms, which enables fully-coupled high-order temporal discretization. The stability constraint is removed due to the L-stable Explicit, Singly Diagonal Implicit Runge-Kutta (ESDIRK) scheme. The governing equations are solved in the conservative form, which allows one to accurately compute shock dynamics, as well as low-speed flows. For spatial discretization, we develop a “recovery” familymore » of DG, exhibiting nearly-spectral accuracy. To precondition the Krylov-based linear solver (GMRES), we developed an “Operator-Split”-(OS) Physics Based Preconditioner (PBP), in which we transform/simplify the fully-coupled system to a sequence of segregated scalar problems, each can be solved efficiently with Multigrid method. Each scalar problem is designed to target/cluster eigenvalues of the Jacobian matrix associated with a specific physics.« less

Low-Rank Correction Methods for Algebraic Domain Decomposition Preconditioners

DOE PAGES

Li, Ruipeng; Saad, Yousef

2017-08-01

This study presents a parallel preconditioning method for distributed sparse linear systems, based on an approximate inverse of the original matrix, that adopts a general framework of distributed sparse matrices and exploits domain decomposition (DD) and low-rank corrections. The DD approach decouples the matrix and, once inverted, a low-rank approximation is applied by exploiting the Sherman--Morrison--Woodbury formula, which yields two variants of the preconditioning methods. The low-rank expansion is computed by the Lanczos procedure with reorthogonalizations. Numerical experiments indicate that, when combined with Krylov subspace accelerators, this preconditioner can be efficient and robust for solving symmetric sparse linear systems. Comparisonsmore » with pARMS, a DD-based parallel incomplete LU (ILU) preconditioning method, are presented for solving Poisson's equation and linear elasticity problems.« less

Low-Rank Correction Methods for Algebraic Domain Decomposition Preconditioners

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

Li, Ruipeng; Saad, Yousef

This study presents a parallel preconditioning method for distributed sparse linear systems, based on an approximate inverse of the original matrix, that adopts a general framework of distributed sparse matrices and exploits domain decomposition (DD) and low-rank corrections. The DD approach decouples the matrix and, once inverted, a low-rank approximation is applied by exploiting the Sherman--Morrison--Woodbury formula, which yields two variants of the preconditioning methods. The low-rank expansion is computed by the Lanczos procedure with reorthogonalizations. Numerical experiments indicate that, when combined with Krylov subspace accelerators, this preconditioner can be efficient and robust for solving symmetric sparse linear systems. Comparisonsmore » with pARMS, a DD-based parallel incomplete LU (ILU) preconditioning method, are presented for solving Poisson's equation and linear elasticity problems.« less

Efficient solution of parabolic equations by Krylov approximation methods

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Y.

1990-01-01

Numerical techniques for solving parabolic equations by the method of lines is addressed. The main motivation for the proposed approach is the possibility of exploiting a high degree of parallelism in a simple manner. The basic idea of the method is to approximate the action of the evolution operator on a given state vector by means of a projection process onto a Krylov subspace. Thus, the resulting approximation consists of applying an evolution operator of a very small dimension to a known vector which is, in turn, computed accurately by exploiting well-known rational approximations to the exponential. Because the rational approximation is only applied to a small matrix, the only operations required with the original large matrix are matrix-by-vector multiplications, and as a result the algorithm can easily be parallelized and vectorized. Some relevant approximation and stability issues are discussed. We present some numerical experiments with the method and compare its performance with a few explicit and implicit algorithms.

On linearization and preconditioning for radiation diffusion coupled to material thermal conduction equations

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

Feng, Tao, E-mail: fengtao2@mail.ustc.edu.cn; Graduate School of China Academy Engineering Physics, Beijing 100083; An, Hengbin, E-mail: an_hengbin@iapcm.ac.cn

2013-03-01

Jacobian-free Newton–Krylov (JFNK) method is an effective algorithm for solving large scale nonlinear equations. One of the most important advantages of JFNK method is that there is no necessity to form and store the Jacobian matrix of the nonlinear system when JFNK method is employed. However, an approximation of the Jacobian is needed for the purpose of preconditioning. In this paper, JFNK method is employed to solve a class of non-equilibrium radiation diffusion coupled to material thermal conduction equations, and two preconditioners are designed by linearizing the equations in two methods. Numerical results show that the two preconditioning methods canmore » improve the convergence behavior and efficiency of JFNK method.« less

Newton-Krylov-Schwarz: An implicit solver for CFD

NASA Technical Reports Server (NTRS)

Cai, Xiao-Chuan; Keyes, David E.; Venkatakrishnan, V.

1995-01-01

Newton-Krylov methods and Krylov-Schwarz (domain decomposition) methods have begun to become established in computational fluid dynamics (CFD) over the past decade. The former employ a Krylov method inside of Newton's method in a Jacobian-free manner, through directional differencing. The latter employ an overlapping Schwarz domain decomposition to derive a preconditioner for the Krylov accelerator that relies primarily on local information, for data-parallel concurrency. They may be composed as Newton-Krylov-Schwarz (NKS) methods, which seem particularly well suited for solving nonlinear elliptic systems in high-latency, distributed-memory environments. We give a brief description of this family of algorithms, with an emphasis on domain decomposition iterative aspects. We then describe numerical simulations with Newton-Krylov-Schwarz methods on aerodynamics applications emphasizing comparisons with a standard defect-correction approach, subdomain preconditioner consistency, subdomain preconditioner quality, and the effect of a coarse grid.

An iterative solver for the 3D Helmholtz equation

NASA Astrophysics Data System (ADS)

Belonosov, Mikhail; Dmitriev, Maxim; Kostin, Victor; Neklyudov, Dmitry; Tcheverda, Vladimir

2017-09-01

We develop a frequency-domain iterative solver for numerical simulation of acoustic waves in 3D heterogeneous media. It is based on the application of a unique preconditioner to the Helmholtz equation that ensures convergence for Krylov subspace iteration methods. Effective inversion of the preconditioner involves the Fast Fourier Transform (FFT) and numerical solution of a series of boundary value problems for ordinary differential equations. Matrix-by-vector multiplication for iterative inversion of the preconditioned matrix involves inversion of the preconditioner and pointwise multiplication of grid functions. Our solver has been verified by benchmarking against exact solutions and a time-domain solver.

Greedy subspace clustering.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses the sets ...

Angular Multigrid Preconditioner for Krylov-Based Solution Techniques Applied to the Sn Equations with Highly Forward-Peaked Scattering

NASA Astrophysics Data System (ADS)

Turcksin, Bruno; Ragusa, Jean C.; Morel, Jim E.

2012-01-01

It is well known that the diffusion synthetic acceleration (DSA) methods for the Sn equations become ineffective in the Fokker-Planck forward-peaked scattering limit. In response to this deficiency, Morel and Manteuffel (1991) developed an angular multigrid method for the 1-D Sn equations. This method is very effective, costing roughly twice as much as DSA per source iteration, and yielding a maximum spectral radius of approximately 0.6 in the Fokker-Planck limit. Pautz, Adams, and Morel (PAM) (1999) later generalized the angular multigrid to 2-D, but it was found that the method was unstable with sufficiently forward-peaked mappings between the angular grids. The method was stabilized via a filtering technique based on diffusion operators, but this filtering also degraded the effectiveness of the overall scheme. The spectral radius was not bounded away from unity in the Fokker-Planck limit, although the method remained more effective than DSA. The purpose of this article is to recast the multidimensional PAM angular multigrid method without the filtering as an Sn preconditioner and use it in conjunction with the Generalized Minimal RESidual (GMRES) Krylov method. The approach ensures stability and our computational results demonstrate that it is also significantly more efficient than an analogous DSA-preconditioned Krylov method.

PRIFIRA: General regularization using prior-conditioning for fast radio interferometric imaging†

NASA Astrophysics Data System (ADS)

Naghibzadeh, Shahrzad; van der Veen, Alle-Jan

2018-06-01

Image formation in radio astronomy is a large-scale inverse problem that is inherently ill-posed. We present a general algorithmic framework based on a Bayesian-inspired regularized maximum likelihood formulation of the radio astronomical imaging problem with a focus on diffuse emission recovery from limited noisy correlation data. The algorithm is dubbed PRIor-conditioned Fast Iterative Radio Astronomy (PRIFIRA) and is based on a direct embodiment of the regularization operator into the system by right preconditioning. The resulting system is then solved using an iterative method based on projections onto Krylov subspaces. We motivate the use of a beamformed image (which includes the classical "dirty image") as an efficient prior-conditioner. Iterative reweighting schemes generalize the algorithmic framework and can account for different regularization operators that encourage sparsity of the solution. The performance of the proposed method is evaluated based on simulated one- and two-dimensional array arrangements as well as actual data from the core stations of the Low Frequency Array radio telescope antenna configuration, and compared to state-of-the-art imaging techniques. We show the generality of the proposed method in terms of regularization schemes while maintaining a competitive reconstruction quality with the current reconstruction techniques. Furthermore, we show that exploiting Krylov subspace methods together with the proper noise-based stopping criteria results in a great improvement in imaging efficiency.

Numerical implementation, verification and validation of two-phase flow four-equation drift flux model with Jacobian-free Newton–Krylov method

DOE PAGES

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2016-08-24

This study presents a numerical investigation on using the Jacobian-free Newton–Krylov (JFNK) method to solve the two-phase flow four-equation drift flux model with realistic constitutive correlations (‘closure models’). The drift flux model is based on Isshi and his collaborators’ work. Additional constitutive correlations for vertical channel flow, such as two-phase flow pressure drop, flow regime map, wall boiling and interfacial heat transfer models, were taken from the RELAP5-3D Code Manual and included to complete the model. The staggered grid finite volume method and fully implicit backward Euler method was used for the spatial discretization and time integration schemes, respectively. Themore » Jacobian-free Newton–Krylov method shows no difficulty in solving the two-phase flow drift flux model with a discrete flow regime map. In addition to the Jacobian-free approach, the preconditioning matrix is obtained by using the default finite differencing method provided in the PETSc package, and consequently the labor-intensive implementation of complex analytical Jacobian matrix is avoided. Extensive and successful numerical verification and validation have been performed to prove the correct implementation of the models and methods. Code-to-code comparison with RELAP5-3D has further demonstrated the successful implementation of the drift flux model.« less

Application of a fast Newton-Krylov solver for equilibrium simulations of phosphorus and oxygen

NASA Astrophysics Data System (ADS)

Fu, Weiwei; Primeau, François

2017-11-01

Model drift due to inadequate spinup is a serious problem that complicates the interpretation of climate change simulations. Even after a 300 year spinup we show that solutions are not only still drifting but often drifting away from their eventual equilibrium over large parts of the ocean. Here we present a Newton-Krylov solver for computing cyclostationary equilibrium solutions of a biogeochemical model for the cycling of phosphorus and oxygen. In addition to using previously developed preconditioning strategies - time-averaging and coarse-graining the Jacobian matrix - we also introduce a new strategy: the adiabatic elimination of a fast variable (particulate organic phosphorus) by slaving it to a slow variable (dissolved inorganic phosphorus). We use transport matrices derived from the Community Earth System Model (CESM) with a nominal horizontal resolution of 1° × 1° and 60 vertical levels to implement and test the solver. We find that the new solver obtains seasonally-varying equilibrium solutions with no visible drift using no more than 80 simulation years.

Subspace-Aware Index Codes

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

Kailkhura, Bhavya; Theagarajan, Lakshmi Narasimhan; Varshney, Pramod K.

In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications (e.g., multimedia), the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unawaremore » cases. In conclusion, our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.« less

Subspace-Aware Index Codes

DOE PAGES

Kailkhura, Bhavya; Theagarajan, Lakshmi Narasimhan; Varshney, Pramod K.

2017-04-12

In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications (e.g., multimedia), the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unawaremore » cases. In conclusion, our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE PAGES

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; ...

2016-11-07

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

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

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Physics-Based Preconditioning of a Compressible Flow Solver for Large-Scale Simulations of Additive Manufacturing Processes

NASA Astrophysics Data System (ADS)

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.

Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering.

PubMed

Peng, Xi; Yu, Zhiding; Yi, Zhang; Tang, Huajin

2017-04-01

Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors and retains only connections between the data points from the same subspace (i.e., intrasubspace data points). Recent works achieve good performance by modeling errors into their objective functions to remove the errors from the inputs. However, these approaches face the limitations that the structure of errors should be known prior and a complex convex problem must be solved. In this paper, we present a novel method to eliminate the effects of the errors from the projection space (representation) rather than from the input space. We first prove that l 1 -, l 2 -, l ∞ -, and nuclear-norm-based linear projection spaces share the property of intrasubspace projection dominance, i.e., the coefficients over intrasubspace data points are larger than those over intersubspace data points. Based on this property, we introduce a method to construct a sparse similarity graph, called L2-graph. The subspace clustering and subspace learning algorithms are developed upon L2-graph. We conduct comprehensive experiment on subspace learning, image clustering, and motion segmentation and consider several quantitative benchmarks classification/clustering accuracy, normalized mutual information, and running time. Results show that L2-graph outperforms many state-of-the-art methods in our experiments, including L1-graph, low rank representation (LRR), and latent LRR, least square regression, sparse subspace clustering, and locally linear representation.

Subspace K-means clustering.

PubMed

Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

2013-12-01

To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

A projected preconditioned conjugate gradient algorithm for computing many extreme eigenpairs of a Hermitian matrix [A projected preconditioned conjugate gradient algorithm for computing a large eigenspace of a Hermitian matrix

DOE PAGES

Vecharynski, Eugene; Yang, Chao; Pask, John E.

2015-02-25

Here, we present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimalmore » block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.« less

A Kronecker product splitting preconditioner for two-dimensional space-fractional diffusion equations

NASA Astrophysics Data System (ADS)

Chen, Hao; Lv, Wen; Zhang, Tongtong

2018-05-01

We study preconditioned iterative methods for the linear system arising in the numerical discretization of a two-dimensional space-fractional diffusion equation. Our approach is based on a formulation of the discrete problem that is shown to be the sum of two Kronecker products. By making use of an alternating Kronecker product splitting iteration technique we establish a class of fixed-point iteration methods. Theoretical analysis shows that the new method converges to the unique solution of the linear system. Moreover, the optimal choice of the involved iteration parameters and the corresponding asymptotic convergence rate are computed exactly when the eigenvalues of the system matrix are all real. The basic iteration is accelerated by a Krylov subspace method like GMRES. The corresponding preconditioner is in a form of a Kronecker product structure and requires at each iteration the solution of a set of discrete one-dimensional fractional diffusion equations. We use structure preserving approximations to the discrete one-dimensional fractional diffusion operators in the action of the preconditioning matrix. Numerical examples are presented to illustrate the effectiveness of this approach.

Beyond union of subspaces: Subspace pursuit on Grassmann manifold for data representation

DOE PAGES

Shen, Xinyue; Krim, Hamid; Gu, Yuantao

2016-03-01

Discovering the underlying structure of a high-dimensional signal or big data has always been a challenging topic, and has become harder to tackle especially when the observations are exposed to arbitrary sparse perturbations. Here in this paper, built on the model of a union of subspaces (UoS) with sparse outliers and inspired by a basis pursuit strategy, we exploit the fundamental structure of a Grassmann manifold, and propose a new technique of pursuing the subspaces systematically by solving a non-convex optimization problem using the alternating direction method of multipliers. This problem as noted is further complicated by non-convex constraints onmore » the Grassmann manifold, as well as the bilinearity in the penalty caused by the subspace bases and coefficients. Nevertheless, numerical experiments verify that the proposed algorithm, which provides elegant solutions to the sub-problems in each step, is able to de-couple the subspaces and pursue each of them under time-efficient parallel computation.« less

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

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

None, None

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE PAGES

None, None

2016-11-21

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Geometric mean for subspace selection.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2009-02-01

Subspace selection approaches are powerful tools in pattern classification and data visualization. One of the most important subspace approaches is the linear dimensionality reduction step in the Fisher's linear discriminant analysis (FLDA), which has been successfully employed in many fields such as biometrics, bioinformatics, and multimedia information management. However, the linear dimensionality reduction step in FLDA has a critical drawback: for a classification task with c classes, if the dimension of the projected subspace is strictly lower than c - 1, the projection to a subspace tends to merge those classes, which are close together in the original feature space. If separate classes are sampled from Gaussian distributions, all with identical covariance matrices, then the linear dimensionality reduction step in FLDA maximizes the mean value of the Kullback-Leibler (KL) divergences between different classes. Based on this viewpoint, the geometric mean for subspace selection is studied in this paper. Three criteria are analyzed: 1) maximization of the geometric mean of the KL divergences, 2) maximization of the geometric mean of the normalized KL divergences, and 3) the combination of 1 and 2. Preliminary experimental results based on synthetic data, UCI Machine Learning Repository, and handwriting digits show that the third criterion is a potential discriminative subspace selection method, which significantly reduces the class separation problem in comparing with the linear dimensionality reduction step in FLDA and its several representative extensions.

Advancing parabolic operators in thermodynamic MHD models: Explicit super time-stepping versus implicit schemes with Krylov solvers

NASA Astrophysics Data System (ADS)

Caplan, R. M.; Mikić, Z.; Linker, J. A.; Lionello, R.

2017-05-01

We explore the performance and advantages/disadvantages of using unconditionally stable explicit super time-stepping (STS) algorithms versus implicit schemes with Krylov solvers for integrating parabolic operators in thermodynamic MHD models of the solar corona. Specifically, we compare the second-order Runge-Kutta Legendre (RKL2) STS method with the implicit backward Euler scheme computed using the preconditioned conjugate gradient (PCG) solver with both a point-Jacobi and a non-overlapping domain decomposition ILU0 preconditioner. The algorithms are used to integrate anisotropic Spitzer thermal conduction and artificial kinematic viscosity at time-steps much larger than classic explicit stability criteria allow. A key component of the comparison is the use of an established MHD model (MAS) to compute a real-world simulation on a large HPC cluster. Special attention is placed on the parallel scaling of the algorithms. It is shown that, for a specific problem and model, the RKL2 method is comparable or surpasses the implicit method with PCG solvers in performance and scaling, but suffers from some accuracy limitations. These limitations, and the applicability of RKL methods are briefly discussed.

Hypercyclic subspaces for Frechet space operators

NASA Astrophysics Data System (ADS)

Petersson, Henrik

2006-07-01

A continuous linear operator is hypercyclic if there is an such that the orbit {Tnx} is dense, and such a vector x is said to be hypercyclic for T. Recent progress show that it is possible to characterize Banach space operators that have a hypercyclic subspace, i.e., an infinite dimensional closed subspace of, except for zero, hypercyclic vectors. The following is known to hold: A Banach space operator T has a hypercyclic subspace if there is a sequence (ni) and an infinite dimensional closed subspace such that T is hereditarily hypercyclic for (ni) and Tni->0 pointwise on E. In this note we extend this result to the setting of Frechet spaces that admit a continuous norm, and study some applications for important function spaces. As an application we also prove that any infinite dimensional separable Frechet space with a continuous norm admits an operator with a hypercyclic subspace.

Optimizing Cubature for Efficient Integration of Subspace Deformations

PubMed Central

An, Steven S.; Kim, Theodore; James, Doug L.

2009-01-01

We propose an efficient scheme for evaluating nonlinear subspace forces (and Jacobians) associated with subspace deformations. The core problem we address is efficient integration of the subspace force density over the 3D spatial domain. Similar to Gaussian quadrature schemes that efficiently integrate functions that lie in particular polynomial subspaces, we propose cubature schemes (multi-dimensional quadrature) optimized for efficient integration of force densities associated with particular subspace deformations, particular materials, and particular geometric domains. We support generic subspace deformation kinematics, and nonlinear hyperelastic materials. For an r-dimensional deformation subspace with O(r) cubature points, our method is able to evaluate subspace forces at O(r2) cost. We also describe composite cubature rules for runtime error estimation. Results are provided for various subspace deformation models, several hyperelastic materials (St.Venant-Kirchhoff, Mooney-Rivlin, Arruda-Boyce), and multimodal (graphics, haptics, sound) applications. We show dramatically better efficiency than traditional Monte Carlo integration. CR Categories: I.6.8 [Simulation and Modeling]: Types of Simulation—Animation, I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Physically based modeling G.1.4 [Mathematics of Computing]: Numerical Analysis—Quadrature and Numerical Differentiation PMID:19956777

Indoor Subspacing to Implement Indoorgml for Indoor Navigation

NASA Astrophysics Data System (ADS)

Jung, H.; Lee, J.

2015-10-01

According to an increasing demand for indoor navigation, there are great attempts to develop applicable indoor network. Representation for a room as a node is not sufficient to apply complex and large buildings. As OGC established IndoorGML, subspacing to partition the space for constructing logical network is introduced. Concerning subspacing for indoor network, transition space like halls or corridors also have to be considered. This study presents the subspacing process for creating an indoor network in shopping mall. Furthermore, categorization of transition space is performed and subspacing of this space is considered. Hall and squares in mall is especially defined for subspacing. Finally, implementation of subspacing process for indoor network is presented.

Active Subspaces of Airfoil Shape Parameterizations

NASA Astrophysics Data System (ADS)

Grey, Zachary J.; Constantine, Paul G.

2018-05-01

Design and optimization benefit from understanding the dependence of a quantity of interest (e.g., a design objective or constraint function) on the design variables. A low-dimensional active subspace, when present, identifies important directions in the space of design variables; perturbing a design along the active subspace associated with a particular quantity of interest changes that quantity more, on average, than perturbing the design orthogonally to the active subspace. This low-dimensional structure provides insights that characterize the dependence of quantities of interest on design variables. Airfoil design in a transonic flow field with a parameterized geometry is a popular test problem for design methodologies. We examine two particular airfoil shape parameterizations, PARSEC and CST, and study the active subspaces present in two common design quantities of interest, transonic lift and drag coefficients, under each shape parameterization. We mathematically relate the two parameterizations with a common polynomial series. The active subspaces enable low-dimensional approximations of lift and drag that relate to physical airfoil properties. In particular, we obtain and interpret a two-dimensional approximation of both transonic lift and drag, and we show how these approximation inform a multi-objective design problem.

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Characterizing L1-norm best-fit subspaces

NASA Astrophysics Data System (ADS)

Brooks, J. Paul; Dulá, José H.

2017-05-01

Fitting affine objects to data is the basis of many tools and methodologies in statistics, machine learning, and signal processing. The L1 norm is often employed to produce subspaces exhibiting a robustness to outliers and faulty observations. The L1-norm best-fit subspace problem is directly formulated as a nonlinear, nonconvex, and nondifferentiable optimization problem. The case when the subspace is a hyperplane can be solved to global optimality efficiently by solving a series of linear programs. The problem of finding the best-fit line has recently been shown to be NP-hard. We present necessary conditions for optimality for the best-fit subspace problem, and use them to characterize properties of optimal solutions.

General purpose nonlinear system solver based on Newton-Krylov method.

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

2013-12-01

KINSOL is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/Algebraic equation Solvers [1]. KINSOL is a general-purpose nonlinear system solver based on Newton-Krylov and fixed-point solver technologies [2].

Zeno subspace in quantum-walk dynamics

NASA Astrophysics Data System (ADS)

Chandrashekar, C. M.

2010-11-01

We investigate discrete-time quantum-walk evolution under the influence of periodic measurements in position subspace. The undisturbed survival probability of the particle at the position subspace P(0,t) is compared with the survival probability after frequent (n) measurements at interval τ=t/n, P(0,τ)n. We show that P(0,τ)n>P(0,t) leads to the quantum Zeno effect in position subspace when a parameter θ in the quantum coin operations and frequency of measurements is greater than the critical value, θ>θc and n>nc. This Zeno effect in the subspace preserves the dynamics in coin Hilbert space of the walk dynamics and has the potential to play a significant role in quantum tasks such as preserving the quantum state of the particle at any particular position, and to understand the Zeno dynamics in a multidimensional system that is highly transient in nature.

Pushing Memory Bandwidth Limitations Through Efficient Implementations of Block-Krylov Space Solvers on GPUs

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

Clark, M. A.; Strelchenko, Alexei; Vaquero, Alejandro

Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic memory-bandwidth constraints of the matrix-vector operation dominating iterative solvers. Batching this operation for multiple vectors and exploiting cache and register blocking can yield a super-linear speed up. Block-Krylov solvers can naturally take advantage of such batched matrix-vector operations, further reducing the iterations to solution by sharing the Krylov space between solves. However, practical implementations typically suffer from the quadratic scaling in the number of vector-vector operations.more » Using the QUDA library, we present an implementation of a block-CG solver on NVIDIA GPUs which reduces the memory-bandwidth complexity of vector-vector operations from quadratic to linear. We present results for the HISQ discretization, showing a 5x speedup compared to highly-optimized independent Krylov solves on NVIDIA's SaturnV cluster.« less

Active Subspaces for Wind Plant Surrogate Modeling

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

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

Learning Robust and Discriminative Subspace With Low-Rank Constraints.

PubMed

Li, Sheng; Fu, Yun

2016-11-01

In this paper, we aim at learning robust and discriminative subspaces from noisy data. Subspace learning is widely used in extracting discriminative features for classification. However, when data are contaminated with severe noise, the performance of most existing subspace learning methods would be limited. Recent advances in low-rank modeling provide effective solutions for removing noise or outliers contained in sample sets, which motivates us to take advantage of low-rank constraints in order to exploit robust and discriminative subspace for classification. In particular, we present a discriminative subspace learning method called the supervised regularization-based robust subspace (SRRS) approach, by incorporating the low-rank constraint. SRRS seeks low-rank representations from the noisy data, and learns a discriminative subspace from the recovered clean data jointly. A supervised regularization function is designed to make use of the class label information, and therefore to enhance the discriminability of subspace. Our approach is formulated as a constrained rank-minimization problem. We design an inexact augmented Lagrange multiplier optimization algorithm to solve it. Unlike the existing sparse representation and low-rank learning methods, our approach learns a low-dimensional subspace from recovered data, and explicitly incorporates the supervised information. Our approach and some baselines are evaluated on the COIL-100, ALOI, Extended YaleB, FERET, AR, and KinFace databases. The experimental results demonstrate the effectiveness of our approach, especially when the data contain considerable noise or variations.

Nonadiabatic holonomic quantum computation in decoherence-free subspaces.

PubMed

Xu, G F; Zhang, J; Tong, D M; Sjöqvist, Erik; Kwek, L C

2012-10-26

Quantum computation that combines the coherence stabilization virtues of decoherence-free subspaces and the fault tolerance of geometric holonomic control is of great practical importance. Some schemes of adiabatic holonomic quantum computation in decoherence-free subspaces have been proposed in the past few years. However, nonadiabatic holonomic quantum computation in decoherence-free subspaces, which avoids a long run-time requirement but with all the robust advantages, remains an open problem. Here, we demonstrate how to realize nonadiabatic holonomic quantum computation in decoherence-free subspaces. By using only three neighboring physical qubits undergoing collective dephasing to encode one logical qubit, we realize a universal set of quantum gates.

An alternative subspace approach to EEG dipole source localization

NASA Astrophysics Data System (ADS)

Xu, Xiao-Liang; Xu, Bobby; He, Bin

2004-01-01

In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist.

Geometry aware Stationary Subspace Analysis

DTIC Science & Technology

2016-11-22

approach to handling non-stationarity is to remove or minimize it before attempting to analyze the data. In the context of brain computer interface ( BCI ...context of brain computer interface ( BCI ) data analysis, two such note-worthy methods are stationary subspace analysis (SSA) (von Bünau et al., 2009a... BCI systems, is sCSP. Its goal is to project the data onto a subspace in which the various data classes are more separable. The sCSP method directs

Subspace-based interference removal methods for a multichannel biomagnetic sensor array.

PubMed

Sekihara, Kensuke; Nagarajan, Srikantan S

2017-10-01

In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

Subspace-based interference removal methods for a multichannel biomagnetic sensor array

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Nagarajan, Srikantan S.

2017-10-01

Objective. In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. Approach. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation

NASA Technical Reports Server (NTRS)

Cai, Xiao-Chuan; Gropp, William D.; Keyes, David E.; Melvin, Robin G.; Young, David P.

1996-01-01

We study parallel two-level overlapping Schwarz algorithms for solving nonlinear finite element problems, in particular, for the full potential equation of aerodynamics discretized in two dimensions with bilinear elements. The overall algorithm, Newton-Krylov-Schwarz (NKS), employs an inexact finite-difference Newton method and a Krylov space iterative method, with a two-level overlapping Schwarz method as a preconditioner. We demonstrate that NKS, combined with a density upwinding continuation strategy for problems with weak shocks, is robust and, economical for this class of mixed elliptic-hyperbolic nonlinear partial differential equations, with proper specification of several parameters. We study upwinding parameters, inner convergence tolerance, coarse grid density, subdomain overlap, and the level of fill-in in the incomplete factorization, and report their effect on numerical convergence rate, overall execution time, and parallel efficiency on a distributed-memory parallel computer.

An accelerated subspace iteration for eigenvector derivatives

NASA Technical Reports Server (NTRS)

Ting, Tienko

1991-01-01

An accelerated subspace iteration method for calculating eigenvector derivatives has been developed. Factors affecting the effectiveness and the reliability of the subspace iteration are identified, and effective strategies concerning these factors are presented. The method has been implemented, and the results of a demonstration problem are presented.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Scalable implicit incompressible resistive MHD with stabilized FE and fully-coupled Newton–Krylov-AMG

DOE PAGES

Shadid, J. N.; Pawlowski, R. P.; Cyr, E. C.; ...

2016-02-10

Here, we discuss that the computational solution of the governing balance equations for mass, momentum, heat transfer and magnetic induction for resistive magnetohydrodynamics (MHD) systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena, as well as the significant range of time- and length-scales that the interactions of these physical mechanisms produce. This paper explores the development of a scalable, fully-implicit stabilized unstructured finite element (FE) capability for 3D incompressible resistive MHD. The discussion considers the development of a stabilized FE formulation in context of the variational multiscale (VMS) method,more » and describes the scalable implicit time integration and direct-to-steady-state solution capability. The nonlinear solver strategy employs Newton–Krylov methods, which are preconditioned using fully-coupled algebraic multilevel preconditioners. These preconditioners are shown to enable a robust, scalable and efficient solution approach for the large-scale sparse linear systems generated by the Newton linearization. Verification results demonstrate the expected order-of-accuracy for the stabilized FE discretization. The approach is tested on a variety of prototype problems, that include MHD duct flows, an unstable hydromagnetic Kelvin–Helmholtz shear layer, and a 3D island coalescence problem used to model magnetic reconnection. Initial results that explore the scaling of the solution methods are also presented on up to 128K processors for problems with up to 1.8B unknowns on a CrayXK7.« less

New subspace methods for ATR

NASA Astrophysics Data System (ADS)

Zhang, Peng; Peng, Jing; Sims, S. Richard F.

2005-05-01

In ATR applications, each feature is a convolution of an image with a filter. It is important to use most discriminant features to produce compact representations. We propose two novel subspace methods for dimension reduction to address limitations associated with Fukunaga-Koontz Transform (FKT). The first method, Scatter-FKT, assumes that target is more homogeneous, while clutter can be anything other than target and anywhere. Thus, instead of estimating a clutter covariance matrix, Scatter-FKT computes a clutter scatter matrix that measures the spread of clutter from the target mean. We choose dimensions along which the difference in variation between target and clutter is most pronounced. When the target follows a Gaussian distribution, Scatter-FKT can be viewed as a generalization of FKT. The second method, Optimal Bayesian Subspace, is derived from the optimal Bayesian classifier. It selects dimensions such that the minimum Bayes error rate can be achieved. When both target and clutter follow Gaussian distributions, OBS computes optimal subspace representations. We compare our methods against FKT using character image as well as IR data.

Techniques and Software for Monolithic Preconditioning of Moderately-sized Geodynamic Stokes Flow Problems

NASA Astrophysics Data System (ADS)

Sanan, Patrick; May, Dave A.; Schenk, Olaf; Bollhöffer, Matthias

2017-04-01

Geodynamics simulations typically involve the repeated solution of saddle-point systems arising from the Stokes equations. These computations often dominate the time to solution. Direct solvers are known for their robustness and ``black box'' properties, yet exhibit superlinear memory requirements and time to solution. More complex multilevel-preconditioned iterative solvers have been very successful for large problems, yet their use can require more effort from the practitioner in terms of setting up a solver and choosing its parameters. We champion an intermediate approach, based on leveraging the power of modern incomplete factorization techniques for indefinite symmetric matrices. These provide an interesting alternative in situations in between the regimes where direct solvers are an obvious choice and those where complex, scalable, iterative solvers are an obvious choice. That is, much like their relatives for definite systems, ILU/ICC-preconditioned Krylov methods and ILU/ICC-smoothed multigrid methods, the approaches demonstrated here provide a useful addition to the solver toolkit. We present results with a simple, PETSc-based, open-source Q2-Q1 (Taylor-Hood) finite element discretization, in 2 and 3 dimensions, with the Stokes and Lamé (linear elasticity) saddle point systems. Attention is paid to cases in which full-operator incomplete factorization gives an improvement in time to solution over direct solution methods (which may not even be feasible due to memory limitations), without the complication of more complex (or at least, less-automatic) preconditioners or smoothers. As an important factor in the relevance of these tools is their availability in portable software, we also describe open-source PETSc interfaces to the factorization routines.

General subspace learning with corrupted training data via graph embedding.

PubMed

Bao, Bing-Kun; Liu, Guangcan; Hong, Richang; Yan, Shuicheng; Xu, Changsheng

2013-11-01

We address the following subspace learning problem: supposing we are given a set of labeled, corrupted training data points, how to learn the underlying subspace, which contains three components: an intrinsic subspace that captures certain desired properties of a data set, a penalty subspace that fits the undesired properties of the data, and an error container that models the gross corruptions possibly existing in the data. Given a set of data points, these three components can be learned by solving a nuclear norm regularized optimization problem, which is convex and can be efficiently solved in polynomial time. Using the method as a tool, we propose a new discriminant analysis (i.e., supervised subspace learning) algorithm called Corruptions Tolerant Discriminant Analysis (CTDA), in which the intrinsic subspace is used to capture the features with high within-class similarity, the penalty subspace takes the role of modeling the undesired features with high between-class similarity, and the error container takes charge of fitting the possible corruptions in the data. We show that CTDA can well handle the gross corruptions possibly existing in the training data, whereas previous linear discriminant analysis algorithms arguably fail in such a setting. Extensive experiments conducted on two benchmark human face data sets and one object recognition data set show that CTDA outperforms the related algorithms.

Adiabatic evolution of decoherence-free subspaces and its shortcuts

NASA Astrophysics Data System (ADS)

Wu, S. L.; Huang, X. L.; Li, H.; Yi, X. X.

2017-10-01

The adiabatic theorem and shortcuts to adiabaticity for time-dependent open quantum systems are explored in this paper. Starting from the definition of dynamical stable decoherence-free subspace, we show that, under a compact adiabatic condition, the quantum state remains in the time-dependent decoherence-free subspace with an extremely high purity, even though the dynamics of the open quantum system may not be adiabatic. The adiabatic condition mentioned here in the adiabatic theorem for open systems is very similar to that for closed quantum systems, except that the operators required to change slowly are the Lindblad operators. We also show that the adiabatic evolution of decoherence-free subspaces depends on the existence of instantaneous decoherence-free subspaces, which requires that the Hamiltonian of open quantum systems be engineered according to the incoherent control protocol. In addition, shortcuts to adiabaticity for adiabatic decoherence-free subspaces are also presented based on the transitionless quantum driving method. Finally, we provide an example that consists of a two-level system coupled to a broadband squeezed vacuum field to show our theory. Our approach employs Markovian master equations and the theory can apply to finite-dimensional quantum open systems.

Implicit solution of Navier-Stokes equations on staggered curvilinear grids using a Newton-Krylov method with a novel analytical Jacobian.

NASA Astrophysics Data System (ADS)

Borazjani, Iman; Asgharzadeh, Hafez

2015-11-01

Flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates with explicit and semi-implicit schemes. Implicit schemes can be used to overcome these restrictions. However, implementing implicit solver for nonlinear equations including Navier-Stokes is not straightforward. Newton-Krylov subspace methods (NKMs) are one of the most advanced iterative methods to solve non-linear equations such as implicit descritization of the Navier-Stokes equation. The efficiency of NKMs massively depends on the Jacobian formation method, e.g., automatic differentiation is very expensive, and matrix-free methods slow down as the mesh is refined. Analytical Jacobian is inexpensive method, but derivation of analytical Jacobian for Navier-Stokes equation on staggered grid is challenging. The NKM with a novel analytical Jacobian was developed and validated against Taylor-Green vortex and pulsatile flow in a 90 degree bend. The developed method successfully handled the complex geometries such as an intracranial aneurysm with multiple overset grids, and immersed boundaries. It is shown that the NKM with an analytical Jacobian is 3 to 25 times faster than the fixed-point implicit Runge-Kutta method, and more than 100 times faster than automatic differentiation depending on the grid (size) and the flow problem. The developed methods are fully parallelized with parallel efficiency of 80-90% on the problems tested.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 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...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2010 CFR

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...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 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...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 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...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 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...

Multilevel Iterative Methods in Nonlinear Computational Plasma Physics

NASA Astrophysics Data System (ADS)

Knoll, D. A.; Finn, J. M.

1997-11-01

Many applications in computational plasma physics involve the implicit numerical solution of coupled systems of nonlinear partial differential equations or integro-differential equations. Such problems arise in MHD, systems of Vlasov-Fokker-Planck equations, edge plasma fluid equations. We have been developing matrix-free Newton-Krylov algorithms for such problems and have applied these algorithms to the edge plasma fluid equations [1,2] and to the Vlasov-Fokker-Planck equation [3]. Recently we have found that with increasing grid refinement, the number of Krylov iterations required per Newton iteration has grown unmanageable [4]. This has led us to the study of multigrid methods as a means of preconditioning matrix-free Newton-Krylov methods. In this poster we will give details of the general multigrid preconditioned Newton-Krylov algorithm, as well as algorithm performance details on problems of interest in the areas of magnetohydrodynamics and edge plasma physics. Work supported by US DoE 1. Knoll and McHugh, J. Comput. Phys., 116, pg. 281 (1995) 2. Knoll and McHugh, Comput. Phys. Comm., 88, pg. 141 (1995) 3. Mousseau and Knoll, J. Comput. Phys. (1997) (to appear) 4. Knoll and McHugh, SIAM J. Sci. Comput. 19, (1998) (to appear)

Controller reduction by preserving impulse response energy

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.; Su, Tzu-Jeng

1989-01-01

A model order reduction algorithm based on a Krylov recurrence formulation is developed to reduce order of controllers. The reduced-order controller is obtained by projecting the full-order LQG controller onto a Krylov subspace in which either the controllability or the observability grammian is equal to the identity matrix. The reduced-order controller preserves the impulse response energy of the full-order controller and has a parameter-matching property. Two numerical examples drawn from other controller reduction literature are used to illustrate the efficacy of the proposed reduction algorithm.

Anomaly General Circulation Models.

NASA Astrophysics Data System (ADS)

Navarra, Antonio

The feasibility of the anomaly model is assessed using barotropic and baroclinic models. In the barotropic case, both a stationary and a time-dependent model has been formulated and constructed, whereas only the stationary, linear case is considered in the baroclinic case. Results from the barotropic model indicate that a relation between the stationary solution and the time-averaged non-linear solution exists. The stationary linear baroclinic solution can therefore be considered with some confidence. The linear baroclinic anomaly model poses a formidable mathematical problem because it is necessary to solve a gigantic linear system to obtain the solution. A new method to find solution of large linear system, based on a projection on the Krylov subspace is shown to be successful when applied to the linearized baroclinic anomaly model. The scheme consists of projecting the original linear system on the Krylov subspace, thereby reducing the dimensionality of the matrix to be inverted to obtain the solution. With an appropriate setting of the damping parameters, the iterative Krylov method reaches a solution even using a Krylov subspace ten times smaller than the original space of the problem. This generality allows the treatment of the important problem of linear waves in the atmosphere. A larger class (nonzonally symmetric) of basic states can now be treated for the baroclinic primitive equations. These problem leads to large unsymmetrical linear systems of order 10000 and more which can now be successfully tackled by the Krylov method. The (R7) linear anomaly model is used to investigate extensively the linear response to equatorial and mid-latitude prescribed heating. The results indicate that the solution is deeply affected by the presence of the stationary waves in the basic state. The instability of the asymmetric flows, first pointed out by Simmons et al. (1983), is active also in the baroclinic case. However, the presence of baroclinic processes modifies the

Subspace Methods for Massive and Messy Data

DTIC Science & Technology

2017-07-12

Subspace Methods for Massive and Messy Data The views, opinions and/or findings contained in this report are those of the author(s) and should not...AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 REPORT DOCUMENTATION PAGE 11. SPONSOR...Number: W911NF-14-1-0634 Organization: University of Michigan - Ann Arbor Title: Subspace Methods for Massive and Messy Data Report Term: 0-Other

Manifold learning-based subspace distance for machinery damage assessment

NASA Astrophysics Data System (ADS)

Sun, Chuang; Zhang, Zhousuo; He, Zhengjia; Shen, Zhongjie; Chen, Binqiang

2016-03-01

Damage assessment is very meaningful to keep safety and reliability of machinery components, and vibration analysis is an effective way to carry out the damage assessment. In this paper, a damage index is designed by performing manifold distance analysis on vibration signal. To calculate the index, vibration signal is collected firstly, and feature extraction is carried out to obtain statistical features that can capture signal characteristics comprehensively. Then, manifold learning algorithm is utilized to decompose feature matrix to be a subspace, that is, manifold subspace. The manifold learning algorithm seeks to keep local relationship of the feature matrix, which is more meaningful for damage assessment. Finally, Grassmann distance between manifold subspaces is defined as a damage index. The Grassmann distance reflecting manifold structure is a suitable metric to measure distance between subspaces in the manifold. The defined damage index is applied to damage assessment of a rotor and the bearing, and the result validates its effectiveness for damage assessment of machinery component.

Multilevel acceleration of scattering-source iterations with application to electron transport

DOE PAGES

Drumm, Clif; Fan, Wesley

2017-08-18

Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates (S N) or spherical-harmonics (P N) solve to accelerate convergence of a high-order S N source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergencemore » of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.« less

Fully Implicit, Nonlinear 3D Extended Magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Chacon, Luis; Knoll, Dana

2003-10-01

Extended magnetohydrodynamics (XMHD) includes nonideal effects such as nonlinear, anisotropic transport and two-fluid (Hall) effects. XMHD supports multiple, separate time scales that make explicit time differencing approaches extremely inefficient. While a fully implicit implementation promises efficiency without sacrificing numerical accuracy,(D. A. Knoll et al., phJ. Comput. Phys.) 185 (2), 583-611 (2003) the nonlinear nature of the XMHD system and the numerical stiffness associated with the fast waves make this endeavor difficult. Newton-Krylov methods are, however, ideally suited for such a task. These synergistically combine Newton's method for nonlinear convergence, and Krylov techniques to solve the associated Jacobian (linear) systems. Krylov methods can be implemented Jacobian-free and can be preconditioned for efficiency. Successful preconditioning strategies have been developed for 2D incompressible resistive(L. Chacón et al., phJ. Comput. Phys). 178 (1), 15- 36 (2002) and Hall(L. Chacón and D. A. Knoll, phJ. Comput. Phys.), 188 (2), 573-592 (2003) MHD models. These are based on ``physics-based'' ideas, in which knowledge of the physics is exploited to derive well-conditioned (diagonally-dominant) approximations to the original system that are amenable to optimal solver technologies (multigrid). In this work, we will describe the status of the extension of the 2D preconditioning ideas for a 3D compressible, single-fluid XMHD model.

An application of the Krylov-FSP-SSA method to parameter fitting with maximum likelihood

NASA Astrophysics Data System (ADS)

Dinh, Khanh N.; Sidje, Roger B.

2017-12-01

Monte Carlo methods such as the stochastic simulation algorithm (SSA) have traditionally been employed in gene regulation problems. However, there has been increasing interest to directly obtain the probability distribution of the molecules involved by solving the chemical master equation (CME). This requires addressing the curse of dimensionality that is inherent in most gene regulation problems. The finite state projection (FSP) seeks to address the challenge and there have been variants that further reduce the size of the projection or that accelerate the resulting matrix exponential. The Krylov-FSP-SSA variant has proved numerically efficient by combining, on one hand, the SSA to adaptively drive the FSP, and on the other hand, adaptive Krylov techniques to evaluate the matrix exponential. Here we apply this Krylov-FSP-SSA to a mutual inhibitory gene network synthetically engineered in Saccharomyces cerevisiae, in which bimodality arises. We show numerically that the approach can efficiently approximate the transient probability distribution, and this has important implications for parameter fitting, where the CME has to be solved for many different parameter sets. The fitting scheme amounts to an optimization problem of finding the parameter set so that the transient probability distributions fit the observations with maximum likelihood. We compare five optimization schemes for this difficult problem, thereby providing further insights into this approach of parameter estimation that is often applied to models in systems biology where there is a need to calibrate free parameters. Work supported by NSF grant DMS-1320849.

Globalized Newton-Krylov-Schwarz Algorithms and Software for Parallel Implicit CFD

NASA Technical Reports Server (NTRS)

Gropp, W. D.; Keyes, D. E.; McInnes, L. C.; Tidriri, M. D.

1998-01-01

Implicit solution methods are important in applications modeled by PDEs with disparate temporal and spatial scales. Because such applications require high resolution with reasonable turnaround, "routine" parallelization is essential. The pseudo-transient matrix-free Newton-Krylov-Schwarz (Psi-NKS) algorithmic framework is presented as an answer. We show that, for the classical problem of three-dimensional transonic Euler flow about an M6 wing, Psi-NKS can simultaneously deliver: globalized, asymptotically rapid convergence through adaptive pseudo- transient continuation and Newton's method-, reasonable parallelizability for an implicit method through deferred synchronization and favorable communication-to-computation scaling in the Krylov linear solver; and high per- processor performance through attention to distributed memory and cache locality, especially through the Schwarz preconditioner. Two discouraging features of Psi-NKS methods are their sensitivity to the coding of the underlying PDE discretization and the large number of parameters that must be selected to govern convergence. We therefore distill several recommendations from our experience and from our reading of the literature on various algorithmic components of Psi-NKS, and we describe a freely available, MPI-based portable parallel software implementation of the solver employed here.

Solution of nonlinear time-dependent PDEs through componentwise approximation of matrix functions

NASA Astrophysics Data System (ADS)

Cibotarica, Alexandru; Lambers, James V.; Palchak, Elisabeth M.

2016-09-01

Exponential propagation iterative (EPI) methods provide an efficient approach to the solution of large stiff systems of ODEs, compared to standard integrators. However, the bulk of the computational effort in these methods is due to products of matrix functions and vectors, which can become very costly at high resolution due to an increase in the number of Krylov projection steps needed to maintain accuracy. In this paper, it is proposed to modify EPI methods by using Krylov subspace spectral (KSS) methods, instead of standard Krylov projection methods, to compute products of matrix functions and vectors. Numerical experiments demonstrate that this modification causes the number of Krylov projection steps to become bounded independently of the grid size, thus dramatically improving efficiency and scalability. As a result, for each test problem featured, as the total number of grid points increases, the growth in computation time is just below linear, while other methods achieved this only on selected test problems or not at all.

Conjunctive patches subspace learning with side information for collaborative image retrieval.

PubMed

Zhang, Lining; Wang, Lipo; Lin, Weisi

2012-08-01

Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

PubMed

Jankovic, Marko V; Ogawa, Hidemitsu

2006-03-01

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.

Adaptive low-rank subspace learning with online optimization for robust visual tracking.

PubMed

Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

2017-04-01

In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Randomized subspace-based robust principal component analysis for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Yang, Gang; Li, Jialin; Zhang, Dianfa

2018-01-01

A randomized subspace-based robust principal component analysis (RSRPCA) method for anomaly detection in hyperspectral imagery (HSI) is proposed. The RSRPCA combines advantages of randomized column subspace and robust principal component analysis (RPCA). It assumes that the background has low-rank properties, and the anomalies are sparse and do not lie in the column subspace of the background. First, RSRPCA implements random sampling to sketch the original HSI dataset from columns and to construct a randomized column subspace of the background. Structured random projections are also adopted to sketch the HSI dataset from rows. Sketching from columns and rows could greatly reduce the computational requirements of RSRPCA. Second, the RSRPCA adopts the columnwise RPCA (CWRPCA) to eliminate negative effects of sampled anomaly pixels and that purifies the previous randomized column subspace by removing sampled anomaly columns. The CWRPCA decomposes the submatrix of the HSI data into a low-rank matrix (i.e., background component), a noisy matrix (i.e., noise component), and a sparse anomaly matrix (i.e., anomaly component) with only a small proportion of nonzero columns. The algorithm of inexact augmented Lagrange multiplier is utilized to optimize the CWRPCA problem and estimate the sparse matrix. Nonzero columns of the sparse anomaly matrix point to sampled anomaly columns in the submatrix. Third, all the pixels are projected onto the complemental subspace of the purified randomized column subspace of the background and the anomaly pixels in the original HSI data are finally exactly located. Several experiments on three real hyperspectral images are carefully designed to investigate the detection performance of RSRPCA, and the results are compared with four state-of-the-art methods. Experimental results show that the proposed RSRPCA outperforms four comparison methods both in detection performance and in computational time.

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

Identifying Optimal Measurement Subspace for the Ensemble Kalman Filter

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

Zhou, Ning; Huang, Zhenyu; Welch, Greg

2012-05-24

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimization algorithm based on the generalized eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective tradeoff between computational complexity and estimation accuracy. This algorithm also can be extended to other Kalman filters for measurement subspace selection.

Bi Sparsity Pursuit: A Paradigm for Robust Subspace Recovery

DTIC Science & Technology

2016-09-27

16. SECURITY CLASSIFICATION OF: The success of sparse models in computer vision and machine learning is due to the fact that, high dimensional data...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Signal recovery, Sparse learning , Subspace modeling REPORT DOCUMENTATION PAGE 11...vision and machine learning is due to the fact that, high dimensional data is distributed in a union of low dimensional subspaces in many real-world

Tensor-GMRES method for large sparse systems of nonlinear equations

NASA Technical Reports Server (NTRS)

Feng, Dan; Pulliam, Thomas H.

1994-01-01

This paper introduces a tensor-Krylov method, the tensor-GMRES method, for large sparse systems of nonlinear equations. This method is a coupling of tensor model formation and solution techniques for nonlinear equations with Krylov subspace projection techniques for unsymmetric systems of linear equations. Traditional tensor methods for nonlinear equations are based on a quadratic model of the nonlinear function, a standard linear model augmented by a simple second order term. These methods are shown to be significantly more efficient than standard methods both on nonsingular problems and on problems where the Jacobian matrix at the solution is singular. A major disadvantage of the traditional tensor methods is that the solution of the tensor model requires the factorization of the Jacobian matrix, which may not be suitable for problems where the Jacobian matrix is large and has a 'bad' sparsity structure for an efficient factorization. We overcome this difficulty by forming and solving the tensor model using an extension of a Newton-GMRES scheme. Like traditional tensor methods, we show that the new tensor method has significant computational advantages over the analogous Newton counterpart. Consistent with Krylov subspace based methods, the new tensor method does not depend on the factorization of the Jacobian matrix. As a matter of fact, the Jacobian matrix is never needed explicitly.

Limb remote-preconditioning protects against focal ischemia in rats and contradicts the dogma of therapeutic time windows for preconditioning

PubMed Central

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

Locally indistinguishable subspaces spanned by three-qubit unextendible product bases

NASA Astrophysics Data System (ADS)

Duan, Runyao; Xin, Yu; Ying, Mingsheng

2010-03-01

We study the local distinguishability of general multiqubit states and show that local projective measurements and classical communication are as powerful as the most general local measurements and classical communication. Remarkably, this indicates that the local distinguishability of multiqubit states can be decided efficiently. Another useful consequence is that a set of orthogonal n-qubit states is locally distinguishable only if the summation of their orthogonal Schmidt numbers is less than the total dimension 2n. Employing these results, we show that any orthonormal basis of a subspace spanned by arbitrary three-qubit orthogonal unextendible product bases (UPB) cannot be exactly distinguishable by local operations and classical communication. This not only reveals another intrinsic property of three-qubit orthogonal UPB but also provides a class of locally indistinguishable subspaces with dimension 4. We also explicitly construct locally indistinguishable subspaces with dimensions 3 and 5, respectively. Similar to the bipartite case, these results on multipartite locally indistinguishable subspaces can be used to estimate the one-shot environment-assisted classical capacity of a class of quantum broadcast channels.

Independence and totalness of subspaces in phase space methods

NASA Astrophysics Data System (ADS)

Vourdas, A.

2018-04-01

The concepts of independence and totalness of subspaces are introduced in the context of quasi-probability distributions in phase space, for quantum systems with finite-dimensional Hilbert space. It is shown that due to the non-distributivity of the lattice of subspaces, there are various levels of independence, from pairwise independence up to (full) independence. Pairwise totalness, totalness and other intermediate concepts are also introduced, which roughly express that the subspaces overlap strongly among themselves, and they cover the full Hilbert space. A duality between independence and totalness, that involves orthocomplementation (logical NOT operation), is discussed. Another approach to independence is also studied, using Rota's formalism on independent partitions of the Hilbert space. This is used to define informational independence, which is proved to be equivalent to independence. As an application, the pentagram (used in discussions on contextuality) is analysed using these concepts.

A hyperspectral imagery anomaly detection algorithm based on local three-dimensional orthogonal subspace projection

NASA Astrophysics Data System (ADS)

Zhang, Xing; Wen, Gongjian

2015-10-01

Anomaly detection (AD) becomes increasingly important in hyperspectral imagery analysis with many practical applications. Local orthogonal subspace projection (LOSP) detector is a popular anomaly detector which exploits local endmembers/eigenvectors around the pixel under test (PUT) to construct background subspace. However, this subspace only takes advantage of the spectral information, but the spatial correlat ion of the background clutter is neglected, which leads to the anomaly detection result sensitive to the accuracy of the estimated subspace. In this paper, a local three dimensional orthogonal subspace projection (3D-LOSP) algorithm is proposed. Firstly, under the jointly use of both spectral and spatial information, three directional background subspaces are created along the image height direction, the image width direction and the spectral direction, respectively. Then, the three corresponding orthogonal subspaces are calculated. After that, each vector along three direction of the local cube is projected onto the corresponding orthogonal subspace. Finally, a composite score is given through the three direction operators. In 3D-LOSP, the anomalies are redefined as the target not only spectrally different to the background, but also spatially distinct. Thanks to the addition of the spatial information, the robustness of the anomaly detection result has been improved greatly by the proposed 3D-LOSP algorithm. It is noteworthy that the proposed algorithm is an expansion of LOSP and this ideology can inspire many other spectral-based anomaly detection methods. Experiments with real hyperspectral images have proved the stability of the detection result.

Optimal preconditioning of lattice Boltzmann methods

NASA Astrophysics Data System (ADS)

Izquierdo, Salvador; Fueyo, Norberto

2009-09-01

A preconditioning technique to accelerate the simulation of steady-state problems using the single-relaxation-time (SRT) lattice Boltzmann (LB) method was first proposed by Guo et al. [Z. Guo, T. Zhao, Y. Shi, Preconditioned lattice-Boltzmann method for steady flows, Phys. Rev. E 70 (2004) 066706-1]. The key idea in this preconditioner is to modify the equilibrium distribution function in such a way that, by means of a Chapman-Enskog expansion, a time-derivative preconditioner of the Navier-Stokes (NS) equations is obtained. In the present contribution, the optimal values for the free parameter γ of this preconditioner are searched both numerically and theoretically; the later with the aid of linear-stability analysis and with the condition number of the system of NS equations. The influence of the collision operator, single- versus multiple-relaxation-times (MRT), is also studied. Three steady-state laminar test cases are used for validation, namely: the two-dimensional lid-driven cavity, a two-dimensional microchannel and the three-dimensional backward-facing step. Finally, guidelines are suggested for an a priori definition of optimal preconditioning parameters as a function of the Reynolds and Mach numbers. The new optimally preconditioned MRT method derived is shown to improve, simultaneously, the rate of convergence, the stability and the accuracy of the lattice Boltzmann simulations, when compared to the non-preconditioned methods and to the optimally preconditioned SRT one. Additionally, direct time-derivative preconditioning of the LB equation is also studied.

BI-sparsity pursuit for robust subspace recovery

DOE PAGES

Bian, Xiao; Krim, Hamid

2015-09-01

Here, the success of sparse models in computer vision and machine learning in many real-world applications, may be attributed in large part, to the fact that many high dimensional data are distributed in a union of low dimensional subspaces. The underlying structure may, however, be adversely affected by sparse errors, thus inducing additional complexity in recovering it. In this paper, we propose a bi-sparse model as a framework to investigate and analyze this problem, and provide as a result , a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We additionally demonstrate the effectiveness ofmore » our method by experiments on real-world vision data.« less

An implementation of the QMR method based on coupled two-term recurrences

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noeel M.

1992-01-01

The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are given, and the look-ahead strategy is described. A new implementation of the QMR method, based on this coupled two-term algorithm, is described. A simplified version of the QMR algorithm without look-ahead is also presented, and the special case of QMR for complex symmetric linear systems is considered. Results of numerical experiments comparing the original and the new implementations of the QMR method are reported.

Projection methods for the numerical solution of Markov chain models

NASA Technical Reports Server (NTRS)

Saad, Youcef

1989-01-01

Projection methods for computing stationary probability distributions for Markov chain models are presented. A general projection method is a method which seeks an approximation from a subspace of small dimension to the original problem. Thus, the original matrix problem of size N is approximated by one of dimension m, typically much smaller than N. A particularly successful class of methods based on this principle is that of Krylov subspace methods which utilize subspaces of the form span(v,av,...,A(exp m-1)v). These methods are effective in solving linear systems and eigenvalue problems (Lanczos, Arnoldi,...) as well as nonlinear equations. They can be combined with more traditional iterative methods such as successive overrelaxation, symmetric successive overrelaxation, or with incomplete factorization methods to enhance convergence.

Preconditioning, postconditioning and their application to clinical cardiology.

PubMed

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.

TranAir: A full-potential, solution-adaptive, rectangular grid code for predicting subsonic, transonic, and supersonic flows about arbitrary configurations. Theory document

NASA Technical Reports Server (NTRS)

Johnson, F. T.; Samant, S. S.; Bieterman, M. B.; Melvin, R. G.; Young, D. P.; Bussoletti, J. E.; Hilmes, C. L.

1992-01-01

A new computer program, called TranAir, for analyzing complex configurations in transonic flow (with subsonic or supersonic freestream) was developed. This program provides accurate and efficient simulations of nonlinear aerodynamic flows about arbitrary geometries with the ease and flexibility of a typical panel method program. The numerical method implemented in TranAir is described. The method solves the full potential equation subject to a set of general boundary conditions and can handle regions with differing total pressure and temperature. The boundary value problem is discretized using the finite element method on a locally refined rectangular grid. The grid is automatically constructed by the code and is superimposed on the boundary described by networks of panels; thus no surface fitted grid generation is required. The nonlinear discrete system arising from the finite element method is solved using a preconditioned Krylov subspace method embedded in an inexact Newton method. The solution is obtained on a sequence of successively refined grids which are either constructed adaptively based on estimated solution errors or are predetermined based on user inputs. Many results obtained by using TranAir to analyze aerodynamic configurations are presented.

Linear solver performance in elastoplastic problem solution on GPU cluster

NASA Astrophysics Data System (ADS)

Khalevitsky, Yu. V.; Konovalov, A. V.; Burmasheva, N. V.; Partin, A. S.

2017-12-01

Applying the finite element method to severe plastic deformation problems involves solving linear equation systems. While the solution procedure is relatively hard to parallelize and computationally intensive by itself, a long series of large scale systems need to be solved for each problem. When dealing with fine computational meshes, such as in the simulations of three-dimensional metal matrix composite microvolume deformation, tens and hundreds of hours may be needed to complete the whole solution procedure, even using modern supercomputers. In general, one of the preconditioned Krylov subspace methods is used in a linear solver for such problems. The method convergence highly depends on the operator spectrum of a problem stiffness matrix. In order to choose the appropriate method, a series of computational experiments is used. Different methods may be preferable for different computational systems for the same problem. In this paper we present experimental data obtained by solving linear equation systems from an elastoplastic problem on a GPU cluster. The data can be used to substantiate the choice of the appropriate method for a linear solver to use in severe plastic deformation simulations.

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

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

Lin, P. T.; Shadid, J. N.; Hu, J. J.

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

DOE PAGES

Lin, P. T.; Shadid, J. N.; Hu, J. J.; ...

2017-11-06

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

Helmholtz and parabolic equation solutions to a benchmark problem in ocean acoustics.

PubMed

Larsson, Elisabeth; Abrahamsson, Leif

2003-05-01

The Helmholtz equation (HE) describes wave propagation in applications such as acoustics and electromagnetics. For realistic problems, solving the HE is often too expensive. Instead, approximations like the parabolic wave equation (PE) are used. For low-frequency shallow-water environments, one persistent problem is to assess the accuracy of the PE model. In this work, a recently developed HE solver that can handle a smoothly varying bathymetry, variable material properties, and layered materials, is used for an investigation of the errors in PE solutions. In the HE solver, a preconditioned Krylov subspace method is applied to the discretized equations. The preconditioner combines domain decomposition and fast transform techniques. A benchmark problem with upslope-downslope propagation over a penetrable lossy seamount is solved. The numerical experiments show that, for the same bathymetry, a soft and slow bottom gives very similar HE and PE solutions, whereas the PE model is far from accurate for a hard and fast bottom. A first attempt to estimate the error is made by computing the relative deviation from the energy balance for the PE solution. This measure gives an indication of the magnitude of the error, but cannot be used as a strict error bound.

Detecting coupled collective motions in protein by independent subspace analysis

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio

2010-11-01

Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.

Exploring the Role of TRPV and CGRP in Adenosine Preconditioning and Remote Hind Limb Preconditioning-Induced Cardioprotection in Rats.

PubMed

Singh, Amritpal; Randhawa, Puneet Kaur; Bali, Anjana; Singh, Nirmal; Jaggi, Amteshwar Singh

2017-04-01

The cardioprotective effects of remote hind limb preconditioning (RIPC) are well known, but mechanisms by which protection occurs still remain to be explored. Therefore, the present study was designed to investigate the role of TRPV and CGRP in adenosine and remote preconditioning-induced cardioprotection, using sumatriptan, a CGRP release inhibitor and ruthenium red, a TRPV inhibitor, in rats. For remote preconditioning, a pressure cuff was tied around the hind limb of the rat and was inflated with air up to 150 mmHg to produce ischemia in the hind limb and during reperfusion pressure was released. Four cycles of ischemia and reperfusion, each consisting of 5 min of inflation and 5 min of deflation of pressure cuff were used to produce remote limb preconditioning. An ex vivo Langendorff's isolated rat heart model was used to induce ischemia reperfusion injury by 30 min of global ischemia followed by 120 min of reperfusion. RIPC demonstrated a significant decrease in ischemia reperfusion-induced significant myocardial injury in terms of increase in LDH, CK, infarct size and decrease in LVDP, +dp/dt max and -dp/dt min . Moreover, pharmacological preconditioning with adenosine produced cardioprotective effects in a similar manner to RIPC. Pretreatment with sumatriptan, a CGRP release blocker, abolished RIPC and adenosine preconditioning-induced cardioprotective effects. Administration of ruthenium red, a TRPV inhibitor, also abolished adenosine preconditioning-induced cardioprotection. It may be proposed that the cardioprotective effects of adenosine and remote preconditioning are possibly mediated through activation of a TRPV channels and consequent, release of CGRP.

Visual exploration of high-dimensional data through subspace analysis and dynamic projections

DOE PAGES

Liu, S.; Wang, B.; Thiagarajan, J. J.; ...

2015-06-01

Here, we introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that createmore » smooth animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections

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

Liu, S.; Wang, B.; Thiagarajan, Jayaraman J.

2015-06-01

We introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that create smoothmore » animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

Variational second order density matrix study of F3-: importance of subspace constraints for size-consistency.

PubMed

van Aggelen, Helen; Verstichel, Brecht; Bultinck, Patrick; Van Neck, Dimitri; Ayers, Paul W; Cooper, David L

2011-02-07

Variational second order density matrix theory under "two-positivity" constraints tends to dissociate molecules into unphysical fractionally charged products with too low energies. We aim to construct a qualitatively correct potential energy surface for F(3)(-) by applying subspace energy constraints on mono- and diatomic subspaces of the molecular basis space. Monoatomic subspace constraints do not guarantee correct dissociation: the constraints are thus geometry dependent. Furthermore, the number of subspace constraints needed for correct dissociation does not grow linearly with the number of atoms. The subspace constraints do impose correct chemical properties in the dissociation limit and size-consistency, but the structure of the resulting second order density matrix method does not exactly correspond to a system of noninteracting units.

Low-Rank Tensor Subspace Learning for RGB-D Action Recognition.

PubMed

Jia, Chengcheng; Fu, Yun

2016-07-09

Since RGB-D action data inherently equip with extra depth information compared with RGB data, recently many works employ RGB-D data in a third-order tensor representation containing spatio-temporal structure to find a subspace for action recognition. However, there are two main challenges of these methods. First, the dimension of subspace is usually fixed manually. Second, preserving local information by finding intraclass and inter-class neighbors from a manifold is highly timeconsuming. In this paper, we learn a tensor subspace, whose dimension is learned automatically by low-rank learning, for RGB-D action recognition. Particularly, the tensor samples are factorized to obtain three Projection Matrices (PMs) by Tucker Decomposition, where all the PMs are performed by nuclear norm in a close-form to obtain the tensor ranks which are used as tensor subspace dimension. Additionally, we extract the discriminant and local information from a manifold using a graph constraint. This graph preserves the local knowledge inherently, which is faster than the previous way by calculating both the intra-class and inter-class neighbors of each sample. We evaluate the proposed method on four widely used RGB-D action datasets including MSRDailyActivity3D, MSRActionPairs, MSRActionPairs skeleton and UTKinect-Action3D datasets, and the experimental results show higher accuracy and efficiency of the proposed method.

Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.

PubMed

Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping

2017-10-06

Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.

Implicit preconditioned WENO scheme for steady viscous flow computation

NASA Astrophysics Data System (ADS)

Huang, Juan-Chen; Lin, Herng; Yang, Jaw-Yen

2009-02-01

A class of lower-upper symmetric Gauss-Seidel implicit weighted essentially nonoscillatory (WENO) schemes is developed for solving the preconditioned Navier-Stokes equations of primitive variables with Spalart-Allmaras one-equation turbulence model. The numerical flux of the present preconditioned WENO schemes consists of a first-order part and high-order part. For first-order part, we adopt the preconditioned Roe scheme and for the high-order part, we employ preconditioned WENO methods. For comparison purpose, a preconditioned TVD scheme is also given and tested. A time-derivative preconditioning algorithm is devised and a discriminant is devised for adjusting the preconditioning parameters at low Mach numbers and turning off the preconditioning at intermediate or high Mach numbers. The computations are performed for the two-dimensional lid driven cavity flow, low subsonic viscous flow over S809 airfoil, three-dimensional low speed viscous flow over 6:1 prolate spheroid, transonic flow over ONERA-M6 wing and hypersonic flow over HB-2 model. The solutions of the present algorithms are in good agreement with the experimental data. The application of the preconditioned WENO schemes to viscous flows at all speeds not only enhances the accuracy and robustness of resolving shock and discontinuities for supersonic flows, but also improves the accuracy of low Mach number flow with complicated smooth solution structures.

Exploratory High-Fidelity Aerostructural Optimization Using an Efficient Monolithic Solution Method

NASA Astrophysics Data System (ADS)

Zhang, Jenmy Zimi

This thesis is motivated by the desire to discover fuel efficient aircraft concepts through exploratory design. An optimization methodology based on tightly integrated high-fidelity aerostructural analysis is proposed, which has the flexibility, robustness, and efficiency to contribute to this goal. The present aerostructural optimization methodology uses an integrated geometry parameterization and mesh movement strategy, which was initially proposed for aerodynamic shape optimization. This integrated approach provides the optimizer with a large amount of geometric freedom for conducting exploratory design, while allowing for efficient and robust mesh movement in the presence of substantial shape changes. In extending this approach to aerostructural optimization, this thesis has addressed a number of important challenges. A structural mesh deformation strategy has been introduced to translate consistently the shape changes described by the geometry parameterization to the structural model. A three-field formulation of the discrete steady aerostructural residual couples the mesh movement equations with the three-dimensional Euler equations and a linear structural analysis. Gradients needed for optimization are computed with a three-field coupled adjoint approach. A number of investigations have been conducted to demonstrate the suitability and accuracy of the present methodology for use in aerostructural optimization involving substantial shape changes. Robustness and efficiency in the coupled solution algorithms is crucial to the success of an exploratory optimization. This thesis therefore also focuses on the design of an effective monolithic solution algorithm for the proposed methodology. This involves using a Newton-Krylov method for the aerostructural analysis and a preconditioned Krylov subspace method for the coupled adjoint solution. Several aspects of the monolithic solution method have been investigated. These include appropriate strategies for scaling

40 CFR 1065.518 - Engine preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Engine preconditioning. 1065.518... CONTROLS ENGINE-TESTING PROCEDURES Performing an Emission Test Over Specified Duty Cycles § 1065.518 Engine preconditioning. (a) This section applies for engines where measured emissions are affected by prior operation...

Parallel Preconditioning for CFD Problems on the CM-5

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Kremenetsky, Mark D.; Richardson, John; Lasinski, T. A. (Technical Monitor)

1994-01-01

Up to today, preconditioning methods on massively parallel systems have faced a major difficulty. The most successful preconditioning methods in terms of accelerating the convergence of the iterative solver such as incomplete LU factorizations are notoriously difficult to implement on parallel machines for two reasons: (1) the actual computation of the preconditioner is not very floating-point intensive, but requires a large amount of unstructured communication, and (2) the application of the preconditioning matrix in the iteration phase (i.e. triangular solves) are difficult to parallelize because of the recursive nature of the computation. Here we present a new approach to preconditioning for very large, sparse, unsymmetric, linear systems, which avoids both difficulties. We explicitly compute an approximate inverse to our original matrix. This new preconditioning matrix can be applied most efficiently for iterative methods on massively parallel machines, since the preconditioning phase involves only a matrix-vector multiplication, with possibly a dense matrix. Furthermore the actual computation of the preconditioning matrix has natural parallelism. For a problem of size n, the preconditioning matrix can be computed by solving n independent small least squares problems. The algorithm and its implementation on the Connection Machine CM-5 are discussed in detail and supported by extensive timings obtained from real problem data.

Dual signal subspace projection (DSSP): a novel algorithm for removing large interference in biomagnetic measurements

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Kawabata, Yuya; Ushio, Shuta; Sumiya, Satoshi; Kawabata, Shigenori; Adachi, Yoshiaki; Nagarajan, Srikantan S.

2016-06-01

Objective. In functional electrophysiological imaging, signals are often contaminated by interference that can be of considerable magnitude compared to the signals of interest. This paper proposes a novel algorithm for removing such interferences that does not require separate noise measurements. Approach. The algorithm is based on a dual definition of the signal subspace in the spatial- and time-domains. Since the algorithm makes use of this duality, it is named the dual signal subspace projection (DSSP). The DSSP algorithm first projects the columns of the measured data matrix onto the inside and outside of the spatial-domain signal subspace, creating a set of two preprocessed data matrices. The intersection of the row spans of these two matrices is estimated as the time-domain interference subspace. The original data matrix is projected onto the subspace that is orthogonal to this interference subspace. Main results. The DSSP algorithm is validated by using the computer simulation, and using two sets of real biomagnetic data: spinal cord evoked field data measured from a healthy volunteer and magnetoencephalography data from a patient with a vagus nerve stimulator. Significance. The proposed DSSP algorithm is effective for removing overlapped interference in a wide variety of biomagnetic measurements.

Application of high-order numerical schemes and Newton-Krylov method to two-phase drift-flux model

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

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

This study concerns the application and solver robustness of the Newton-Krylov method in solving two-phase flow drift-flux model problems using high-order numerical schemes. In our previous studies, the Newton-Krylov method has been proven as a promising solver for two-phase flow drift-flux model problems. However, these studies were limited to use first-order numerical schemes only. Moreover, the previous approach to treating the drift-flux closure correlations was later revealed to cause deteriorated solver convergence performance, when the mesh was highly refined, and also when higher-order numerical schemes were employed. In this study, a second-order spatial discretization scheme that has been tested withmore » two-fluid two-phase flow model was extended to solve drift-flux model problems. In order to improve solver robustness, and therefore efficiency, a new approach was proposed to treating the mean drift velocity of the gas phase as a primary nonlinear variable to the equation system. With this new approach, significant improvement in solver robustness was achieved. With highly refined mesh, the proposed treatment along with the Newton-Krylov solver were extensively tested with two-phase flow problems that cover a wide range of thermal-hydraulics conditions. Satisfactory convergence performances were observed for all test cases. Numerical verification was then performed in the form of mesh convergence studies, from which expected orders of accuracy were obtained for both the first-order and the second-order spatial discretization schemes. Finally, the drift-flux model, along with numerical methods presented, were validated with three sets of flow boiling experiments that cover different flow channel geometries (round tube, rectangular tube, and rod bundle), and a wide range of test conditions (pressure, mass flux, wall heat flux, inlet subcooling and outlet void fraction).« less

Application of high-order numerical schemes and Newton-Krylov method to two-phase drift-flux model

DOE PAGES

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2017-08-07

This study concerns the application and solver robustness of the Newton-Krylov method in solving two-phase flow drift-flux model problems using high-order numerical schemes. In our previous studies, the Newton-Krylov method has been proven as a promising solver for two-phase flow drift-flux model problems. However, these studies were limited to use first-order numerical schemes only. Moreover, the previous approach to treating the drift-flux closure correlations was later revealed to cause deteriorated solver convergence performance, when the mesh was highly refined, and also when higher-order numerical schemes were employed. In this study, a second-order spatial discretization scheme that has been tested withmore » two-fluid two-phase flow model was extended to solve drift-flux model problems. In order to improve solver robustness, and therefore efficiency, a new approach was proposed to treating the mean drift velocity of the gas phase as a primary nonlinear variable to the equation system. With this new approach, significant improvement in solver robustness was achieved. With highly refined mesh, the proposed treatment along with the Newton-Krylov solver were extensively tested with two-phase flow problems that cover a wide range of thermal-hydraulics conditions. Satisfactory convergence performances were observed for all test cases. Numerical verification was then performed in the form of mesh convergence studies, from which expected orders of accuracy were obtained for both the first-order and the second-order spatial discretization schemes. Finally, the drift-flux model, along with numerical methods presented, were validated with three sets of flow boiling experiments that cover different flow channel geometries (round tube, rectangular tube, and rod bundle), and a wide range of test conditions (pressure, mass flux, wall heat flux, inlet subcooling and outlet void fraction).« less

MGMRES: A generalization of GMRES for solving large sparse nonsymmetric linear systems

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

Young, D.M.; Chen, J.Y.

1994-12-31

The authors are concerned with the solution of the linear system (1): Au = b, where A is a real square nonsingular matrix which is large, sparse and non-symmetric. They consider the use of Krylov subspace methods. They first choose an initial approximation u{sup (0)} to the solution {bar u} = A{sup {minus}1}B of (1). They also choose an auxiliary matrix Z which is nonsingular. For n = 1,2,{hor_ellipsis} they determine u{sup (n)} such that u{sup (n)} {minus} u{sup (0)}{epsilon}K{sub n}(r{sup (0)},A) where K{sub n}(r{sup (0)},A) is the (Krylov) subspace spanned by the Krylov vectors r{sup (0)}, Ar{sup (0)}, {hor_ellipsis},more » A{sup n{minus}1}r{sup 0} and where r{sup (0)} = b{minus}Au{sup (0)}. If ZA is SPD they also require that (u{sup (n)}{minus}{bar u}, ZA(u{sup (n)}{minus}{bar u})) be minimized. If, on the other hand, ZA is not SPD, then they require that the Galerkin condition, (Zr{sup n}, v) = 0, be satisfied for all v{epsilon}K{sub n}(r{sup (0)}, A) where r{sup n} = b{minus}Au{sup (n)}. In this paper the authors consider a generalization of GMRES. This generalized method, which they refer to as `MGMRES`, is very similar to GMRES except that they let Z = A{sup T}Y where Y is a nonsingular matrix which is symmetric by not necessarily SPD.« less

Entanglement dynamics of coupled qubits and a semi-decoherence free subspace

NASA Astrophysics Data System (ADS)

Campagnano, Gabriele; Hamma, Alioscia; Weiss, Ulrich

2010-01-01

We study the entanglement dynamics and relaxation properties of a system of two interacting qubits in the cases of (I) two independent bosonic baths and (II) one common bath. We find that in the case (II) the existence of a decoherence-free subspace (DFS) makes entanglement dynamics very rich. We show that when the system is initially in a state with a component in the DFS the relaxation time is surprisingly long, showing the existence of semi-decoherence free subspaces.

Subspace in Linear Algebra: Investigating Students' Concept Images and Interactions with the Formal Definition

ERIC Educational Resources Information Center

Wawro, Megan; Sweeney, George F.; Rabin, Jeffrey M.

2011-01-01

This paper reports on a study investigating students' ways of conceptualizing key ideas in linear algebra, with the particular results presented here focusing on student interactions with the notion of subspace. In interviews conducted with eight undergraduates, we found students' initial descriptions of subspace often varied substantially from…

Condition Number Estimation of Preconditioned Matrices

PubMed Central

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager’s method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei’s matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei’s matrix, and matrices generated with the finite element method. PMID:25816331

Condition number estimation of preconditioned matrices.

PubMed

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager's method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei's matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei's matrix, and matrices generated with the finite element method.

Preconditioning and the limit to the incompressible flow equations

NASA Technical Reports Server (NTRS)

Turkel, E.; Fiterman, A.; Vanleer, B.

1993-01-01

The use of preconditioning methods to accelerate the convergence to a steady state for both the incompressible and compressible fluid dynamic equations are considered. The relation between them for both the continuous problem and the finite difference approximation is also considered. The analysis relies on the inviscid equations. The preconditioning consists of a matrix multiplying the time derivatives. Hence, the steady state of the preconditioned system is the same as the steady state of the original system. For finite difference methods the preconditioning can change and improve the steady state solutions. An application to flow around an airfoil is presented.

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

40 CFR 86.1232-96 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... awaiting testing, to prevent unusual loading of the canisters. During this time care must be taken to... vehicles with multiple canisters in a series configuration, the set of canisters must be preconditioned as... designed for vapor load or purge steps, the service port shall be used during testing to precondition the...

40 CFR 86.1232-96 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 20 2012-07-01 2012-07-01 false Vehicle preconditioning. 86.1232-96... (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED) Evaporative... Methanol-Fueled Heavy-Duty Vehicles § 86.1232-96 Vehicle preconditioning. (a) Fuel tank cap(s) of gasoline...

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Nonlinear Krylov and moving nodes in the method of lines

NASA Astrophysics Data System (ADS)

Miller, Keith

2005-11-01

We report on some successes and problem areas in the Method of Lines from our work with moving node finite element methods. First, we report on our "nonlinear Krylov accelerator" for the modified Newton's method on the nonlinear equations of our stiff ODE solver. Since 1990 it has been robust, simple, cheap, and automatic on all our moving node computations. We publicize further trials with it here because it should be of great general usefulness to all those solving evolutionary equations. Second, we discuss the need for reliable automatic choice of spatially variable time steps. Third, we discuss the need for robust and efficient iterative solvers for the difficult linearized equations (Jx=b) of our stiff ODE solver. Here, the 1997 thesis of Zulu Xaba has made significant progress.

A model reduction approach to numerical inversion for a parabolic partial differential equation

NASA Astrophysics Data System (ADS)

Borcea, Liliana; Druskin, Vladimir; Mamonov, Alexander V.; Zaslavsky, Mikhail

2014-12-01

We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss-Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments.

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

PubMed

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

2016-01-01

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

Incomplete Sparse Approximate Inverses for Parallel Preconditioning

DOE PAGES

Anzt, Hartwig; Huckle, Thomas K.; Bräckle, Jürgen; ...

2017-10-28

In this study, we propose a new preconditioning method that can be seen as a generalization of block-Jacobi methods, or as a simplification of the sparse approximate inverse (SAI) preconditioners. The “Incomplete Sparse Approximate Inverses” (ISAI) is in particular efficient in the solution of sparse triangular linear systems of equations. Those arise, for example, in the context of incomplete factorization preconditioning. ISAI preconditioners can be generated via an algorithm providing fine-grained parallelism, which makes them attractive for hardware with a high concurrency level. Finally, in a study covering a large number of matrices, we identify the ISAI preconditioner as anmore » attractive alternative to exact triangular solves in the context of incomplete factorization preconditioning.« less

Implementation of Preconditioned Dual-Time Procedures in OVERFLOW

NASA Technical Reports Server (NTRS)

Pandya, Shishir A.; Venkateswaran, Sankaran; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)

2003-01-01

Preconditioning methods have become the method of choice for the solution of flowfields involving the simultaneous presence of low Mach and transonic regions. It is well known that these methods are important for insuring accurate numerical discretization as well as convergence efficiency over various operating conditions such as low Mach number, low Reynolds number and high Strouhal numbers. For unsteady problems, the preconditioning is introduced within a dual-time framework wherein the physical time-derivatives are used to march the unsteady equations and the preconditioned time-derivatives are used for purposes of numerical discretization and iterative solution. In this paper, we describe the implementation of the preconditioned dual-time methodology in the OVERFLOW code. To demonstrate the performance of the method, we employ both simple and practical unsteady flowfields, including vortex propagation in a low Mach number flow, flowfield of an impulsively started plate (Stokes' first problem) arid a cylindrical jet in a low Mach number crossflow with ground effect. All the results demonstrate that the preconditioning algorithm is responsible for improvements to both numerical accuracy and convergence efficiency and, thereby, enables low Mach number unsteady computations to be performed at a fraction of the cost of traditional time-marching methods.

Subspace-based analysis of the ERT inverse problem

NASA Astrophysics Data System (ADS)

Ben Hadj Miled, Mohamed Khames; Miller, Eric L.

2004-05-01

In a previous work, we proposed a source-type formulation to the electrical resistance tomography (ERT) problem. Specifically, we showed that inhomogeneities in the medium can be viewed as secondary sources embedded in the homogeneous background medium and located at positions associated with variation in electrical conductivity. Assuming a piecewise constant conductivity distribution, the support of equivalent sources is equal to the boundary of the inhomogeneity. The estimation of the anomaly shape takes the form of an inverse source-type problem. In this paper, we explore the use of subspace methods to localize the secondary equivalent sources associated with discontinuities in the conductivity distribution. Our first alternative is the multiple signal classification (MUSIC) algorithm which is commonly used in the localization of multiple sources. The idea is to project a finite collection of plausible pole (or dipole) sources onto an estimated signal subspace and select those with largest correlations. In ERT, secondary sources are excited simultaneously but in different ways, i.e. with distinct amplitude patterns, depending on the locations and amplitudes of primary sources. If the number of receivers is "large enough", different source configurations can lead to a set of observation vectors that span the data subspace. However, since sources that are spatially close to each other have highly correlated signatures, seperation of such signals becomes very difficult in the presence of noise. To overcome this problem we consider iterative MUSIC algorithms like R-MUSIC and RAP-MUSIC. These recursive algorithms pose a computational burden as they require multiple large combinatorial searches. Results obtained with these algorithms using simulated data of different conductivity patterns are presented.

Ischemic preconditioning protects against gap junctional uncoupling in cardiac myofibroblasts.

PubMed

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.

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

Lin, Paul T.; Shadid, John N.; Tsuji, Paul H.

Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered inmore » an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.« less

Numerical methods in Markov chain modeling

NASA Technical Reports Server (NTRS)

Philippe, Bernard; Saad, Youcef; Stewart, William J.

1989-01-01

Several methods for computing stationary probability distributions of Markov chains are described and compared. The main linear algebra problem consists of computing an eigenvector of a sparse, usually nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem of solving a homogeneous singular linear system. Several methods based on combinations of Krylov subspace techniques are presented. The performance of these methods on some realistic problems are compared.

Preconditioning for traumatic brain injury

PubMed Central

Yokobori, Shoji; Mazzeo, Anna T; Hosein, Khadil; Gajavelli, Shyam; Dietrich, W. Dalton; Bullock, M. Ross

2016-01-01

Traumatic brain injury (TBI) treatment is now focused on the prevention of primary injury and reduction of secondary injury. However, no single effective treatment is available as yet for the mitigation of traumatic brain damage in humans. Both chemical and environmental stresses applied before injury, have been shown to induce consequent protection against post-TBI neuronal death. This concept termed “preconditioning” is achieved by exposure to different pre-injury stressors, to achieve the induction of “tolerance” to the effect of the TBI. However, the precise mechanisms underlying this “tolerance” phenomenon are not fully understood in TBI, and therefore even less information is available about possible indications in clinical TBI patients. In this review we will summarize TBI pathophysiology, and discuss existing animal studies demonstrating the efficacy of preconditioning in diffuse and focal type of TBI. We will also review other non-TBI preconditionng studies, including ischemic, environmental, and chemical preconditioning, which maybe relevant to TBI. To date, no clinical studies exist in this field, and we speculate on possible futureclinical situation, in which pre-TBI preconditioning could be considered. PMID:24323189

No influence of ischemic preconditioning on running economy.

PubMed

Kaur, Gungeet; Binger, Megan; Evans, Claire; Trachte, Tiffany; Van Guilder, Gary P

2017-02-01

Many of the potential performance-enhancing properties of ischemic preconditioning suggest that the oxygen cost for a given endurance exercise workload will be reduced, thereby improving the economy of locomotion. The aim of this study was to identify whether ischemic preconditioning improves exercise economy in recreational runners. A randomized sham-controlled crossover study was employed in which 18 adults (age 27 ± 7 years; BMI 24.6 ± 3 kg/m 2 ) completed two, incremental submaximal (65-85% VO 2max ) treadmill running protocols (3 × 5 min stages from 7.2-14.5 km/h) coupled with indirect calorimetry to assess running economy following ischemic preconditioning (3 × 5 min bilateral upper thigh ischemia) and sham control. Running economy was expressed as mlO 2 /kg/km and as the energy in kilocalories required to cover 1 km of horizontal distance (kcal/kg/km). Ischemic preconditioning did not influence steady-state heart rate, oxygen consumption, minute ventilation, respiratory exchange ratio, energy expenditure, and blood lactate. Likewise, running economy was similar (P = 0.647) between the sham (from 201.6 ± 17.7 to 204.0 ± 16.1 mlO 2 /kg/km) and ischemic preconditioning trials (from 202.8 ± 16.2 to 203.1 ± 15.6 mlO 2 /kg/km). There was no influence (P = 0.21) of ischemic preconditioning on running economy expressed as the caloric unit cost (from 0.96 ± 0.12 to 1.01 ± 0.11 kcal/kg/km) compared with sham (from 1.00 ± 0.10 to 1.00 ± 0.08 kcal/kg/km). The properties of ischemic preconditioning thought to affect exercise performance at vigorous to severe exercise intensities, which generate more extensive physiological challenge, are ineffective at submaximal workloads and, therefore, do not change running economy.

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

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

PubMed Central

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

2016-01-01

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

Improved Detection of Local Earthquakes in the Vienna Basin (Austria), using Subspace Detectors

NASA Astrophysics Data System (ADS)

Apoloner, Maria-Theresia; Caffagni, Enrico; Bokelmann, Götz

2016-04-01

The Vienna Basin in Eastern Austria is densely populated and highly-developed; it is also a region of low to moderate seismicity, yet the seismological network coverage is relatively sparse. This demands improving our capability of earthquake detection by testing new methods, enlarging the existing local earthquake catalogue. This contributes to imaging tectonic fault zones for better understanding seismic hazard, also through improved earthquake statistics (b-value, magnitude of completeness). Detection of low-magnitude earthquakes or events for which the highest amplitudes slightly exceed the signal-to-noise-ratio (SNR), may be possible by using standard methods like the short-term over long-term average (STA/LTA). However, due to sparse network coverage and high background noise, such a technique may not detect all potentially recoverable events. Yet, earthquakes originating from the same source region and relatively close to each other, should be characterized by similarity in seismic waveforms, at a given station. Therefore, waveform similarity can be exploited by using specific techniques such as correlation-template based (also known as matched filtering) or subspace detection methods (based on the subspace theory). Matching techniques basically require a reference or template event, usually characterized by high waveform coherence in the array receivers, and high SNR, which is cross-correlated with the continuous data. Instead, subspace detection methods overcome in principle the necessity of defining template events as single events, but use a subspace extracted from multiple events. This approach theoretically should be more robust in detecting signals that exhibit a strong variability (e.g. because of source or magnitude). In this study we scan the continuous data recorded in the Vienna Basin with a subspace detector to identify additional events. This will allow us to estimate the increase of the seismicity rate in the local earthquake catalogue

Conditioned invariant subspaces, disturbance decoupling and solutions of rational matrix equations

NASA Technical Reports Server (NTRS)

Li, Z.; Sastry, S. S.

1986-01-01

Conditioned invariant subspaces are introduced both in terms of output injection and in terms of state estimation. Various properties of these subspaces are explored and the problem of disturbance decoupling by output injection (OIP) is defined. It is then shown that OIP is equivalent to the problem of disturbance decoupled estimation as introduced in Willems (1982) and Willems and Commault (1980). Both solvability conditions and a description of solutions for a class of rational matrix equations of the form X(s)M(s) = Q(s) on several ways are given in state-space form. Finally, the problem of output stabilization with respect to a disturbance is briefly addressed.

Matrix preconditioning: a robust operation for optical linear algebra processors.

PubMed

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.

Active Subspace Methods for Data-Intensive Inverse Problems

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

Wang, Qiqi

2017-04-27

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

Metastable decoherence-free subspaces and electromagnetically induced transparency in interacting many-body systems

NASA Astrophysics Data System (ADS)

Macieszczak, Katarzyna; Zhou, YanLi; Hofferberth, Sebastian; Garrahan, Juan P.; Li, Weibin; Lesanovsky, Igor

2017-10-01

We investigate the dynamics of a generic interacting many-body system under conditions of electromagnetically induced transparency (EIT). This problem is of current relevance due to its connection to nonlinear optical media realized by Rydberg atoms. In an interacting system the structure of the dynamics and the approach to the stationary state becomes far more complex than in the case of conventional EIT. In particular, we discuss the emergence of a metastable decoherence-free subspace, whose dimension for a single Rydberg excitation grows linearly in the number of atoms. On approach to stationarity this leads to a slow dynamics, which renders the typical assumption of fast relaxation invalid. We derive analytically the effective nonequilibrium dynamics in the decoherence-free subspace, which features coherent and dissipative two-body interactions. We discuss the use of this scenario for the preparation of collective entangled dark states and the realization of general unitary dynamics within the spin-wave subspace.

The Krylov accelerated SIMPLE(R) method for flow problems in industrial furnaces

NASA Astrophysics Data System (ADS)

Vuik, C.; Saghir, A.; Boerstoel, G. P.

2000-08-01

Numerical modeling of the melting and combustion process is an important tool in gaining understanding of the physical and chemical phenomena that occur in a gas- or oil-fired glass-melting furnace. The incompressible Navier-Stokes equations are used to model the gas flow in the furnace. The discrete Navier-Stokes equations are solved by the SIMPLE(R) pressure-correction method. In these applications, many SIMPLE(R) iterations are necessary to obtain an accurate solution. In this paper, Krylov accelerated versions are proposed: GCR-SIMPLE(R). The properties of these methods are investigated for a simple two-dimensional flow. Thereafter, the efficiencies of the methods are compared for three-dimensional flows in industrial glass-melting furnaces. Copyright

A Newton-Krylov solver for fast spin-up of online ocean tracers

NASA Astrophysics Data System (ADS)

Lindsay, Keith

2017-01-01

We present a Newton-Krylov based solver to efficiently spin up tracers in an online ocean model. We demonstrate that the solver converges, that tracer simulations initialized with the solution from the solver have small drift, and that the solver takes orders of magnitude less computational time than the brute force spin-up approach. To demonstrate the application of the solver, we use it to efficiently spin up the tracer ideal age with respect to the circulation from different time intervals in a long physics run. We then evaluate how the spun-up ideal age tracer depends on the duration of the physics run, i.e., on how equilibrated the circulation is.

The importance of Leonhard Euler's discoveries in the field of shipbuilding for the scientific evolution of academician A. N. Krylov

NASA Astrophysics Data System (ADS)

Sharkov, N. A.; Sharkova, O. A.

2018-05-01

The paper identifies the importance of the Leonhard Euler's discoveries in the field of shipbuilding for the scientific evolution of academician A. N. Krylov and for the modern knowledge in survivability and safety of ships. The works by Leonard Euler "Marine Science" and "The Moon Motion New Theory" are discussed.

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

DOE PAGES

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.; ...

2017-10-16

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

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

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

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

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

NASA Astrophysics Data System (ADS)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE PAGES

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Pre-test procedures and preconditioning... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

Preconditioning Provides Neuroprotection in Models of CNS Disease: Paradigms and Clinical Significance

PubMed Central

Stetler, R. Anne; Leak, Rehana K.; Gan, Yu; Li, Peiying; Hu, Xiaoming; Jing, Zheng; Chen, Jun; Zigmond, Michael J.; Gao, Yanqin

2014-01-01

Preconditioning is a phenomenon in which brief episodes of a sublethal insult induce robust protection against subsequent lethal injuries. Preconditioning has been observed in multiple organisms and can occur in the brain as well as other tissues. Extensive animal studies suggest that the brain can be preconditioned to resist acute injuries, such as ischemic stroke, neonatal hypoxia/ischemia, trauma, and agents that are used in models of neurodegenerative diseases, such as Parkinson’s disease and Alzheimer’s disease. Effective preconditioning stimuli are numerous and diverse, ranging from transient ischemia, hypoxia, hyperbaric oxygen, hypothermia and hyperthermia, to exposure to neurotoxins and pharmacological agents. The phenomenon of “cross-tolerance,” in which a sublethal stress protects against a different type of injury, suggests that different preconditioning stimuli may confer protection against a wide range of injuries. Research conducted over the past few decades indicates that brain preconditioning is complex, involving multiple effectors such as metabolic inhibition, activation of extra- and intracellular defense mechanisms, a shift in the neuronal excitatory/inhibitory balance, and reduction in inflammatory sequelae. An improved understanding of brain preconditioning should help us identify innovative therapeutic strategies that prevent or at least reduce neuronal damage in susceptible patients. In this review, we focus on the experimental evidence of preconditioning in the brain and systematically survey the models used to develop paradigms for neuroprotection, and then discuss the clinical potential of brain preconditioning. In a subsequent components of this two-part series, we will discuss the cellular and molecular events that are likely to underlie these phenomena. PMID:24389580

Super-low dose endotoxin pre-conditioning exacerbates sepsis mortality.

PubMed

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.

Effects of exercise preconditioning on intestinal ischemia-reperfusion injury.

PubMed

Gokbel, H; Oz, M; Okudan, N; Belviranli, M; Esen, H

2014-01-01

To investigate the effects of exercise preconditioning on oxidative injury in the intestinal tissue of rats. Sixty male Wistar rats were randomly divided into six groups as sham (n = 10), ischemia-reperfusion (n = 10), exercise (n = 10), exercise plus ischemia-reperfusion (n = 10), ischemic preconditioning (n = 10), and ischemic preconditioning plus ischemia-reperfusion groups (n = 10). Tissue levels of malondialdehyde and activities of myeloperoxidase and superoxide dismutase, and serum levels of tumor necrosis factor-alpha and interleukin-6 were measured. Intestinal tissue histopathology was also evaluated by light microscopy. Tumor necrosis factor-alpha concentrations significantly decreased in the exercise group compared to the sham group (p < 0.05). Myeloperoxidase activity significantly increased and superoxide dismutase activity significantly decreased in ischemia-reperfusion group compared to the sham group (p < 0.05). Superoxide dismutase activity in the ischemic preconditioning and ischemic preconditioning plus ischemia-reperfusion groups were significantly higher compared to the ischemia-reperfusion and exercise groups (p < 0.05). Histopathologically, intestinal injury significantly attenuated in the exercise plus ischemia-reperfusion group compared to the ischemia-reperfusion group. The results of the present study indicate that exercise training seems to have a protective role against intestinal ischemia-reperfusion injury (Tab. 3, Fig. 1, Ref. 35).

Analysis of physics-based preconditioning for single-phase subchannel equations

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

Hansel, J. E.; Ragusa, J. C.; Allu, S.

2013-07-01

The (single-phase) subchannel approximations are used throughout nuclear engineering to provide an efficient flow simulation because the computational burden is much smaller than for computational fluid dynamics (CFD) simulations, and empirical relations have been developed and validated to provide accurate solutions in appropriate flow regimes. Here, the subchannel equations have been recast in a residual form suitable for a multi-physics framework. The Eigen spectrum of the Jacobian matrix, along with several potential physics-based preconditioning approaches, are evaluated, and the the potential for improved convergence from preconditioning is assessed. The physics-based preconditioner options include several forms of reduced equations that decouplemore » the subchannels by neglecting crossflow, conduction, and/or both turbulent momentum and energy exchange between subchannels. Eigen-scopy analysis shows that preconditioning moves clusters of eigenvalues away from zero and toward one. A test problem is run with and without preconditioning. Without preconditioning, the solution failed to converge using GMRES, but application of any of the preconditioners allowed the solution to converge. (authors)« less

A preconditioned formulation of the Cauchy-Riemann equations

NASA Technical Reports Server (NTRS)

Phillips, T. N.

1983-01-01

A preconditioning of the Cauchy-Riemann equations which results in a second-order system is described. This system is shown to have a unique solution if the boundary conditions are chosen carefully. This choice of boundary condition enables the solution of the first-order system to be retrieved. A numerical solution of the preconditioned equations is obtained by the multigrid method.

N-Screen Aware Multicriteria Hybrid Recommender System Using Weight Based Subspace Clustering

PubMed Central

Ullah, Farman; Lee, Sungchang

2014-01-01

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements. PMID:25152921

The Galvanotactic Migration of Keratinocytes is Enhanced by Hypoxic Preconditioning

PubMed Central

Guo, Xiaowei; Jiang, Xupin; Ren, Xi; Sun, Huanbo; Zhang, Dongxia; Zhang, Qiong; Zhang, Jiaping; Huang, Yuesheng

2015-01-01

The endogenous electric field (EF)-directed migration of keratinocytes (galvanotaxis) into wounds is an essential step in wound re-epithelialization. Hypoxia, which occurs immediately after injury, acts as an early stimulus to initiate the healing process; however, the mechanisms for this effect, remain elusive. We show here that the galvanotactic migration of keratinocytes was enhanced by hypoxia preconditioning as a result of the increased directionality rather than the increased motility of keratinocytes. This enhancement was both oxygen tension- and preconditioning time-dependent, with the maximum effects achieved using 2% O2 preconditioning for 6 hours. Hypoxic preconditioning (2% O2, 6 hours) decreased the threshold voltage of galvanotaxis to < 25 mV/mm, whereas this value was between 25 and 50 mV/mm in the normal culture control. In a scratch-wound monolayer assay in which the applied EF was in the default healing direction, hypoxic preconditioning accelerated healing by 1.38-fold compared with the control conditions. Scavenging of the induced ROS by N-acetylcysteine (NAC) abolished the enhanced galvanotaxis and the accelerated healing by hypoxic preconditioning. Our data demonstrate a novel and unsuspected role of hypoxia in supporting keratinocyte galvanotaxis. Enhancing the galvanotactic response of cells might therefore be a clinically attractive approach to induce improved wound healing. PMID:25988491

40 CFR 85.2218 - Preconditioned idle test-EPA 91.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 18 2011-07-01 2011-07-01 false Preconditioned idle test-EPA 91. 85.2218 Section 85.2218 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... Tests § 85.2218 Preconditioned idle test—EPA 91. (a) General requirements—(1) Exhaust gas sampling...

Roles of thioredoxin in nitric oxide-dependent preconditioning-induced tolerance against MPTP neurotoxin

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

Chiueh, C.C.; Andoh, Tsugunobu; Chock, P. Boon

2005-09-01

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 {center_dot}NO-cGMP-PKG (protein kinase G) may mediate preconditioning phenomenon. We developed a human SH-SY5Y cell model for investigating {sup {center_dot}}NO-mediated signaling pathway, gene regulation, and protein expression following a sublethal preconditioning stress caused by a brief 2-h serum deprivation.more » 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{sup +}). Both sublethal and lethal oxidative stress caused by serum withdrawal increased neuronal nitric oxide synthase (nNOS/NOS1) expression and {sup {center_dot}}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{sup +}, which was blocked by Trx mRNA antisense oligonucleotide and Trx reductase inhibitor. It is concluded that Trx plays a pivotal role in {sup {center_dot}}NO-dependent preconditioning hormesis

40 CFR 85.2218 - Preconditioned idle test-EPA 91.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 19 2012-07-01 2012-07-01 false Preconditioned idle test-EPA 91. 85... Tests § 85.2218 Preconditioned idle test—EPA 91. (a) General requirements—(1) Exhaust gas sampling algorithm. The analysis of exhaust gas concentrations begins ten seconds after the applicable test mode...

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2004-10-01

Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

PIXIE3D: A Parallel, Implicit, eXtended MHD 3D Code.

NASA Astrophysics Data System (ADS)

Chacon, L.; Knoll, D. A.

2004-11-01

We report on the development of PIXIE3D, a 3D parallel, fully implicit Newton-Krylov extended primitive-variable MHD code in general curvilinear geometry. PIXIE3D employs a second-order, finite-volume-based spatial discretization that satisfies remarkable properties such as being conservative, solenoidal in the magnetic field, non-dissipative, and stable in the absence of physical dissipation.(L. Chacón , phComput. Phys. Comm.) submitted (2004) PIXIE3D employs fully-implicit Newton-Krylov methods for the time advance. Currently, first and second-order implicit schemes are available, although higher-order temporal implicit schemes can be effortlessly implemented within the Newton-Krylov framework. A successful, scalable, MG physics-based preconditioning strategy, similar in concept to previous 2D MHD efforts,(L. Chacón et al., phJ. Comput. Phys). 178 (1), 15- 36 (2002); phJ. Comput. Phys., 188 (2), 573-592 (2003) has been developed. We are currently in the process of parallelizing the code using the PETSc library, and a Newton-Krylov-Schwarz approach for the parallel treatment of the preconditioner. In this poster, we will report on both the serial and parallel performance of PIXIE3D, focusing primarily on scalability and CPU speedup vs. an explicit approach.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well

Fetal asphyctic preconditioning alters the transcriptional response to perinatal asphyxia.

PubMed

Cox-Limpens, Kimberly E M; Vles, Johan S H; LA van den Hove, Daniel; Zimmermann, Luc J I; Gavilanes, Antonio W D

2014-05-29

Genomic reprogramming is thought to be, at least in part, responsible for the protective effect of brain preconditioning. Unraveling mechanisms of this endogenous neuroprotection, activated by preconditioning, is an important step towards new clinical strategies for treating asphyctic neonates.Therefore, we investigated whole-genome transcriptional changes in the brain of rats which underwent perinatal asphyxia (PA), and rats where PA was preceded by fetal asphyctic preconditioning (FAPA). Offspring were sacrificed 6 h and 96 h after birth, and whole-genome transcription was investigated using the Affymetrix Gene1.0ST chip. Microarray data were analyzed with the Bioconductor Limma package. In addition to univariate analysis, we performed Gene Set Enrichment Analysis (GSEA) in order to derive results with maximum biological relevance. We observed minimal, 25% or less, overlap of differentially regulated transcripts across different experimental groups which leads us to conclude that the transcriptional phenotype of these groups is largely unique. In both the PA and FAPA group we observe an upregulation of transcripts involved in cellular stress. Contrastingly, transcripts with a function in the cell nucleus were mostly downregulated in PA animals, while we see considerable upregulation in the FAPA group. Furthermore, we observed that histone deacetylases (HDACs) are exclusively regulated in FAPA animals. This study is the first to investigate whole-genome transcription in the neonatal brain after PA alone, and after perinatal asphyxia preceded by preconditioning (FAPA). We describe several genes/pathways, such as ubiquitination and proteolysis, which were not previously linked to preconditioning-induced neuroprotection. Furthermore, we observed that the majority of upregulated genes in preconditioned animals have a function in the cell nucleus, including several epigenetic players such as HDACs, which suggests that epigenetic mechanisms are likely to play a role in

Fetal asphyctic preconditioning alters the transcriptional response to perinatal asphyxia

PubMed Central

2014-01-01

Background Genomic reprogramming is thought to be, at least in part, responsible for the protective effect of brain preconditioning. Unraveling mechanisms of this endogenous neuroprotection, activated by preconditioning, is an important step towards new clinical strategies for treating asphyctic neonates. Therefore, we investigated whole-genome transcriptional changes in the brain of rats which underwent perinatal asphyxia (PA), and rats where PA was preceded by fetal asphyctic preconditioning (FAPA). Offspring were sacrificed 6 h and 96 h after birth, and whole-genome transcription was investigated using the Affymetrix Gene1.0ST chip. Microarray data were analyzed with the Bioconductor Limma package. In addition to univariate analysis, we performed Gene Set Enrichment Analysis (GSEA) in order to derive results with maximum biological relevance. Results We observed minimal, 25% or less, overlap of differentially regulated transcripts across different experimental groups which leads us to conclude that the transcriptional phenotype of these groups is largely unique. In both the PA and FAPA group we observe an upregulation of transcripts involved in cellular stress. Contrastingly, transcripts with a function in the cell nucleus were mostly downregulated in PA animals, while we see considerable upregulation in the FAPA group. Furthermore, we observed that histone deacetylases (HDACs) are exclusively regulated in FAPA animals. Conclusions This study is the first to investigate whole-genome transcription in the neonatal brain after PA alone, and after perinatal asphyxia preceded by preconditioning (FAPA). We describe several genes/pathways, such as ubiquitination and proteolysis, which were not previously linked to preconditioning-induced neuroprotection. Furthermore, we observed that the majority of upregulated genes in preconditioned animals have a function in the cell nucleus, including several epigenetic players such as HDACs, which suggests that epigenetic

Hypoxic preconditioning facilitates acclimatization to hypobaric hypoxia in rat heart.

PubMed

Singh, Mrinalini; Shukla, Dhananjay; Thomas, Pauline; Saxena, Saurabh; Bansal, Anju

2010-12-01

Acute systemic hypoxia induces delayed cardioprotection against ischaemia-reperfusion injury in the heart. As cobalt chloride (CoCl₂) is known to elicit hypoxia-like responses, it was hypothesized that this chemical would mimic the preconditioning effect and facilitate acclimatization to hypobaric hypoxia in rat heart. Male Sprague-Dawley rats treated with distilled water or cobalt chloride (12.5 mg Co/kg for 7 days) were exposed to simulated altitude at 7622 m for different time periods (1, 2, 3 and 5 days). Hypoxic preconditioning with cobalt appreciably attenuated hypobaric hypoxia-induced oxidative damage as observed by a decrease in free radical (reactive oxygen species) generation, oxidation of lipids and proteins. Interestingly, the observed effect was due to increased expression of the antioxidant proteins hemeoxygenase and metallothionein, as no significant change was observed in antioxidant enzyme activity. Hypoxic preconditioning with cobalt increased hypoxia-inducible factor 1α (HIF-1α) expression as well as HIF-1 DNA binding activity, which further resulted in increased expression of HIF-1 regulated genes such as erythropoietin, vascular endothelial growth factor and glucose transporter. A significant decrease was observed in lactate dehydrogenase activity and lactate levels in the heart of preconditioned animals compared with non-preconditioned animals exposed to hypoxia. The results showed that hypoxic preconditioning with cobalt induces acclimatization by up-regulation of hemeoxygenase 1 and metallothionein 1 via HIF-1 stabilization. © 2010 The Authors. JPP © 2010 Royal Pharmaceutical Society of Great Britain.

Efficient Solution of Three-Dimensional Problems of Acoustic and Electromagnetic Scattering by Open Surfaces

NASA Technical Reports Server (NTRS)

Turc, Catalin; Anand, Akash; Bruno, Oscar; Chaubell, Julian

2011-01-01

We present a computational methodology (a novel Nystrom approach based on use of a non-overlapping patch technique and Chebyshev discretizations) for efficient solution of problems of acoustic and electromagnetic scattering by open surfaces. Our integral equation formulations (1) Incorporate, as ansatz, the singular nature of open-surface integral-equation solutions, and (2) For the Electric Field Integral Equation (EFIE), use analytical regularizes that effectively reduce the number of iterations required by iterative linear-algebra solution based on Krylov-subspace iterative solvers.

A sub-space greedy search method for efficient Bayesian Network inference.

PubMed

Zhang, Qing; Cao, Yong; Li, Yong; Zhu, Yanming; Sun, Samuel S M; Guo, Dianjing

2011-09-01

Bayesian network (BN) has been successfully used to infer the regulatory relationships of genes from microarray dataset. However, one major limitation of BN approach is the computational cost because the calculation time grows more than exponentially with the dimension of the dataset. In this paper, we propose a sub-space greedy search method for efficient Bayesian Network inference. Particularly, this method limits the greedy search space by only selecting gene pairs with higher partial correlation coefficients. Using both synthetic and real data, we demonstrate that the proposed method achieved comparable results with standard greedy search method yet saved ∼50% of the computational time. We believe that sub-space search method can be widely used for efficient BN inference in systems biology. Copyright © 2011 Elsevier Ltd. All rights reserved.

Preconditioning the Helmholtz Equation for Rigid Ducts

NASA Technical Reports Server (NTRS)

Baumeister, Kenneth J.; Kreider, Kevin L.

1998-01-01

An innovative hyperbolic preconditioning technique is developed for the numerical solution of the Helmholtz equation which governs acoustic propagation in ducts. Two pseudo-time parameters are used to produce an explicit iterative finite difference scheme. This scheme eliminates the large matrix storage requirements normally associated with numerical solutions to the Helmholtz equation. The solution procedure is very fast when compared to other transient and steady methods. Optimization and an error analysis of the preconditioning factors are present. For validation, the method is applied to sound propagation in a 2D semi-infinite hard wall duct.

Preconditioning for the Navier-Stokes equations with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Godfrey, Andrew G.

1993-01-01

The extension of Van Leer's preconditioning procedure to generalized finite-rate chemistry is discussed. Application to viscous flow is begun with the proper preconditioning matrix for the one-dimensional Navier-Stokes equations. Eigenvalue stiffness is resolved and convergence-rate acceleration is demonstrated over the entire Mach-number range from nearly stagnant flow to hypersonic. Specific benefits are realized at the low and transonic flow speeds typical of complete propulsion-system simulations. The extended preconditioning matrix necessarily accounts for both thermal and chemical nonequilibrium. Numerical analysis reveals the possible theoretical improvements from using a preconditioner for all Mach number regimes. Numerical results confirm the expectations from the numerical analysis. Representative test cases include flows with previously troublesome embedded high-condition-number areas. Van Leer, Lee, and Roe recently developed an optimal, analytic preconditioning technique to reduce eigenvalue stiffness over the full Mach-number range. By multiplying the flux-balance residual with the preconditioning matrix, the acoustic wave speeds are scaled so that all waves propagate at the same rate, an essential property to eliminate inherent eigenvalue stiffness. This session discusses a synthesis of the thermochemical nonequilibrium flux-splitting developed by Grossman and Cinnella and the characteristic wave preconditioning of Van Leer into a powerful tool for implicitly solving two and three-dimensional flows with generalized finite-rate chemistry. For finite-rate chemistry, the state vector of unknowns is variable in length. Therefore, the preconditioning matrix extended to generalized finite-rate chemistry must accommodate a flexible system of moving waves. Fortunately, no new kind of wave appears in the system. The only existing waves are entropy and vorticity waves, which move with the fluid, and acoustic waves, which propagate in Mach number dependent

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

Aliaga, José I., E-mail: aliaga@uji.es; Alonso, Pedro; Badía, José M.

We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousandsmore » degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.« less

Polarimetric subspace target detector for SAR data based on the Huynen dihedral model

NASA Astrophysics Data System (ADS)

Larson, Victor J.; Novak, Leslie M.

1995-06-01

Two new polarimetric subspace target detectors are developed based on a dihedral signal model for bright peaks within a spatially extended target signature. The first is a coherent dihedral target detector based on the exact Huynen model for a dihedral. The second is a noncoherent dihedral target detector based on the Huynen model with an extra unknown phase term. Expressions for these polarimetric subspace target detectors are developed for both additive Gaussian clutter and more general additive spherically invariant random vector clutter including the K-distribution. For the case of Gaussian clutter with unknown clutter parameters, constant false alarm rate implementations of these polarimetric subspace target detectors are developed. The performance of these dihedral detectors is demonstrated with real millimeter-wave fully polarimetric SAR data. The coherent dihedral detector which is developed with a more accurate description of a dihedral offers no performance advantage over the noncoherent dihedral detector which is computationally more attractive. The dihedral detectors do a better job of separating a set of tactical military targets from natural clutter compared to a detector that assumes no knowledge about the polarimetric structure of the target signal.

Slope angle estimation method based on sparse subspace clustering for probe safe landing

NASA Astrophysics Data System (ADS)

Li, Haibo; Cao, Yunfeng; Ding, Meng; Zhuang, Likui

2018-06-01

To avoid planetary probes landing on steep slopes where they may slip or tip over, a new method of slope angle estimation based on sparse subspace clustering is proposed to improve accuracy. First, a coordinate system is defined and established to describe the measured data of light detection and ranging (LIDAR). Second, this data is processed and expressed with a sparse representation. Third, on this basis, the data is made to cluster to determine which subspace it belongs to. Fourth, eliminating outliers in subspace, the correct data points are used for the fitting planes. Finally, the vectors normal to the planes are obtained using the plane model, and the angle between the normal vectors is obtained through calculation. Based on the geometric relationship, this angle is equal in value to the slope angle. The proposed method was tested in a series of experiments. The experimental results show that this method can effectively estimate the slope angle, can overcome the influence of noise and obtain an exact slope angle. Compared with other methods, this method can minimize the measuring errors and further improve the estimation accuracy of the slope angle.

Preconditioning principles for preventing sports injuries in adolescents and children.

PubMed

Dollard, Mark D; Pontell, David; Hallivis, Robert

2006-01-01

Preseason preconditioning can be accomplished well over a 4-week period with a mandatory period of rest as we have discussed. Athletic participation must be guided by a gradual increase of skills performance in the child assessed after a responsible preconditioning program applying physiologic parameters as outlined. Clearly, designing a preconditioning program is a dynamic process when accounting for all the variables in training discussed so far. Despite the physiologic demands of sport and training, we still need to acknowledge the psychologic maturity and welfare of the child so as to ensure that the sport environment is a wholesome and emotionally rewarding experience.

Silymarin and its constituents in cardiac preconditioning.

PubMed

Zholobenko, A; Modriansky, M

2014-09-01

Silymarin, a standardised extract of Silybum marianum (milk thistle), comprises mainly of silybin, with dehydrosilybin (DHSB), quercetin, taxifolin, silychristin and a number of other compounds which are known to possess a range of salutary effects. Indeed, there is evidence for their role in reducing tumour growth, preventing liver toxicity, and protecting a number of organs against ischemic damage. The hepatoprotective effects of silymarin, especially in preventing Amanita and alcohol intoxication induced damage to the liver, are a well established fact. Likewise, there is weighty evidence that silymarin possesses antimicrobial and anticancer activities. Additionally, it has emerged that in animal models, silymarin can protect the heart, brain, liver and kidneys against ischemia reperfusion injury, probably by preconditioning. The mechanisms of preconditioning are, in general, well studied, especially in the heart. On the other hand, the mechanism by which silymarin protects the heart from ischemia remains largely unexplored. This review, therefore, focuses on evaluating existing studies on silymarin induced cardioprotection in the context of the established mechanisms of preconditioning. Copyright © 2014. Published by Elsevier B.V.

On polynomial preconditioning for indefinite Hermitian matrices

NASA Technical Reports Server (NTRS)

Freund, Roland W.

1989-01-01

The minimal residual method is studied combined with polynomial preconditioning for solving large linear systems (Ax = b) with indefinite Hermitian coefficient matrices (A). The standard approach for choosing the polynomial preconditioners leads to preconditioned systems which are positive definite. Here, a different strategy is studied which leaves the preconditioned coefficient matrix indefinite. More precisely, the polynomial preconditioner is designed to cluster the positive, resp. negative eigenvalues of A around 1, resp. around some negative constant. In particular, it is shown that such indefinite polynomial preconditioners can be obtained as the optimal solutions of a certain two parameter family of Chebyshev approximation problems. Some basic results are established for these approximation problems and a Remez type algorithm is sketched for their numerical solution. The problem of selecting the parameters such that the resulting indefinite polynomial preconditioners speeds up the convergence of minimal residual method optimally is also addressed. An approach is proposed based on the concept of asymptotic convergence factors. Finally, some numerical examples of indefinite polynomial preconditioners are given.

Molecular activity prediction by means of supervised subspace projection based ensembles of classifiers.

PubMed

Cerruela García, G; García-Pedrajas, N; Luque Ruiz, I; Gómez-Nieto, M Á

2018-03-01

This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods. Therefore, we show that ensembles constructed using supervised subspace projections offer an effective way of creating classifiers in cheminformatics.

Remote Ischemic Preconditioning and Outcomes of Cardiac Surgery.

PubMed

Hausenloy, Derek J; Candilio, Luciano; Evans, Richard; Ariti, Cono; Jenkins, David P; Kolvekar, Shyam; Knight, Rosemary; Kunst, Gudrun; Laing, Christopher; Nicholas, Jennifer; Pepper, John; Robertson, Steven; Xenou, Maria; Clayton, Tim; Yellon, Derek M

2015-10-08

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, patients were randomly assigned to remote ischemic preconditioning (four 5-minute inflations and deflations of a standard blood-pressure cuff on the upper arm) or sham conditioning (control group). Anesthetic management and perioperative care were not standardized. The combined primary end point was death from cardiovascular causes, nonfatal myocardial infarction, coronary revascularization, or stroke, assessed 12 months after randomization. We enrolled a total of 1612 patients (811 in the control group and 801 in the ischemic-preconditioning group) at 30 cardiac surgery centers in the United Kingdom. There was no significant difference in the cumulative incidence of the primary end point at 12 months between the patients in the remote ischemic preconditioning group and those in the control group (212 patients [26.5%] and 225 patients [27.7%], respectively; hazard ratio with ischemic preconditioning, 0.95; 95% confidence interval, 0.79 to 1.15; P=0.58). Furthermore, there were no significant between-group differences in either adverse events or the secondary end points of perioperative myocardial injury (assessed on the basis of the area under the curve for the high-sensitivity assay of serum troponin T at 72 hours), inotrope score (calculated from the maximum dose of the individual inotropic agents administered in the first 3 days after surgery), acute kidney injury, duration of stay in the intensive care unit and hospital, distance on the 6-minute walk test, and quality of life

Eigenmode Analysis of Boundary Conditions for One-Dimensional Preconditioned Euler Equations

NASA Technical Reports Server (NTRS)

Darmofal, David L.

1998-01-01

An analysis of the effect of local preconditioning on boundary conditions for the subsonic, one-dimensional Euler equations is presented. Decay rates for the eigenmodes of the initial boundary value problem are determined for different boundary conditions. Riemann invariant boundary conditions based on the unpreconditioned Euler equations are shown to be reflective with preconditioning, and, at low Mach numbers, disturbances do not decay. Other boundary conditions are investigated which are non-reflective with preconditioning and numerical results are presented confirming the analysis.

Orderings for conjugate gradient preconditionings

NASA Technical Reports Server (NTRS)

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.

Age-related reduction of cerebral ischemic preconditioning: myth or reality?

PubMed Central

Della-Morte, David; Cacciatore, Francesco; Salsano, Elisa; Pirozzi, Gilda; Genio, Maria Teresa Del; D’Antonio, Iole; Gargiulo, Gaetano; Palmirotta, Raffaele; Guadagni, Fiorella; Rundek, Tatjana; Abete, Pasquale

2013-01-01

Stroke is one of the leading causes of death in industrialized countries for people older than 65 years of age. The reasons are still unclear. A reduction of endogenous mechanisms against ischemic insults has been proposed to explain this phenomenon. The “cerebral” ischemic preconditioning mechanism is characterized by a brief episode of ischemia that renders the brain more resistant against subsequent longer ischemic events. This ischemic tolerance has been shown in numerous experimental models of cerebral ischemia. This protective mechanism seems to be reduced with aging both in experimental and clinical studies. Alterations of mediators released and/or intracellular pathways may be responsible for age-related ischemic preconditioning reduction. Agents able to mimic the “cerebral” preconditioning effect may represent a new powerful tool for the treatment of acute ischemic stroke in the elderly. In this article, animal and human cerebral ischemic preconditioning, its age-related difference, and its potential therapeutical applications are discussed. PMID:24204128

Physical subspace in a model of the quantized electromagnetic field coupled to an external field with an indefinite metric

NASA Astrophysics Data System (ADS)

Suzuki, Akito

2008-04-01

We study a model of the quantized electromagnetic field interacting with an external static source ρ in the Feynman (Lorentz) gauge and construct the quantized radiation field Aμ (μ=0,1,2,3) as an operator-valued distribution acting on the Fock space F with an indefinite metric. By using the Gupta subsidiary condition ∂μAμ(x)(+)Ψ=0, one can select the physical subspace Vphys. According to the Gupta-Bleuler formalism, Vphys is a non-negative subspace so that elements of Vphys, called physical states, can be probabilistically interpretable. Indeed, assuming that the external source ρ is infrared regular, i.e., ρ̂/∣k∣3/2ɛL2(R3), we can characterize the physical subspace Vphys and show that Vphys is non-negative. In addition, we find that the Hamiltonian of the model is reduced to the Hamiltonian of the transverse photons with the Coulomb interaction. We, however, prove that the physical subspace is trivial, i.e., Vphys={0}, if and only if the external source ρ is infrared singular, i.e., ρ̂/∣k∣3/2∉L2(R3). We also discuss a representation different from the above representation such that the physical subspace is not trivial under the infrared singular condition.

Management of Preconditioned Calves and Impacts of Preconditioning.

PubMed

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.

Loss of glycogen during preconditioning is not a prerequisite for protection of the rabbit heart.

PubMed

Weinbrenner, C; Wang, P; Downey, J M

1996-01-01

Depletion of glycogen has been proposed as the mechanism of protection from ischemic preconditioning. The hypothesis was tested by seeing whether pharmacological manipulation of preconditioning causes parallel changes in cardiac glycogen content. Five groups of isolated rabbit hearts were studied. Group 1 experienced 30 min of ischemia only. Group 2 (PC) was preconditioned with 5 min of global ischemia followed by 10 min of reperfusion. Group 3 was preconditioned with 5 min exposure to 400 nM bradykinin followed by a 10 min washout period. Group 4 experienced exposure to 10 microM adenosine followed by a 10 min washout period, and the fifth group was also preconditioned with 5 min ischemia and 10 min reperfusion but 100 microM 8-(p-sulfophenyl)theophylline (SPT), which blocks adenosine receptors, was included in the buffer to block preconditioning's protection. Transmural biopsies were taken before treatment, just prior to the 30 min period of global ischemia, and after 30 min of global ischemia. Glycogen in the samples was digested with amyloglucosidase and the resulting glucose was assayed. Baseline glycogen averaged 17.3 +/- 0.6 mumol glucose/g wet weight. After preconditioning glycogen decreased to 13.3 +/- 1.3 mumol glucose/g wet weight (p < 0.005 vs. baseline). Glycogen was similarly depleted after pharmacological preconditioning with adenosine (14.0 +/- 1.0 mumol glucose/g wet weight, p < 0.05 vs. baseline) suggesting a correlation. However, when preconditioning was performed in the presence of SPT, which blocks protection, glycogen was also depleted by the same amount (13.3 +/- 0.7 mumol glucose/g wet weight, p = ns vs. PC). Bradykinin, which also mimics preconditioning, caused no depletion of glycogen (16.3 +/- 0.8 mumol glucose/g wet weight, p = ns vs. baseline). Because preconditioning with bradykinin did not deplete glycogen and because glycogen continued to be low when protection from preconditioning was blocked with SPT, we conclude that loss of

Hyperbaric oxygen preconditioning protects against traumatic brain injury at high altitude.

PubMed

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.

Density-matrix-based algorithm for solving eigenvalue problems

NASA Astrophysics Data System (ADS)

Polizzi, Eric

2009-03-01

A fast and stable numerical algorithm for solving the symmetric eigenvalue problem is presented. The technique deviates fundamentally from the traditional Krylov subspace iteration based techniques (Arnoldi and Lanczos algorithms) or other Davidson-Jacobi techniques and takes its inspiration from the contour integration and density-matrix representation in quantum mechanics. It will be shown that this algorithm—named FEAST—exhibits high efficiency, robustness, accuracy, and scalability on parallel architectures. Examples from electronic structure calculations of carbon nanotubes are presented, and numerical performances and capabilities are discussed.

Application of Earthquake Subspace Detectors at Kilauea and Mauna Loa Volcanoes, Hawai`i

NASA Astrophysics Data System (ADS)

Okubo, P.; Benz, H.; Yeck, W.

2016-12-01

Recent studies have demonstrated the capabilities of earthquake subspace detectors for detailed cataloging and tracking of seismicity in a number of regions and settings. We are exploring the application of subspace detectors at the United States Geological Survey's Hawaiian Volcano Observatory (HVO) to analyze seismicity at Kilauea and Mauna Loa volcanoes. Elevated levels of microseismicity and occasional swarms of earthquakes associated with active volcanism here present cataloging challenges due the sheer numbers of earthquakes and an intrinsically low signal-to-noise environment featuring oceanic microseism and volcanic tremor in the ambient seismic background. With high-quality continuous recording of seismic data at HVO, we apply subspace detectors (Harris and Dodge, 2011, Bull. Seismol. Soc. Am., doi: 10.1785/0120100103) during intervals of noteworthy seismicity. Waveform templates are drawn from Magnitude 2 and larger earthquakes within clusters of earthquakes cataloged in the HVO seismic database. At Kilauea, we focus on seismic swarms in the summit caldera region where, despite continuing eruptions from vents in the summit region and in the east rift zone, geodetic measurements reflect a relatively inflated volcanic state. We also focus on seismicity beneath and adjacent to Mauna Loa's summit caldera that appears to be associated with geodetic expressions of gradual volcanic inflation, and where precursory seismicity clustered prior to both Mauna Loa's most recent eruptions in 1975 and 1984. We recover several times more earthquakes with the subspace detectors - down to roughly 2 magnitude units below the templates, based on relative amplitudes - compared to the numbers of cataloged earthquakes. The increased numbers of detected earthquakes in these clusters, and the ability to associate and locate them, allow us to infer details of the spatial and temporal distributions and possible variations in stresses within these key regions of the volcanoes.

Preconditioned alternating direction method of multipliers for inverse problems with constraints

NASA Astrophysics Data System (ADS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-02-01

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.

Rapamycin preconditioning attenuates transient focal cerebral ischemia/reperfusion injury in mice.

PubMed

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.

Discrete-State Stochastic Models of Calcium-Regulated Calcium Influx and Subspace Dynamics Are Not Well-Approximated by ODEs That Neglect Concentration Fluctuations

PubMed Central

Weinberg, Seth H.; Smith, Gregory D.

2012-01-01

Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597

Subspace Clustering via Learning an Adaptive Low-Rank Graph.

PubMed

Yin, Ming; Xie, Shengli; Wu, Zongze; Zhang, Yun; Gao, Junbin

2018-08-01

By using a sparse representation or low-rank representation of data, the graph-based subspace clustering has recently attracted considerable attention in computer vision, given its capability and efficiency in clustering data. However, the graph weights built using the representation coefficients are not the exact ones as the traditional definition is in a deterministic way. The two steps of representation and clustering are conducted in an independent manner, thus an overall optimal result cannot be guaranteed. Furthermore, it is unclear how the clustering performance will be affected by using this graph. For example, the graph parameters, i.e., the weights on edges, have to be artificially pre-specified while it is very difficult to choose the optimum. To this end, in this paper, a novel subspace clustering via learning an adaptive low-rank graph affinity matrix is proposed, where the affinity matrix and the representation coefficients are learned in a unified framework. As such, the pre-computed graph regularizer is effectively obviated and better performance can be achieved. Experimental results on several famous databases demonstrate that the proposed method performs better against the state-of-the-art approaches, in clustering.

A Newton-Krylov method with an approximate analytical Jacobian for implicit solution of Navier-Stokes equations on staggered overset-curvilinear grids with immersed boundaries.

PubMed

Asgharzadeh, Hafez; Borazjani, Iman

2017-02-15

The explicit and semi-implicit schemes in flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates. Implicit schemes can be used to overcome these restrictions, but implementing them to solve the Navier-Stokes equations is not straightforward due to their non-linearity. Among the implicit schemes for nonlinear equations, Newton-based techniques are preferred over fixed-point techniques because of their high convergence rate but each Newton iteration is more expensive than a fixed-point iteration. Krylov subspace methods are one of the most advanced iterative methods that can be combined with Newton methods, i.e., Newton-Krylov Methods (NKMs) to solve non-linear systems of equations. The success of NKMs vastly depends on the scheme for forming the Jacobian, e.g., automatic differentiation is very expensive, and matrix-free methods without a preconditioner slow down as the mesh is refined. A novel, computationally inexpensive analytical Jacobian for NKM is developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered overset-curvilinear grids with immersed boundaries. Moreover, the analytical Jacobian is used to form preconditioner for matrix-free method in order to improve its performance. The NKM with the analytical Jacobian was validated and verified against Taylor-Green vortex, inline oscillations of a cylinder in a fluid initially at rest, and pulsatile flow in a 90 degree bend. The capability of the method in handling complex geometries with multiple overset grids and immersed boundaries is shown by simulating an intracranial aneurysm. It was shown that the NKM with an analytical Jacobian is 1.17 to 14.77 times faster than the fixed-point Runge-Kutta method, and 1.74 to 152.3 times (excluding an intensively stretched grid) faster than automatic differentiation depending on the grid (size) and the flow problem. In addition, it was shown that using only the

A Newton–Krylov method with an approximate analytical Jacobian for implicit solution of Navier–Stokes equations on staggered overset-curvilinear grids with immersed boundaries

PubMed Central

Asgharzadeh, Hafez; Borazjani, Iman

2016-01-01

The explicit and semi-implicit schemes in flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates. Implicit schemes can be used to overcome these restrictions, but implementing them to solve the Navier-Stokes equations is not straightforward due to their non-linearity. Among the implicit schemes for nonlinear equations, Newton-based techniques are preferred over fixed-point techniques because of their high convergence rate but each Newton iteration is more expensive than a fixed-point iteration. Krylov subspace methods are one of the most advanced iterative methods that can be combined with Newton methods, i.e., Newton-Krylov Methods (NKMs) to solve non-linear systems of equations. The success of NKMs vastly depends on the scheme for forming the Jacobian, e.g., automatic differentiation is very expensive, and matrix-free methods without a preconditioner slow down as the mesh is refined. A novel, computationally inexpensive analytical Jacobian for NKM is developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered overset-curvilinear grids with immersed boundaries. Moreover, the analytical Jacobian is used to form preconditioner for matrix-free method in order to improve its performance. The NKM with the analytical Jacobian was validated and verified against Taylor-Green vortex, inline oscillations of a cylinder in a fluid initially at rest, and pulsatile flow in a 90 degree bend. The capability of the method in handling complex geometries with multiple overset grids and immersed boundaries is shown by simulating an intracranial aneurysm. It was shown that the NKM with an analytical Jacobian is 1.17 to 14.77 times faster than the fixed-point Runge-Kutta method, and 1.74 to 152.3 times (excluding an intensively stretched grid) faster than automatic differentiation depending on the grid (size) and the flow problem. In addition, it was shown that using only the

A Newton-Krylov method with an approximate analytical Jacobian for implicit solution of Navier-Stokes equations on staggered overset-curvilinear grids with immersed boundaries

NASA Astrophysics Data System (ADS)

Asgharzadeh, Hafez; Borazjani, Iman

2017-02-01

The explicit and semi-implicit schemes in flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates. Implicit schemes can be used to overcome these restrictions, but implementing them to solve the Navier-Stokes equations is not straightforward due to their non-linearity. Among the implicit schemes for non-linear equations, Newton-based techniques are preferred over fixed-point techniques because of their high convergence rate but each Newton iteration is more expensive than a fixed-point iteration. Krylov subspace methods are one of the most advanced iterative methods that can be combined with Newton methods, i.e., Newton-Krylov Methods (NKMs) to solve non-linear systems of equations. The success of NKMs vastly depends on the scheme for forming the Jacobian, e.g., automatic differentiation is very expensive, and matrix-free methods without a preconditioner slow down as the mesh is refined. A novel, computationally inexpensive analytical Jacobian for NKM is developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered overset-curvilinear grids with immersed boundaries. Moreover, the analytical Jacobian is used to form a preconditioner for matrix-free method in order to improve its performance. The NKM with the analytical Jacobian was validated and verified against Taylor-Green vortex, inline oscillations of a cylinder in a fluid initially at rest, and pulsatile flow in a 90 degree bend. The capability of the method in handling complex geometries with multiple overset grids and immersed boundaries is shown by simulating an intracranial aneurysm. It was shown that the NKM with an analytical Jacobian is 1.17 to 14.77 times faster than the fixed-point Runge-Kutta method, and 1.74 to 152.3 times (excluding an intensively stretched grid) faster than automatic differentiation depending on the grid (size) and the flow problem. In addition, it was shown that using only the

The Role of Ionospheric Outflow Preconditioning in Determining Storm Geoeffectiveness

NASA Astrophysics Data System (ADS)

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

[The relationship between ischemic preconditioning-induced infarction size limitation and duration of test myocardial ischemia].

PubMed

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.

Updating Hawaii Seismicity Catalogs with Systematic Relocations and Subspace Detectors

NASA Astrophysics Data System (ADS)

Okubo, P.; Benz, H.; Matoza, R. S.; Thelen, W. A.

2015-12-01

We continue the systematic relocation of seismicity recorded in Hawai`i by the United States Geological Survey's (USGS) Hawaiian Volcano Observatory (HVO), with interests in adding to the products derived from the relocated seismicity catalogs published by Matoza et al., (2013, 2014). Another goal of this effort is updating the systematically relocated HVO catalog since 2009, when earthquake cataloging at HVO was migrated to the USGS Advanced National Seismic System Quake Management Software (AQMS) systems. To complement the relocation analyses of the catalogs generated from traditional STA/LTA event-triggered and analyst-reviewed approaches, we are also experimenting with subspace detection of events at Kilauea as a means to augment AQMS procedures for cataloging seismicity to lower magnitudes and during episodes of elevated volcanic activity. Our earlier catalog relocations have demonstrated the ability to define correlated or repeating families of earthquakes and provide more detailed definition of seismogenic structures, as well as the capability for improved automatic identification of diverse volcanic seismic sources. Subspace detectors have been successfully applied to cataloging seismicity in situations of low seismic signal-to-noise and have significantly increased catalog sensitivity to lower magnitude thresholds. We anticipate similar improvements using event subspace detections and cataloging of volcanic seismicity that include improved discrimination among not only evolving earthquake sequences but also diverse volcanic seismic source processes. Matoza et al., 2013, Systematic relocation of seismicity on Hawai`i Island from 1992 to 2009 using waveform cross correlation and cluster analysis, J. Geophys. Res., 118, 2275-2288, doi:10.1002/jgrb.580189 Matoza et al., 2014, High-precision relocation of long-period events beneath the summit region of Kīlauea Volcano, Hawai`i, from 1986 to 2009, Geophys. Res. Lett., 41, 3413-3421, doi:10.1002/2014GL059819

Fourier analysis of finite element preconditioned collocation schemes

NASA Technical Reports Server (NTRS)

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.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

PubMed

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

Visual tracking based on the sparse representation of the PCA subspace

NASA Astrophysics Data System (ADS)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

Experimental creation of quantum Zeno subspaces by repeated multi-spin projections in diamond

NASA Astrophysics Data System (ADS)

Kalb, N.; Cramer, J.; Twitchen, D. J.; Markham, M.; Hanson, R.; Taminiau, T. H.

2016-10-01

Repeated observations inhibit the coherent evolution of quantum states through the quantum Zeno effect. In multi-qubit systems this effect provides opportunities to control complex quantum states. Here, we experimentally demonstrate that repeatedly projecting joint observables of multiple spins creates quantum Zeno subspaces and simultaneously suppresses the dephasing caused by a quasi-static environment. We encode up to two logical qubits in these subspaces and show that the enhancement of the dephasing time with increasing number of projections follows a scaling law that is independent of the number of spins involved. These results provide experimental insight into the interplay between frequent multi-spin measurements and slowly varying noise and pave the way for tailoring the dynamics of multi-qubit systems through repeated projections.

Detecting and characterizing coal mine related seismicity in the Western U.S. using subspace methods

NASA Astrophysics Data System (ADS)

Chambers, Derrick J. A.; Koper, Keith D.; Pankow, Kristine L.; McCarter, Michael K.

2015-11-01

We present an approach for subspace detection of small seismic events that includes methods for estimating magnitudes and associating detections from multiple stations into unique events. The process is used to identify mining related seismicity from a surface coal mine and an underground coal mining district, both located in the Western U.S. Using a blasting log and a locally derived seismic catalogue as ground truth, we assess detector performance in terms of verified detections, false positives and failed detections. We are able to correctly identify over 95 per cent of the surface coal mine blasts and about 33 per cent of the events from the underground mining district, while keeping the number of potential false positives relatively low by requiring all detections to occur on two stations. We find that most of the potential false detections for the underground coal district are genuine events missed by the local seismic network, demonstrating the usefulness of regional subspace detectors in augmenting local catalogues. We note a trade-off in detection performance between stations at smaller source-receiver distances, which have increased signal-to-noise ratio, and stations at larger distances, which have greater waveform similarity. We also explore the increased detection capabilities of a single higher dimension subspace detector, compared to multiple lower dimension detectors, in identifying events that can be described as linear combinations of training events. We find, in our data set, that such an advantage can be significant, justifying the use of a subspace detection scheme over conventional correlation methods.

Preconditioning for the Navier-Stokes equations with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Godfrey, Andrew G.; Walters, Robert W.; Van Leer, Bram

1993-01-01

The preconditioning procedure for generalized finite-rate chemistry and the proper preconditioning for the one-dimensional Navier-Stokes equations are presented. Eigenvalue stiffness is resolved and convergence-rate acceleration is demonstrated over the entire Mach-number range from the incompressible to the hypersonic. Specific benefits are realized at low and transonic flow speeds. The extended preconditioning matrix accounts for thermal and chemical non-equilibrium and its implementation is explained for both explicit and implicit time marching. The effect of higher-order spatial accuracy and various flux splittings is investigated. Numerical analysis reveals the possible theoretical improvements from using proconditioning at all Mach numbers. Numerical results confirm the expectations from the numerical analysis. Representative test cases include flows with previously troublesome embedded high-condition-number regions.

GENE EXPRESSION CHANGES AFTER SEIZURE PRECONDITIONING IN THE THREE MAJOR HIPPOCAMPAL CELL LAYERS

PubMed Central

Borges, Karin; Shaw, Renee; Dingledine, Raymond

2008-01-01

Rodents experience hippocampal damage after status epilepticus (SE) mainly in pyramidal cells while sparing the dentate granule cell layer (DGCL). Hippocampal damage was prevented in rats that had been preconditioned by brief seizures on two consecutive days before SE. To identify neuroprotective genes and biochemical pathways changed after preconditioning we compared the effect of preconditioning on gene expression in the CA1 and CA3 pyramidal and DGCLs, harvested by laser capture microscopy. In the DGCL the expression of 632 genes was altered, compared to only 151 and 58 genes in CA1 and CA3 pyramidal cell layers. Most of the differentially expressed genes regulate tissue structure and intra- and extracellular signaling, including neurotransmission. A selective upregulation of energy metabolism transcripts occurred in CA1 pyramidal cells relative to the DGCL. These results reveal a broad transcriptional response of the DGCL to preconditioning, and suggest several mechanisms underlying the neuroprotective effect of preconditioning seizures. PMID:17239605

Remote ischaemic preconditioning and prevention of cerebral injury.

PubMed

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.

Implementation details of the coupled QMR algorithm

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noel M.

1992-01-01

The original quasi-minimal residual method (QMR) relies on the three-term look-ahead Lanczos process, to generate basis vectors for the underlying Krylov subspaces. However, empirical observations indicate that, in finite precision arithmetic, three-term vector recurrences are less robust than mathematically equivalent coupled two-term recurrences. Therefore, we recently proposed a new implementation of the QMR method based on a coupled two-term look-ahead Lanczos procedure. In this paper, we describe implementation details of this coupled QMR algorithm, and we present results of numerical experiments.

Sleep Is Critical for Remote Preconditioning-Induced Neuroprotection.

PubMed

Brager, Allison J; Yang, Tao; Ehlen, J Christopher; Simon, Roger P; Meller, Robert; Paul, Ketema N

2016-11-01

Episodes of brief limb ischemia (remote preconditioning) in mice induce tolerance to modeled ischemic stroke (focal brain ischemia). Since stroke outcomes are in part dependent on sleep-wake history, we sought to determine if sleep is critical for the neuroprotective effect of limb ischemia. EEG/EMG recording electrodes were implanted in mice. After a 24 h baseline recording, limb ischemia was induced by tightening an elastic band around the left quadriceps for 10 minutes followed by 10 minutes of release for two cycles. Two days following remote preconditioning, a second 24 h EEG/EMG recording was completed and was immediately followed by a 60-minute suture occlusion of the middle cerebral artery (modeled ischemic stroke). This experiment was then repeated in a model of circadian and sleep abnormalities ( Bmal1 knockout [KO] mice sleep 2 h more than wild-type littermates). Brain infarction was determined by vital dye staining, and sleep was assessed by trained identification of EEG/EMG recordings. Two days after limb ischemia, wild-type mice slept an additional 2.4 h. This additional sleep was primarily comprised of non-rapid eye movement (NREM) sleep during the middle of the light-phase (i.e., naps). Repeating the experiment but preventing increases in sleep after limb ischemia abolished tolerance to ischemic stroke. In Bmal1 knockout mice, remote preconditioning did not increase daily sleep nor provide tolerance to subsequent focal ischemia. These results suggest that sleep induced by remote preconditioning is both sufficient and necessary for its neuroprotective effects on stroke outcome. © 2016 Associated Professional Sleep Societies, LLC.

Signal transduction of flumazenil-induced preconditioning in myocytes.

PubMed

Yao, Z; McPherson, B C; Liu, H; Shao, Z; Li, C; Qin, Y; Vanden Hoek, T L; Becker, L B; Schumacker, P T

2001-03-01

The objective of this study was to examine the role of oxygen radicals, protein kinase C (PKC), and ATP-sensitive K(+) (K(ATP)) channels in mediating flumazenil-produced preconditioning. Chick cardiomyocyte death was quantified using propidium iodide, and oxygen radical generation was assessed using 2',7'-dichlorofluorescin oxidation. Preconditioning was initiated with 10 min of ischemia followed by 10 min of reoxygenation. Alternatively, flumazenil was infused for 10 min and removed 10 min before ischemia. Flumazenil (10 microM) and preconditioning increased oxygen radicals [1,693 +/- 101 (n = 3) and 1,567 +/- 98 (n = 3), respectively, vs. 345 +/- 53 (n = 3) in control] and reduced cell death similarly [22 +/- 3% (n = 5) and 18 +/- 2% (n = 6), respectively, vs. controls 49 +/- 5% (n = 8)]. Protection and increased oxygen radicals by flumazenil were abolished by pretreatment with the antioxidant thiol reductant 2-mercaptopropionyl glycine (800 microM; 52 +/- 10%, n = 6). Specific PKC inhibitors Go-6976 (0.1 microM) and chelerythrine (2 microM), given during ischemia and reoxygenation, blocked flumazenil-produced protection (47 +/- 5%, n = 6). The PKC activator phorbol 12-myristate 13-acetate (0.2 microM), given during ischemia and reoxygenation, reduced cell death similarly to that with flumazenil [17 +/- 4% (n = 6) and 22 +/- 3% (n = 5)]. Finally, 5-hydroxydecanoate (1 mM), a selective mitochondrial K(ATP) channel antagonist given during ischemia and reoxygenation, abolished the protection of flumazenil and phorbol 12-myristate 13-acetate. Thus flumazenil mimics preconditioning to reduce cell death in cardiomyocytes. Oxygen radicals activate mitochondrial K(ATP) channels via PKC during the process.

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning.

PubMed

Zhang, Zhao; Yan, Shuicheng; Zhao, Mingbo

2014-05-01

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Flap preconditioning by pressure-controlled cupping in a rat model.

PubMed

Koh, Kyung S; Park, Sung Woo; Oh, Tae Suk; Choi, Jong Woo

2016-08-01

Flap survival is essential for the success of soft-tissue reconstruction. Accordingly, various surgical and medical methods aim to increase flap survival. Because flap survival is affected by the innate vascular supply, traditional preconditioning methods mainly target vasodilatation or vascular reorientation to increase blood flow to the tissue. External stress on the skin, such as an external volume expander or cupping, induces vascular remodeling, and these approaches have been used in the fat grafting field and in traditional Asian medicine. In the present study, we used a rat random-pattern dorsal flap model to study the effectiveness of preconditioning with an externally applied device (cupping) at the flap site that directly applied negative pressure to the skin. The device, the pressure-controlled cupping, is connected to negative pressure vacuum device providing accurate pressure control from 0 mm Hg to -200 mm Hg. Flap surgery was performed after preconditioning under -25 mm Hg suction pressure for 30 min a day for 5 d, followed by 9 d of postoperative observation. Flap survival was assessed as the area of viable tissue and was compared between the preconditioned group and a control group. The preconditioned group showed absolute percentage increase of flap viability relative to the entire flap by 19.0± 7.6% (average 70.1% versus 51.0%). Tissue perfusion of entire flap, evaluated by laser Doppler imaging system, was improved with absolute percentage increase by 24.2± 10.4% (average 77.4% versus 53.1%). Histologic analysis of hematoxylin and eosin, CD31, and Masson-trichrome staining showed increased vascular density in the subdermal plexus and more organized collagen production with hypertrophy of the attached muscle. Our study suggests that flap preconditioning caused by controlled noninvasive suction induces vascular remodeling that increases tissue perfusion and improves flap survival in a rat model. Copyright © 2016 Elsevier Inc. All rights

Sensory Preconditioning in Newborn Rabbits: From Common to Distinct Odor Memories

ERIC Educational Resources Information Center

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…

40 CFR 85.2220 - Preconditioned two speed idle test-EPA 91.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Preconditioned two speed idle test-EPA... Warranty Short Tests § 85.2220 Preconditioned two speed idle test—EPA 91. (a) General requirements—(1...-speed mode followed immediately by a first-chance idle mode. (ii) The second-chance test as described...

40 CFR 85.2220 - Preconditioned two speed idle test-EPA 91.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 18 2011-07-01 2011-07-01 false Preconditioned two speed idle test-EPA... Warranty Short Tests § 85.2220 Preconditioned two speed idle test—EPA 91. (a) General requirements—(1...-speed mode followed immediately by a first-chance idle mode. (ii) The second-chance test as described...

Peptide Nanofibers Preconditioned with Stem Cell Secretome Are Renoprotective

PubMed Central

Wang, Yin; Bakota, Erica; Chang, Benny H.J.; Entman, Mark; Hartgerink, Jeffrey D.

2011-01-01

Stem cells may contribute to renal recovery following acute kidney injury, and this may occur through their secretion of cytokines, chemokines, and growth factors. Here, we developed an acellular, nanofiber-based preparation of self-assembled peptides to deliver the secretome of embryonic stem cells (ESCs). Using an integrated in vitro and in vivo approach, we found that nanofibers preconditioned with ESCs could reverse cell hyperpermeability and apoptosis in vitro and protect against lipopolysaccharide-induced acute kidney injury in vivo. The renoprotective effect of preconditioned nanofibers associated with an attenuation of Rho kinase activation. We also observed that the combined presence of follistatin, adiponectin, and secretory leukoprotease during preconditioning was essential to the renoprotective properties of the nanofibers. In summary, we developed a designer-peptide nanofiber that can serve as a delivery platform for the beneficial effects of stem cells without the problems of teratoma formation or limited cell engraftment and viability. PMID:21415151

Sound transmission through a poroelastic layered panel

NASA Astrophysics Data System (ADS)

Nagler, Loris; Rong, Ping; Schanz, Martin; von Estorff, Otto

2014-04-01

Multi-layered panels are often used to improve the acoustics in cars, airplanes, rooms, etc. For such an application these panels include porous and/or fibrous layers. The proposed numerical method is an approach to simulate the acoustical behavior of such multi-layered panels. The model assumes plate-like structures and, hence, combines plate theories for the different layers. The poroelastic layer is modelled with a recently developed plate theory. This theory uses a series expansion in thickness direction with subsequent analytical integration in this direction to reduce the three dimensions to two. The same idea is used to model either air gaps or fibrous layers. The latter are modeled as equivalent fluid and can be handled like an air gap, i.e., a kind of `air plate' is used. The coupling of the layers is done by using the series expansion to express the continuity conditions on the surfaces of the plates. The final system is solved with finite elements, where domain decomposition techniques in combination with preconditioned iterative solvers are applied to solve the final system of equations. In a large frequency range, the comparison with measurements shows very good agreement. From the numerical solution process it can be concluded that different preconditioners for the different layers are necessary. A reuse of the Krylov subspace of the iterative solvers pays if several excitations have to be computed but not that much in the loop over the frequencies.

Fuzzy Subspace Clustering

NASA Astrophysics Data System (ADS)

Borgelt, Christian

In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to transfer an alternative to the fuzzifier (Klawonn and Höppner, What is fuzzy about fuzzy clustering? Understanding and improving the concept of the fuzzifier, In: Proc. 5th Int. Symp. on Intelligent Data Analysis, 254-264, Springer, Berlin, 2003) to attribute weighting fuzzy clustering (Keller and Klawonn, Int J Uncertain Fuzziness Knowl Based Syst 8:735-746, 2000). In addition, by reformulating Gustafson-Kessel fuzzy clustering, a scheme for weighting and selecting principal axes can be obtained. While in Borgelt (Feature weighting and feature selection in fuzzy clustering, In: Proc. 17th IEEE Int. Conf. on Fuzzy Systems, IEEE Press, Piscataway, NJ, 2008) I already presented such an approach for a global selection of attributes and principal axes, this paper extends it to a cluster-specific selection, thus arriving at a fuzzy subspace clustering algorithm (Parsons, Haque, and Liu, 2004).

Mechanical preconditioning enables electrophysiologic coupling of skeletal myoblast cells to myocardium

PubMed Central

Treskes, Philipp; Cowan, Douglas B.; Stamm, Christof; Rubach, Martin; Adelmann, Roland; Wittwer, Thorsten; Wahlers, Thorsten

2015-01-01

Objective The effect of mechanical preconditioning on skeletal myoblasts in engineered tissue constructs was investigated to resolve issues associated with conduction block between skeletal myoblast cells and cardiomyocytes. Methods Murine skeletal myoblasts were used to generate engineered tissue constructs with or without application of mechanical strain. After in vitro myotube formation, engineered tissue constructs were co-cultured for 6 days with viable embryonic heart slices. With the use of sharp electrodes, electrical coupling between engineered tissue constructs and embryonic heart slices was assessed in the presence or absence of pharmacologic agents. Results The isolation and expansion procedure for skeletal myoblasts resulted in high yields of homogeneously desmin-positive (97.1% ± 0.1%) cells. Mechanical strain was exerted on myotubes within engineered tissue constructs during gelation of the matrix, generating preconditioned engineered tissue constructs. Electrical coupling between preconditioned engineered tissue constructs and embryonic heart slices was observed; however, no coupling was apparent when engineered tissue constructs were not subjected to mechanical strain. Coupling of cells from engineered tissue constructs to cells in embryonic heart slices showed slower conduction velocities than myocardial cells with the embryonic heart slices (preconditioned engineered tissue constructs vs embryonic heart slices: 0.04 ± 0.02 ms vs 0.10 ± 0.05 ms, P = .011), lower stimulation frequencies (preconditioned engineered tissue constructs vs maximum embryonic heart slices: 4.82 ± 1.42 Hz vs 10.58 ± 1.56 Hz; P = .0009), and higher sensitivities to the gap junction inhibitor (preconditioned engineered tissue constructs vs embryonic heart slices: 0.22 ± 0.07 mmol/L vs 0.93 ± 0.15 mmol/L; P = .0004). Conclusions We have generated skeletal myoblast–based transplantable grafts that electrically couple to myocardium. PMID:22980065

Hypoxia preconditioning protection of corneal stromal cells requires HIF1alpha but not VEGF.

PubMed

Xing, Dongmei; Bonanno, Joseph A

2009-05-18

Hypoxia preconditioning protects corneal stromal cells from stress-induced death. This study determined whether the transcription factor HIF-1alpha (Hypoxia Inducible Factor) is responsible and whether this is promulgated by VEGF (Vascular Endothelial Growth Factor). Cultured bovine stromal cells were preconditioned with hypoxia in the presence of cadmium chloride, a chemical inhibitor of HIF-1alpha, and HIF-1alpha siRNA to test if HIF-1alpha activity is needed for hypoxia preconditioning protection from UV-irradiation induced cell death. TUNEL assay was used to detect cell apoptosis after UV-irradiation. RT-PCR and western blot were used to detect the presence of HIF-1alpha and VEGF in transcriptional and translational levels. During hypoxia (0.5% O2), 5 muM cadmium chloride completely inhibited HIF-1alpha expression and reversed the protection by hypoxia preconditioning. HIF-1alpha siRNA (15 nM) reduced HIF-1alpha expression by 90% and produced a complete loss of protection provided by hypoxia preconditioning. Since VEGF is induced by hypoxia, can be HIF-1alpha dependent, and is often protective, we examined the changes in transcription of VEGF and its receptors after 4 h of hypoxia preconditioning. VEGF and its receptors Flt-1 and Flk-1 are up-regulated after hypoxia preconditioning. However, the transcription and translation of VEGF were paradoxically increased by siHIF-1alpha, suggesting that VEGF expression in stromal cells is not down-stream of HIF-1alpha. These findings demonstrate that hypoxia preconditioning protection in corneal stromal cells requires HIF-1alpha, but that VEGF is not a component of the protection.

Subspace aware recovery of low rank and jointly sparse signals

PubMed Central

Biswas, Sampurna; Dasgupta, Soura; Mudumbai, Raghuraman; Jacob, Mathews

2017-01-01

We consider the recovery of a matrix X, which is simultaneously low rank and joint sparse, from few measurements of its columns using a two-step algorithm. Each column of X is measured using a combination of two measurement matrices; one which is the same for every column, while the the second measurement matrix varies from column to column. The recovery proceeds by first estimating the row subspace vectors from the measurements corresponding to the common matrix. The estimated row subspace vectors are then used to recover X from all the measurements using a convex program of joint sparsity minimization. Our main contribution is to provide sufficient conditions on the measurement matrices that guarantee the recovery of such a matrix using the above two-step algorithm. The results demonstrate quite significant savings in number of measurements when compared to the standard multiple measurement vector (MMV) scheme, which assumes same time invariant measurement pattern for all the time frames. We illustrate the impact of the sampling pattern on reconstruction quality using breath held cardiac cine MRI and cardiac perfusion MRI data, while the utility of the algorithm to accelerate the acquisition is demonstrated on MR parameter mapping. PMID:28630889

Beamforming using subspace estimation from a diagonally averaged sample covariance.

PubMed

Quijano, Jorge E; Zurk, Lisa M

2017-08-01

The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2012 CFR

2012-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2011 CFR

2011-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2014 CFR

2014-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2013 CFR

2013-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

Exercise and Cardiac Preconditioning Against Ischemia Reperfusion Injury

PubMed Central

Quindry, John C; Hamilton, Karyn L

2013-01-01

Cardiovascular disease (CVD), including ischemia reperfusion (IR) injury, remains a major cause of morbidity and mortality in industrialized nations. Ongoing research is aimed at uncovering therapeutic interventions against IR injury. Regular exercise participation is recognized as an important lifestyle intervention in the prevention and treatment of CVD and IR injury. More recent understanding reveals that moderate intensity aerobic exercise is also an important experimental model for understanding the cellular mechanisms of cardioprotection against IR injury. An important discovery in this regard was the observation that one-to-several days of exercise will attenuate IR injury. This phenomenon has been observed in young and old hearts of both sexes. Due to the short time course of exercise induced protection, IR injury prevention must be mediated by acute biochemical alterations within the myocardium. Research over the last decade reveals that redundant mechanisms account for exercise induced cardioprotection against IR. While much is now known about exercise preconditioning against IR injury, many questions remain. Perhaps most pressing, is what mechanisms mediate cardioprotection in aged hearts and what sex-dependent differences exist. Given that that exercise preconditioning is a polygenic effect, it is likely that multiple mediators of exercise induced cardioprotection have yet to be uncovered. Also unknown, is whether post translational modifications due to exercise are responsible for IR injury prevention. This review will provide an overview the major mechanisms of IR injury and exercise preconditioning. The discussion highlights many promising avenues for further research and describes how exercise preconditioning may continue to be an important scientific paradigm in the translation of cardioprotection research to the clinic. PMID:23909636

Priming of the Cells: Hypoxic Preconditioning for Stem Cell Therapy.

PubMed

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.

Myocardial protection using diadenosine tetraphosphate with pharmacological preconditioning.

PubMed

Ahmet, I; Sawa, Y; Nishimura, M; Yamaguchi, T; Kitakaze, M; Matsuda, H

2000-09-01

We have reported a similar cardioprotective effect and mechanism of diadenosine tetraphosphate (AP4A) and ischemic preconditioning in rat hearts. In this study, the applicability of AP4A administration to cardiac surgery was tested by using a canine cardiopulmonary bypass model. Hearts underwent 60 minutes of cardioplegic arrest (34 degrees C) by a single dose of cardioplegia. Cardioplegia contained either AP4A (40 micromol/L; n = 6) or saline (n = 6). Beagles were weaned from cardiopulmonary bypass 30 minutes after reperfusion, and left ventricular function was evaluated after another 30 minutes by using the cardiac loop analysis system. Administration of AP4A significantly improved the postischemic recovery of cardiac function and reduced the leakage of serum creatine kinase compared with saline. Systemic vascular resistance, mean aortic blood pressure, and the electrocardiographic indices were not significantly altered by AP4A administration. Administration of AP4A was cardioprotective without apparent adverse effects. Because the cardioprotective mechanism may be similar to that of ischemic preconditioning, the addition of AP4A into cardioplegia may be a novel safe method for clinical application of preconditioning cardioprotection.

Effect of ozone oxidative preconditioning in preventing early radiation-induced lung injury in rats

PubMed Central

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. PMID:23969972

On adaptive weighted polynomial preconditioning for Hermitian positive definite matrices

NASA Technical Reports Server (NTRS)

Fischer, Bernd; Freund, Roland W.

1992-01-01

The conjugate gradient algorithm for solving Hermitian positive definite linear systems is usually combined with preconditioning in order to speed up convergence. In recent years, there has been a revival of polynomial preconditioning, motivated by the attractive features of the method on modern architectures. Standard techniques for choosing the preconditioning polynomial are based only on bounds for the extreme eigenvalues. Here a different approach is proposed, which aims at adapting the preconditioner to the eigenvalue distribution of the coefficient matrix. The technique is based on the observation that good estimates for the eigenvalue distribution can be derived after only a few steps of the Lanczos process. This information is then used to construct a weight function for a suitable Chebyshev approximation problem. The solution of this problem yields the polynomial preconditioner. In particular, we investigate the use of Bernstein-Szego weights.

SIMULTANEOUS MULTISLICE MAGNETIC RESONANCE FINGERPRINTING WITH LOW-RANK AND SUBSPACE MODELING

PubMed Central

Zhao, Bo; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A.; Wald, Lawrence L.; Setsompop, Kawin

2018-01-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3x speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice. PMID:29060594

3D deformable image matching: a hierarchical approach over nested subspaces

NASA Astrophysics Data System (ADS)

Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

2000-06-01

This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

Multi-subject subspace alignment for non-stationary EEG-based emotion recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Liu, Xin; Liu, Dan; Bai, Ou

2018-01-01

Emotion recognition based on EEG signals is a critical component in Human-Machine collaborative environments and psychiatric health diagnoses. However, EEG patterns have been found to vary across subjects due to user fatigue, different electrode placements, and varying impedances, etc. This problem renders the performance of EEG-based emotion recognition highly specific to subjects, requiring time-consuming individual calibration sessions to adapt an emotion recognition system to new subjects. Recently, domain adaptation (DA) strategies have achieved a great deal success in dealing with inter-subject adaptation. However, most of them can only adapt one subject to another subject, which limits their applicability in real-world scenarios. To alleviate this issue, a novel unsupervised DA strategy called Multi-Subject Subspace Alignment (MSSA) is proposed in this paper, which takes advantage of subspace alignment solution and multi-subject information in a unified framework to build personalized models without user-specific labeled data. Experiments on a public EEG dataset known as SEED verify the effectiveness and superiority of MSSA over other state of the art methods for dealing with multi-subject scenarios.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.

PubMed

Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-07-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

Expedited Holonomic Quantum Computation via Net Zero-Energy-Cost Control in Decoherence-Free Subspace.

PubMed

Pyshkin, P V; Luo, Da-Wei; Jing, Jun; You, J Q; Wu, Lian-Ao

2016-11-25

Holonomic quantum computation (HQC) may not show its full potential in quantum speedup due to the prerequisite of a long coherent runtime imposed by the adiabatic condition. Here we show that the conventional HQC can be dramatically accelerated by using external control fields, of which the effectiveness is exclusively determined by the integral of the control fields in the time domain. This control scheme can be realized with net zero energy cost and it is fault-tolerant against fluctuation and noise, significantly relaxing the experimental constraints. We demonstrate how to realize the scheme via decoherence-free subspaces. In this way we unify quantum robustness merits of this fault-tolerant control scheme, the conventional HQC and decoherence-free subspace, and propose an expedited holonomic quantum computation protocol.

Geometrical eigen-subspace framework based molecular conformation representation for efficient structure recognition and comparison

NASA Astrophysics Data System (ADS)

Li, Xiao-Tian; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-04-01

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. A complete set of atomic EPFs constitute an intrinsic representation of molecular conformation, based on which the interatomic EPF distance and intermolecular EPF distance can be reasonably defined. Exemplified with a few cases, the intermolecular EPF distance shows exceptional rationality and efficiency in structure recognition and comparison.

Choice of Variables and Preconditioning for Time Dependent Problems

NASA Technical Reports Server (NTRS)

Turkel, Eli; Vatsa, Verr N.

2003-01-01

We consider the use of low speed preconditioning for time dependent problems. These are solved using a dual time step approach. We consider the effect of this dual time step on the parameter of the low speed preconditioning. In addition, we compare the use of two sets of variables, conservation and primitive variables, to solve the system. We show the effect of these choices on both the convergence to a steady state and the accuracy of the numerical solutions for low Mach number steady state and time dependent flows.

Scalable Parallel Computation for Extended MHD Modeling of Fusion Plasmas

NASA Astrophysics Data System (ADS)

Glasser, Alan H.

2008-11-01

Parallel solution of a linear system is scalable if simultaneously doubling the number of dependent variables and the number of processors results in little or no increase in the computation time to solution. Two approaches have this property for parabolic systems: multigrid and domain decomposition. Since extended MHD is primarily a hyperbolic rather than a parabolic system, additional steps must be taken to parabolize the linear system to be solved by such a method. Such physics-based preconditioning (PBP) methods have been pioneered by Chac'on, using finite volumes for spatial discretization, multigrid for solution of the preconditioning equations, and matrix-free Newton-Krylov methods for the accurate solution of the full nonlinear preconditioned equations. The work described here is an extension of these methods using high-order spectral element methods and FETI-DP domain decomposition. Application of PBP to a flux-source representation of the physics equations is discussed. The resulting scalability will be demonstrated for simple wave and for ideal and Hall MHD waves.

Subspace methods for identification of human ankle joint stiffness.

PubMed

Zhao, Y; Westwick, D T; Kearney, R E

2011-11-01

Joint stiffness, the dynamic relationship between the angular position of a joint and the torque acting about it, describes the dynamic, mechanical behavior of a joint during posture and movement. Joint stiffness arises from both intrinsic and reflex mechanisms, but the torques due to these mechanisms cannot be measured separately experimentally, since they appear and change together. Therefore, the direct estimation of the intrinsic and reflex stiffnesses is difficult. In this paper, we present a new, two-step procedure to estimate the intrinsic and reflex components of ankle stiffness. In the first step, a discrete-time, subspace-based method is used to estimate a state-space model for overall stiffness from the measured overall torque and then predict the intrinsic and reflex torques. In the second step, continuous-time models for the intrinsic and reflex stiffnesses are estimated from the predicted intrinsic and reflex torques. Simulations and experimental results demonstrate that the algorithm estimates the intrinsic and reflex stiffnesses accurately. The new subspace-based algorithm has three advantages over previous algorithms: 1) It does not require iteration, and therefore, will always converge to an optimal solution; 2) it provides better estimates for data with high noise or short sample lengths; and 3) it provides much more accurate results for data acquired under the closed-loop conditions, that prevail when subjects interact with compliant loads.

Priming of the Cells: Hypoxic Preconditioning for Stem Cell Therapy

PubMed Central

Wei, Zheng Z; Zhu, Yan-Bing; Zhang, James Y; McCrary, Myles R; Wang, Song; Zhang, Yong-Bo; Yu, Shan-Ping; Wei, Ling

2017-01-01

Objective: 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. Data Sources: 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.” Study Selection: Original articles and critical reviews on the topics were selected. Results: 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. Conclusions: 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

Preconditioning to Reduce Decompression Stress in Scuba Divers.

PubMed

Germonpré, Peter; Balestra, Costantino

2017-02-01

Using ultrasound imaging, vascular gas emboli (VGE) are observed after asymptomatic scuba dives and are considered a key element in the potential development of decompression sickness (DCS). Diving is also accompanied with vascular dysfunction, as measured by flow-mediated dilation (FMD). Previous studies showed significant intersubject variability to VGE for the same diving exposure and demonstrated that VGE can be reduced with even a single pre-dive intervention. Several preconditioning methods have been reported recently, seemingly acting either on VGE quantity or on endothelial inflammatory markers. Nine male divers who consistently showed VGE postdive performed a standardized deep pool dive (33 m/108 ft, 20 min in 33°C water temperature) to investigate the effect of three different preconditioning interventions: heat exposure (a 30-min session of dry infrared sauna), whole-body vibration (a 30-min session on a vibration mattress), and dark chocolate ingestion (30 g of chocolate containing 86% cocoa). Dives were made one day per week and interventions were administered in a randomized order. These interventions were shown to selectively reduce VGE, FMD, or both compared to control dives. Vibration had an effect on VGE (39.54%, SEM 16.3%) but not on FMD postdive. Sauna had effects on both parameters (VGE: 26.64%, SEM 10.4%; FMD: 102.7%, SEM 2.1%), whereas chocolate only improved FMD (102.5%, SEM 1.7%). This experiment, which had the same subjects perform all control and preconditioning dives in wet but completely standardized diving conditions, demonstrates that endothelial dysfunction appears to not be solely related to VGE.Germonpré P, Balestra C. Preconditioning to reduce decompression stress in scuba divers. Aerosp Med Hum Perform. 2017; 88(2):114-120.

Code subspaces for LLM geometries

NASA Astrophysics Data System (ADS)

Berenstein, David; Miller, Alexandra

2018-03-01

We consider effective field theory around classical background geometries with a gauge theory dual, specifically those in the class of LLM geometries. These are dual to half-BPS states of N= 4 SYM. We find that the language of code subspaces is natural for discussing the set of nearby states, which are built by acting with effective fields on these backgrounds. This work extends our previous work by going beyond the strict infinite N limit. We further discuss how one can extract the topology of the state beyond N→∞ and find that, as before, uncertainty and entanglement entropy calculations provide a useful tool to do so. Finally, we discuss obstructions to writing down a globally defined metric operator. We find that the answer depends on the choice of reference state that one starts with. Therefore, within this setup, there is ambiguity in trying to write an operator that describes the metric globally.

A hybrid approach to generating search subspaces in dynamically constrained 4-dimensional data assimilation

NASA Astrophysics Data System (ADS)

Yaremchuk, Max; Martin, Paul; Beattie, Christopher

2017-09-01

Development and maintenance of the linearized and adjoint code for advanced circulation models is a challenging issue, requiring a significant proportion of total effort in operational data assimilation (DA). The ensemble-based DA techniques provide a derivative-free alternative, which appears to be competitive with variational methods in many practical applications. This article proposes a hybrid scheme for generating the search subspaces in the adjoint-free 4-dimensional DA method (a4dVar) that does not use a predefined ensemble. The method resembles 4dVar in that the optimal solution is strongly constrained by model dynamics and search directions are supplied iteratively using information from the current and previous model trajectories generated in the process of optimization. In contrast to 4dVar, which produces a single search direction from exact gradient information, a4dVar employs an ensemble of directions to form a subspace in order to proceed. In the earlier versions of a4dVar, search subspaces were built using the leading EOFs of either the model trajectory or the projections of the model-data misfits onto the range of the background error covariance (BEC) matrix at the current iteration. In the present study, we blend both approaches and explore a hybrid scheme of ensemble generation in order to improve the performance and flexibility of the algorithm. In addition, we introduce balance constraints into the BEC structure and periodically augment the search ensemble with BEC eigenvectors to avoid repeating minimization over already explored subspaces. Performance of the proposed hybrid a4dVar (ha4dVar) method is compared with that of standard 4dVar in a realistic regional configuration assimilating real data into the Navy Coastal Ocean Model (NCOM). It is shown that the ha4dVar converges faster than a4dVar and can be potentially competitive with 4dvar both in terms of the required computational time and the forecast skill.

Improving the Nulling Beamformer Using Subspace Suppression.

PubMed

Rana, Kunjan D; Hämäläinen, Matti S; Vaina, Lucia M

2018-01-01

Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, which may be removed by the TSVD operation. To address this issue we propose a new method, the nulling beamformer with subspace suppression (NBSS). This method, controlled by a tuning parameter, reweights the singular values of the gain matrix mapping from source to sensor space such that components with high overlap are reduced. By doing so, we are able to measure signals between nearby source locations with limited cross-talk interference, allowing for reliable cortical connectivity analysis between them. In two simulations, we demonstrated that NBSS reduces cross-talk while retaining ROIs' signal power, and has higher separating power than both the minimum norm estimate (MNE) and the nulling beamformer without subspace suppression. We also showed that NBSS successfully localized the auditory M100 event-related field in primary auditory cortex, measured from a subject undergoing an auditory localizer task, and suppressed cross-talk in a nearby region in the superior temporal sulcus.

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

PubMed

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Application of Subspace Detection to the 6 November 2011 M5.6 Prague, Oklahoma Aftershock Sequence

NASA Astrophysics Data System (ADS)

McMahon, N. D.; Benz, H.; Johnson, C. E.; Aster, R. C.; McNamara, D. E.

2015-12-01

Subspace detection is a powerful tool for the identification of small seismic events. Subspace detectors improve upon single-event matched filtering techniques by using multiple orthogonal waveform templates whose linear combinations characterize a range of observed signals from previously identified earthquakes. Subspace detectors running on multiple stations can significantly increasing the number of locatable events, lowering the catalog's magnitude of completeness and thus providing extraordinary detail on the kinematics of the aftershock process. The 6 November 2011 M5.6 earthquake near Prague, Oklahoma is the largest earthquake instrumentally recorded in Oklahoma history and the largest earthquake resultant from deep wastewater injection. A M4.8 foreshock on 5 November 2011 and the M5.6 mainshock triggered tens of thousands of detectable aftershocks along a 20 km splay of the Wilzetta Fault Zone known as the Meeker-Prague fault. In response to this unprecedented earthquake, 21 temporary seismic stations were deployed surrounding the seismic activity. We utilized a catalog of 767 previously located aftershocks to construct subspace detectors for the 21 temporary and 10 closest permanent seismic stations. Subspace detection identified more than 500,000 new arrival-time observations, which associated into more than 20,000 locatable earthquakes. The associated earthquakes were relocated using the Bayesloc multiple-event locator, resulting in ~7,000 earthquakes with hypocentral uncertainties of less than 500 m. The relocated seismicity provides unique insight into the spatio-temporal evolution of the aftershock sequence along the Wilzetta Fault Zone and its associated structures. We find that the crystalline basement and overlying sedimentary Arbuckle formation accommodate the majority of aftershocks. While we observe aftershocks along the entire 20 km length of the Meeker-Prague fault, the vast majority of earthquakes were confined to a 9 km wide by 9 km deep

Multi-frequency subspace migration for imaging of perfectly conducting, arc-like cracks in full- and limited-view inverse scattering problems

NASA Astrophysics Data System (ADS)

Park, Won-Kwang

2015-02-01

Multi-frequency subspace migration imaging techniques are usually adopted for the non-iterative imaging of unknown electromagnetic targets, such as cracks in concrete walls or bridges and anti-personnel mines in the ground, in the inverse scattering problems. It is confirmed that this technique is very fast, effective, robust, and can not only be applied to full- but also to limited-view inverse problems if a suitable number of incidents and corresponding scattered fields are applied and collected. However, in many works, the application of such techniques is heuristic. With the motivation of such heuristic application, this study analyzes the structure of the imaging functional employed in the subspace migration imaging technique in two-dimensional full- and limited-view inverse scattering problems when the unknown targets are arbitrary-shaped, arc-like perfectly conducting cracks located in the two-dimensional homogeneous space. In contrast to the statistical approach based on statistical hypothesis testing, our approach is based on the fact that the subspace migration imaging functional can be expressed by a linear combination of the Bessel functions of integer order of the first kind. This is based on the structure of the Multi-Static Response (MSR) matrix collected in the far-field at nonzero frequency in either Transverse Magnetic (TM) mode (Dirichlet boundary condition) or Transverse Electric (TE) mode (Neumann boundary condition). The investigation of the expression of imaging functionals gives us certain properties of subspace migration and explains why multi-frequency enhances imaging resolution. In particular, we carefully analyze the subspace migration and confirm some properties of imaging when a small number of incident fields are applied. Consequently, we introduce a weighted multi-frequency imaging functional and confirm that it is an improved version of subspace migration in TM mode. Various results of numerical simulations performed on the far

Expedited Holonomic Quantum Computation via Net Zero-Energy-Cost Control in Decoherence-Free Subspace

PubMed Central

Pyshkin, P. V.; Luo, Da-Wei; Jing, Jun; You, J. Q.; Wu, Lian-Ao

2016-01-01

Holonomic quantum computation (HQC) may not show its full potential in quantum speedup due to the prerequisite of a long coherent runtime imposed by the adiabatic condition. Here we show that the conventional HQC can be dramatically accelerated by using external control fields, of which the effectiveness is exclusively determined by the integral of the control fields in the time domain. This control scheme can be realized with net zero energy cost and it is fault-tolerant against fluctuation and noise, significantly relaxing the experimental constraints. We demonstrate how to realize the scheme via decoherence-free subspaces. In this way we unify quantum robustness merits of this fault-tolerant control scheme, the conventional HQC and decoherence-free subspace, and propose an expedited holonomic quantum computation protocol. PMID:27886234

Liquid hydrogen turbopump rapid start program. [thermal preconditioning using coatings

NASA Technical Reports Server (NTRS)

Wong, G. S.

1973-01-01

This program was to analyze, test, and evaluate methods of achieving rapid-start of a liquid hydrogen feed system (inlet duct and turbopump) using a minimum of thermal preconditioning time and propellant. The program was divided into four tasks. Task 1 includes analytical studies of the testing conducted in the other three tasks. Task 2 describes the results from laboratory testing of coating samples and the successful adherence of a KX-635 coating to the internal surfaces of the feed system tested in Task 4. Task 3 presents results of testing an uncoated feed system. Tank pressure was varied to determine the effect of flowrate on preconditioning. The discharge volume and the discharge pressure which initiates opening of the discharge valve were varied to determine the effect on deadhead (no through-flow) start transients. Task 4 describes results of testing a similar, internally coated feed system and illustrates the savings in preconditioning time and propellant resulting from the coatings.

A Reduced Order Model of the Linearized Incompressible Navier-Strokes Equations for the Sensor/Actuator Placement Problem

NASA Technical Reports Server (NTRS)

Allan, Brian G.

2000-01-01

A reduced order modeling approach of the Navier-Stokes equations is presented for the design of a distributed optimal feedback kernel. This approach is based oil a Krylov subspace method where significant modes of the flow are captured in the model This model is then used in all optimal feedback control design where sensing and actuation is performed oil tile entire flow field. This control design approach yields all optimal feedback kernel which provides insight into the placement of sensors and actuators in the flow field. As all evaluation of this approach, a two-dimensional shear layer and driven cavity flow are investigated.

Research on the Changes to the Lipid/Polymer Membrane Used in the Acidic Bitterness Sensor Caused by Preconditioning

PubMed Central

Harada, Yuhei; Noda, Junpei; Yatabe, Rui; Ikezaki, Hidekazu; Toko, Kiyoshi

2016-01-01

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. PMID:26891299

Exogenous Gene Transmission of Isocitrate Dehydrogenase 2 Mimics Ischemic Preconditioning Protection.

PubMed

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.

Preconditioning for Numerical Simulation of Low Mach Number Three-Dimensional Viscous Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Tweedt, Daniel L.; Chima, Rodrick V.; Turkel, Eli

1997-01-01

A preconditioning scheme has been implemented into a three-dimensional viscous computational fluid dynamics code for turbomachine blade rows. The preconditioning allows the code, originally developed for simulating compressible flow fields, to be applied to nearly-incompressible, low Mach number flows. A brief description is given of the compressible Navier-Stokes equations for a rotating coordinate system, along with the preconditioning method employed. Details about the conservative formulation of artificial dissipation are provided, and different artificial dissipation schemes are discussed and compared. The preconditioned code was applied to a well-documented case involving the NASA large low-speed centrifugal compressor for which detailed experimental data are available for comparison. Performance and flow field data are compared for the near-design operating point of the compressor, with generally good agreement between computation and experiment. Further, significant differences between computational results for the different numerical implementations, revealing different levels of solution accuracy, are discussed.

Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures

NASA Technical Reports Server (NTRS)

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.

Interpreting the Coulomb-field approximation for generalized-Born electrostatics using boundary-integral equation theory.

PubMed

Bardhan, Jaydeep P

2008-10-14

The importance of molecular electrostatic interactions in aqueous solution has motivated extensive research into physical models and numerical methods for their estimation. The computational costs associated with simulations that include many explicit water molecules have driven the development of implicit-solvent models, with generalized-Born (GB) models among the most popular of these. In this paper, we analyze a boundary-integral equation interpretation for the Coulomb-field approximation (CFA), which plays a central role in most GB models. This interpretation offers new insights into the nature of the CFA, which traditionally has been assessed using only a single point charge in the solute. The boundary-integral interpretation of the CFA allows the use of multiple point charges, or even continuous charge distributions, leading naturally to methods that eliminate the interpolation inaccuracies associated with the Still equation. This approach, which we call boundary-integral-based electrostatic estimation by the CFA (BIBEE/CFA), is most accurate when the molecular charge distribution generates a smooth normal displacement field at the solute-solvent boundary, and CFA-based GB methods perform similarly. Conversely, both methods are least accurate for charge distributions that give rise to rapidly varying or highly localized normal displacement fields. Supporting this analysis are comparisons of the reaction-potential matrices calculated using GB methods and boundary-element-method (BEM) simulations. An approximation similar to BIBEE/CFA exhibits complementary behavior, with superior accuracy for charge distributions that generate rapidly varying normal fields and poorer accuracy for distributions that produce smooth fields. This approximation, BIBEE by preconditioning (BIBEE/P), essentially generates initial guesses for preconditioned Krylov-subspace iterative BEMs. Thus, iterative refinement of the BIBEE/P results recovers the BEM solution; excellent agreement

The multigrid preconditioned conjugate gradient method

NASA Technical Reports Server (NTRS)

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.

Highly Entangled, Non-random Subspaces of Tensor Products from Quantum Groups

NASA Astrophysics Data System (ADS)

Brannan, Michael; Collins, Benoît

2018-03-01

In this paper we describe a class of highly entangled subspaces of a tensor product of finite-dimensional Hilbert spaces arising from the representation theory of free orthogonal quantum groups. We determine their largest singular values and obtain lower bounds for the minimum output entropy of the corresponding quantum channels. An application to the construction of d-positive maps on matrix algebras is also presented.

The time dependence of the effect of ischemic preconditioning on successive sprint swimming performance.

PubMed

Lisbôa, Felipe D; Turnes, Tiago; Cruz, Rogério S O; Raimundo, João A G; Pereira, Gustavo S; Caputo, Fabrizio

2017-05-01

The present study aimed to determine the effects of ischemic preconditioning on performance in three successive 50-m swimming trials and to measure stroke rate, stroke length and blood lactate accumulation. Counterbalanced, repeated-measures cross-over study. On two separate days, eleven competitive male swimmers (20±3 years, 182±5cm, 77±5kg) performed three successive 50-m trials in a 50-m swimming pool, preceded by intermittent bilateral cuff inflation (4× 5-min of blood flow restriction+5-min of cuff deflation) at either 220 for thighs and 180mmHg for arms (ischemic preconditioning) or 20mmHg for both limbs (control-treatment). The 50-m trials were conducted 1-, 2-, and 8-h after the procedure. While no ergogenic effect of ischemic preconditioning was observed for 1-h (0.4%, 95% confidence limits of ±0.6%, p=0.215), there were clear beneficial effects of ischemic preconditioning on 2- and 8-h (1.0% and 1.2%, respectively; 95% confidence limits of ±0.6% in both cases, p≤0.002). Furthermore, ischemic preconditioning increased blood lactate accumulation in 2-(p<0.001) and 8-h (p=0.010) and stroke rate for 2- and 8-h in specific 10-m segments (p<0.05). These findings suggest a time-dependent effect of ischemic preconditioning on 50-m swimming performance for competitive athletes, with the time window of the beneficial effect starting after about 2-h and lasting for at least 8-h after ischemic preconditioning. This change in performance was accompanied by an increase in blood lactate accumulation and faster strokes in front crawl. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

NASA Astrophysics Data System (ADS)

Chen, Xudong

2010-07-01

This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging.

Molecular mechanisms of liver preconditioning

PubMed Central

Alchera, Elisa; Dal Ponte, Caterina; Imarisio, Chiara; Albano, Emanuele; Carini, Rita

2010-01-01

Ischemia/reperfusion (I/R) injury still represents an important cause of morbidity following hepatic surgery and limits the use of marginal livers in hepatic transplantation. Transient blood flow interruption followed by reperfusion protects tissues against damage induced by subsequent I/R. This process known as ischemic preconditioning (IP) depends upon intrinsic cytoprotective systems whose activation can inhibit the progression of irreversible tissue damage. Compared to other organs, liver IP has additional features as it reduces inflammation and promotes hepatic regeneration. Our present understanding of the molecular mechanisms involved in liver IP is still largely incomplete. Experimental studies have shown that the protective effects of liver IP are triggered by the release of adenosine and nitric oxide and the subsequent activation of signal networks involving protein kinases such as phosphatidylinositol 3-kinase, protein kinase C δ/ε and p38 MAP kinase, and transcription factors such as signal transducer and activator of transcription 3, nuclear factor-κB and hypoxia-inducible factor 1. This article offers an overview of the molecular events underlying the preconditioning effects in the liver and points to the possibility of developing pharmacological approaches aimed at activating the intrinsic protective systems in patients undergoing liver surgery. PMID:21182220

Impact of remote ischemic preconditioning on wound healing in small bowel anastomoses

PubMed Central

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

Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations.

PubMed

Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E

2018-06-12

We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).

Multiple fault separation and detection by joint subspace learning for the health assessment of wind turbine gearboxes

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Zi, Yanyang; Yan, Ruqiang

2017-09-01

The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.

Redox signaling in remote ischemic preconditioning-induced cardioprotection: Evidences and mechanisms.

PubMed

Singh, Lovedeep; Randhawa, Puneet Kaur; Singh, Nirmal; Jaggi, Amteshwar Singh

2017-08-15

Reactive oxygen species are the reactive molecules that are derived from molecular oxygen and play an important role as redox signaling molecules to confer cardioprotection. Various scientists have demonstrated the key role of redox signaling in cardioprotection by showing a transient increase in their levels during remote ischemic preconditioning (RIPC) phase. The transient increase in reactive oxygen species levels during remote preconditioning phase may take place either through activation of K ATP channels or through increased nitric oxide (NO) production. A transient increase in reactive oxygen species during preconditioning may also increase the expression of heat shock proteins (HSP), the level of antioxidant enzymes and decrease the expression of inflammatory genes (Egr-1) during ischemia-reperfusion phase to confer cardioprotection. The present review describes the role of redox signaling in RIPC-induced cardioprotective effect with possible mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient Multi-Stage Time Marching for Viscous Flows via Local Preconditioning

NASA Technical Reports Server (NTRS)

Kleb, William L.; Wood, William A.; vanLeer, Bram

1999-01-01

A new method has been developed to accelerate the convergence of explicit time-marching, laminar, Navier-Stokes codes through the combination of local preconditioning and multi-stage time marching optimization. Local preconditioning is a technique to modify the time-dependent equations so that all information moves or decays at nearly the same rate, thus relieving the stiffness for a system of equations. Multi-stage time marching can be optimized by modifying its coefficients to account for the presence of viscous terms, allowing larger time steps. We show it is possible to optimize the time marching scheme for a wide range of cell Reynolds numbers for the scalar advection-diffusion equation, and local preconditioning allows this optimization to be applied to the Navier-Stokes equations. Convergence acceleration of the new method is demonstrated through numerical experiments with circular advection and laminar boundary-layer flow over a flat plate.

Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

2017-09-01

It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus

Subspace projection method for unstructured searches with noisy quantum oracles using a signal-based quantum emulation device

NASA Astrophysics Data System (ADS)

La Cour, Brian R.; Ostrove, Corey I.

2017-01-01

This paper describes a novel approach to solving unstructured search problems using a classical, signal-based emulation of a quantum computer. The classical nature of the representation allows one to perform subspace projections in addition to the usual unitary gate operations. Although bandwidth requirements will limit the scale of problems that can be solved by this method, it can nevertheless provide a significant computational advantage for problems of limited size. In particular, we find that, for the same number of noisy oracle calls, the proposed subspace projection method provides a higher probability of success for finding a solution than does an single application of Grover's algorithm on the same device.

AMP-activated protein kinase (AMPK)-induced preconditioning in primary cortical neurons involves activation of MCL-1.

PubMed

Anilkumar, Ujval; Weisová, Petronela; Düssmann, Heiko; Concannon, Caoimhín G; König, Hans-Georg; Prehn, Jochen H M

2013-03-01

Neuronal preconditioning is a phenomenon where a previous exposure to a sub-lethal stress stimulus increases the resistance of neurons towards a second, normally lethal stress stimulus. Activation of the energy stress sensor, AMP-activated protein kinase (AMPK) has been shown to contribute to the protective effects of ischaemic and mitochondrial uncoupling-induced preconditioning in neurons, however, the molecular basis of AMPK-mediated preconditioning has been less well characterized. We investigated the effect of AMPK preconditioning using 5-aminoimidazole-4-carboxamide riboside (AICAR) in a model of NMDA-mediated excitotoxic injury in primary mouse cortical neurons. Activation of AMPK with low concentrations of AICAR (0.1 mM for 2 h) induced a transient increase in AMPK phosphorylation, protecting neurons against NMDA-induced excitotoxicity. Analysing potential targets of AMPK activation, demonstrated a marked increase in mRNA expression and protein levels of the anti-apoptotic BCL-2 family protein myeloid cell leukaemia sequence 1 (MCL-1) in AICAR-preconditioned neurons. Interestingly, over-expression of MCL-1 protected neurons against NMDA-induced excitotoxicity while MCL-1 gene silencing abolished the effect of AICAR preconditioning. Monitored intracellular Ca²⁺ levels during NMDA excitation revealed that MCL-1 over-expressing neurons exhibited improved bioenergetics and markedly reduced Ca²⁺ elevations, suggesting a potential mechanism through which MCL-1 confers neuroprotection. This study identifies MCL-1 as a key effector of AMPK-induced preconditioning in neurons. © 2012 International Society for Neurochemistry.

The in vitro preconditioning of myoblasts to enhance subsequent survival in an in vivo tissue engineering chamber model.

PubMed

Tilkorn, Daniel J; Davies, E Michele; Keramidaris, Effie; Dingle, Aaron M; Gerrand, Yi-Wen; Taylor, Caroline J; Han, Xiao Lian; Palmer, Jason A; Penington, Anthony J; Mitchell, Christina A; Morrison, Wayne A; Dusting, Gregory J; Mitchell, Geraldine M

2012-05-01

The effects of in vitro preconditioning protocols on the ultimate survival of myoblasts implanted in an in vivo tissue engineering chamber were examined. In vitro testing: L6 myoblasts were preconditioned by heat (42 °C; 1.5 h); hypoxia (<8% O(2); 1.5 h); or nitric oxide donors: S-nitroso-N-acetylpenicillamine (SNAP, 200 μM, 1.5 h) or 1-[N-(2-aminoethyl)-N-(2-aminoethyl)amino]-diazen-1-ium-1,2-diolate (DETA-NONOate, 500 μM, 7 h). Following a rest phase preconditioned cells were exposed to 24 h hypoxia, and demonstrated minimal overall cell loss, whilst controls (not preconditioned, but exposed to 24 h hypoxia) demonstrated a 44% cell loss. Phosphoimmunoblot analysis of pro-survival signaling pathways revealed significant activation of serine threonine kinase Akt with DETA-NONOate (p < 0.01) and heat preconditioning (p < 0.05). DETA-NONOate also activated ERK 1/2 signaling (p < 0.05). In vivo implantation: 100,000 preconditioned (heat, hypoxia, or DETA-NONOate) myoblasts were implanted in SCID mouse tissue engineering chambers. 100,000 (not preconditioned) myoblasts were implanted in control chambers. At 3 weeks, morphometric assessment of surviving myoblasts indicated myoblast percent volume (p = 0.012) and myoblasts/mm(2) (p = 0.0005) overall significantly increased in preconditioned myoblast chambers compared to control, with DETA-NONOate-preconditioned myoblasts demonstrating the greatest increase in survival (p = 0.007 and p = 0.001 respectively). DETA-NONOate therefore has potential therapeutic benefits to significantly improve survival of transplanted cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

40 CFR 86.132-00 - Vehicle preconditioning.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Vehicle preconditioning. 86.132-00 Section 86.132-00 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS...] (iii) If a manufacturer has concerns about fuel effects on adaptive memory systems, a manufacturer may...

40 CFR 86.1232-96 - Vehicle preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... preconditioned separately. If production evaporative canisters are equipped with a functional service port... production evaporative canisters are equipped with a functional service port designed for vapor load or purge... provides at least a 4:1 safety factor against the lean flammability limit. (iii) The FID hydrocarbon...

Nested Conjugate Gradient Algorithm with Nested Preconditioning for Non-linear Image Restoration.

PubMed

Skariah, Deepak G; Arigovindan, Muthuvel

2017-06-19

We develop a novel optimization algorithm, which we call Nested Non-Linear Conjugate Gradient algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient (CG) iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT based non-iterative preconditioner. We prove that the method converges to a stationary point for both convex and non-convex regularization functionals. We demonstrate experimentally that proposed method outperforms the well-known majorization-minimization method used for convex regularization, and a non-convex inertial-proximal method for non-convex regularization functional.

Mechanisms of acetylcholine- and bradykinin-induced preconditioning.

PubMed

Critz, Stuart D; Cohen, Michael V; Downey, James M

2005-01-01

Acetylcholine (ACh) and bradykinin (BK) are potent pharmacological agents which mimic ischemic preconditioning (IPC) enabling hearts to resist infarction during a subsequent period of ischemia. The cardioprotective pathways activated by BK but not ACh may also protect when activated at reperfusion. ACh and BK stimulate Gi/o-linked receptors and ultimately mediate protection by opening mitochondrial ATP-sensitive potassium channels with the generation of reactive oxygen species that act as second messengers to activate protein kinase C (PKC). There appear to be key differences, however, in the pathways prior to potassium channel opening for these two receptors. This review aims to summarize what is currently known about pharmacological preconditioning by ACh and BK with an emphasis on differences that are seen in the signal transduction cascades. Understanding the cellular basis of protection by ACh and BK is a critical step towards developing pharmacological agents that will prevent infarction during ischemia resulting from coronary occlusion or heart attack.

Effect of non-invasive remote ischemic preconditioning on intra-renal perfusion in volunteers.

PubMed

Robert, René; Vinet, Mathieu; Jamet, Angéline; Coudroy, Rémi

2017-06-01

Remote ischemic preconditioning may attenuate renal injury and protect the kidney during subsequent inflammatory or ischemic stress. However, the mechanism of such a protection is not well understood. The aim of this study was to investigate the impact of remote ischemic preconditioning on renal resistivity index (RRI) in nine healthy volunteers. In six volunteers, four cycles of 4-min inflation of a blood pressure cuff were applied to one upper arm, followed by 4-min reperfusion with the cuff deflated. RRI was determined using Doppler echography during each cuff deflated period. Measures were also performed in three volunteers without preconditioning. The median value of RRI significantly decreased progressively from 0.59 [0.53-0.62] before the remote conditioning (baseline) to 0.49 [0.46-0.53] at the end of the experiment (p < 0.001) whereas there was no change in controls. In this study, for the first time, we have clearly shown in a small group of subjects that remote ischemic preconditioning can induce a significantly decrease in RRI through increased intra-renal perfusion.

Preconditioned Alternating Projection Algorithms for Maximum a Posteriori ECT Reconstruction

PubMed Central

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 constrain 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 preconditioned alternating projection algorithm. 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. PMID:23271835

Visual characterization and diversity quantification of chemical libraries: 2. Analysis and selection of size-independent, subspace-specific diversity indices.

PubMed

Colliandre, Lionel; Le Guilloux, Vincent; Bourg, Stephane; Morin-Allory, Luc

2012-02-27

High Throughput Screening (HTS) is a standard technique widely used to find hit compounds in drug discovery projects. The high costs associated with such experiments have highlighted the need to carefully design screening libraries in order to avoid wasting resources. Molecular diversity is an established concept that has been used to this end for many years. In this article, a new approach to quantify the molecular diversity of screening libraries is presented. The approach is based on the Delimited Reference Chemical Subspace (DRCS) methodology, a new method that can be used to delimit the densest subspace spanned by a reference library in a reduced 2D continuous space. A total of 22 diversity indices were implemented or adapted to this methodology, which is used here to remove outliers and obtain a relevant cell-based partition of the subspace. The behavior of these indices was assessed and compared in various extreme situations and with respect to a set of theoretical rules that a diversity function should satisfy when libraries of different sizes have to be compared. Some gold standard indices are found inappropriate in such a context, while none of the tested indices behave perfectly in all cases. Five DRCS-based indices accounting for different aspects of diversity were finally selected, and a simple framework is proposed to use them effectively. Various libraries have been profiled with respect to more specific subspaces, which further illustrate the interest of the method.

Hybrid preconditioning for iterative diagonalization of ill-conditioned generalized eigenvalue problems in electronic structure calculations

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

Cai, Yunfeng, E-mail: yfcai@math.pku.edu.cn; Department of Computer Science, University of California, Davis 95616; Bai, Zhaojun, E-mail: bai@cs.ucdavis.edu

2013-12-15

The iterative diagonalization of a sequence of large ill-conditioned generalized eigenvalue problems is a computational bottleneck in quantum mechanical methods employing a nonorthogonal basis for ab initio electronic structure calculations. We propose a hybrid preconditioning scheme to effectively combine global and locally accelerated preconditioners for rapid iterative diagonalization of such eigenvalue problems. In partition-of-unity finite-element (PUFE) pseudopotential density-functional calculations, employing a nonorthogonal basis, we show that the hybrid preconditioned block steepest descent method is a cost-effective eigensolver, outperforming current state-of-the-art global preconditioning schemes, and comparably efficient for the ill-conditioned generalized eigenvalue problems produced by PUFE as the locally optimal blockmore » preconditioned conjugate-gradient method for the well-conditioned standard eigenvalue problems produced by planewave methods.« less

Integrity of Cerebellar Fastigial Nucleus Intrinsic Neurons Is Critical for the Global Ischemic Preconditioning

PubMed Central

Regnier-Golanov, Angelique S.; Britz, Gavin W.

2017-01-01

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”. PMID:28934119

Neuroprotective Effects of Peptides during Ischemic Preconditioning.

PubMed

Zarubina, I V; Shabanov, P D

2016-02-01

Experiments on rats showed that neurospecific protein preparations reduce the severity of neurological deficit, restore the structure of individual behavior of the animals with different hypoxia tolerance, and exert antioxidant action during chronic ischemic damage to the brain unfolding during the early and late phases of ischemic preconditioning.

A Subspace Semi-Definite programming-based Underestimation (SSDU) method for stochastic global optimization in protein docking*

PubMed Central

Nan, Feng; Moghadasi, Mohammad; Vakili, Pirooz; Vajda, Sandor; Kozakov, Dima; Ch. Paschalidis, Ioannis

2015-01-01

We propose a new stochastic global optimization method targeting protein docking problems. The method is based on finding a general convex polynomial underestimator to the binding energy function in a permissive subspace that possesses a funnel-like structure. We use Principal Component Analysis (PCA) to determine such permissive subspaces. The problem of finding the general convex polynomial underestimator is reduced into the problem of ensuring that a certain polynomial is a Sum-of-Squares (SOS), which can be done via semi-definite programming. The underestimator is then used to bias sampling of the energy function in order to recover a deep minimum. We show that the proposed method significantly improves the quality of docked conformations compared to existing methods. PMID:25914440

Improving M-SBL for Joint Sparse Recovery Using a Subspace Penalty

NASA Astrophysics Data System (ADS)

Ye, Jong Chul; Kim, Jong Min; Bresler, Yoram

2015-12-01

The multiple measurement vector problem (MMV) is a generalization of the compressed sensing problem that addresses the recovery of a set of jointly sparse signal vectors. One of the important contributions of this paper is to reveal that the seemingly least related state-of-art MMV joint sparse recovery algorithms - M-SBL (multiple sparse Bayesian learning) and subspace-based hybrid greedy algorithms - have a very important link. More specifically, we show that replacing the $\\log\\det(\\cdot)$ term in M-SBL by a rank proxy that exploits the spark reduction property discovered in subspace-based joint sparse recovery algorithms, provides significant improvements. In particular, if we use the Schatten-$p$ quasi-norm as the corresponding rank proxy, the global minimiser of the proposed algorithm becomes identical to the true solution as $p \\rightarrow 0$. Furthermore, under the same regularity conditions, we show that the convergence to a local minimiser is guaranteed using an alternating minimization algorithm that has closed form expressions for each of the minimization steps, which are convex. Numerical simulations under a variety of scenarios in terms of SNR, and condition number of the signal amplitude matrix demonstrate that the proposed algorithm consistently outperforms M-SBL and other state-of-the art algorithms.

The role of adenosine in preconditioning by brief pressure overload in rats.

PubMed

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 < 0.001). Pretreatment with 8-(p-sulfophenyl)-theophylline (SPT), an inhibitor of adenosine receptors, did not significantly limit the protection by pressure overload and ischemic preconditioning (18.3 ± 1.5% and 18.2 ± 2.0%, respectively, p < 0.001). SPT itself did not affect the extent of infarct (25.4 ± 2.0%). The hemodynamics, area at risk and mortality were not significantly different among all groups of animals. Brief pressure 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.

Remote ischemic preconditioning and endothelial function in patients with acute myocardial infarction and primary PCI.

PubMed

Manchurov, Vladimir; Ryazankina, Nadezda; Khmara, Tatyana; Skrypnik, Dmitry; Reztsov, Roman; Vasilieva, Elena; Shpektor, Alexander

2014-07-01

Remote ischemic preconditioning by transient limb ischemia reduces myocardial ischemia-reperfusion injury in patients undergoing percutaneous coronary intervention. The aim of the study we report here was to assess the effect of remote ischemic preconditioning on endothelial function in patients with acute myocardial infarction who underwent primary percutaneous coronary intervention. Forty-eight patients with acute myocardial infarction were enrolled. All participants were randomly divided into 2 groups. In Group I (n = 23), remote ischemic preconditioning was performed before primary percutaneous coronary intervention (intermittent arm ischemia-reperfusion through 4 cycles of 5-minute inflation and 5-minute deflation of a blood-pressure cuff to 200 mm Hg). In Group II (n = 25), standard percutaneous coronary intervention without preconditioning was performed. We assessed endothelial function using the flow-mediated dilation test on baseline, then within 1-3 hours after percutaneous coronary intervention, and again on days 2 and 7 after percutaneous coronary intervention. The brachial artery flow-mediated dilation results were significantly higher on the first day after primary percutaneous coronary intervention in the preconditioning group (Group I) than in the control group (Group II) (12.1% vs 0.0%, P = .03, and 11.1% vs 6.3%, P = .016, respectively), and this difference remained on the seventh day (12.3% vs 7.4%, P = .0005, respectively). We demonstrated for the first time that remote ischemic preconditioning before primary percutaneous coronary intervention significantly improves endothelial function in patients with acute myocardial infarction, and this effect remains constant for at least a week. We suppose that the improvement of endothelial function may be one of the possible explanations of the effect of remote ischemic preconditioning. Copyright © 2014 Elsevier Inc. All rights reserved.

40 CFR 86.132-96 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... outdoors awaiting testing, to prevent unusual loading of the canisters. During this time care must be taken... idle again for 1 minute. (H) After the vehicle is turned off the last time, it may be tested for... preconditioned according to the following procedure. For vehicles with multiple canisters in a series...

Galilean-invariant preconditioned central-moment lattice Boltzmann method without cubic velocity errors for efficient steady flow simulations

NASA Astrophysics Data System (ADS)

Hajabdollahi, Farzaneh; Premnath, Kannan N.

2018-05-01

Lattice Boltzmann (LB) models used for the computation of fluid flows represented by the Navier-Stokes (NS) equations on standard lattices can lead to non-Galilean-invariant (GI) viscous stress involving cubic velocity errors. This arises from the dependence of their third-order diagonal moments on the first-order moments for standard lattices, and strategies have recently been introduced to restore Galilean invariance without such errors using a modified collision operator involving corrections to either the relaxation times or the moment equilibria. Convergence acceleration in the simulation of steady flows can be achieved by solving the preconditioned NS equations, which contain a preconditioning parameter that can be used to tune the effective sound speed, and thereby alleviating the numerical stiffness. In the present paper, we present a GI formulation of the preconditioned cascaded central-moment LB method used to solve the preconditioned NS equations, which is free of cubic velocity errors on a standard lattice, for steady flows. A Chapman-Enskog analysis reveals the structure of the spurious non-GI defect terms and it is demonstrated that the anisotropy of the resulting viscous stress is dependent on the preconditioning parameter, in addition to the fluid velocity. It is shown that partial correction to eliminate the cubic velocity defects is achieved by scaling the cubic velocity terms in the off-diagonal third-order moment equilibria with the square of the preconditioning parameter. Furthermore, we develop additional corrections based on the extended moment equilibria involving gradient terms with coefficients dependent locally on the fluid velocity and the preconditioning parameter. Such parameter dependent corrections eliminate the remaining truncation errors arising from the degeneracy of the diagonal third-order moments and fully restore Galilean invariance without cubic defects for the preconditioned LB scheme on a standard lattice. Several

The effect of brain death in rat steatotic and non-steatotic liver transplantation with previous ischemic preconditioning.

PubMed

Jiménez-Castro, Mónica B; Meroño, Noelia; Mendes-Braz, Mariana; Gracia-Sancho, Jordi; Martínez-Carreres, Laia; Cornide-Petronio, Maria Eugenia; Casillas-Ramirez, Araní; Rodés, Juan; Peralta, Carmen

2015-01-01

Most liver grafts undergoing transplantation derive from brain dead donors, which may also show hepatic steatosis, being both characteristic risk factors in liver transplantation. Ischemic preconditioning shows benefits when applied in non-brain dead clinical situations like hepatectomies, whereas it has been less promising in the transplantation from brain dead patients. This study examined how brain death affects preconditioned steatotic and non-steatotic liver grafts undergoing transplantation. Steatotic and non-steatotic grafts from non-brain dead and brain dead-donors were cold stored for 6h and then transplanted. After 2, 4, and 16 h of reperfusion, hepatic damage was analysed. In addition, two therapeutic strategies, ischemic preconditioning and/or acetylcholine pre-treatment, and their underlying mechanisms were characterized. Preconditioning benefits in non-brain dead donors were associated with nitric oxide and acetylcholine generation. In brain dead donors, preconditioning generated nitric oxide but did not promote acetylcholine upregulation, and this resulted in inflammation and damage. Acetylcholine treatment in brain dead donors, through PKC, increased antioxidants and reduced lipid peroxidation, nitrotyrosines and neutrophil accumulation, altogether protecting against damage. The combination of acetylcholine and preconditioning conferred stronger protection against damage, oxidative stress and neutrophil accumulation than acetylcholine treatment alone. These superior beneficial effects were due to a selective preconditioning-mediated generation of nitric oxide and regulation of PPAR and TLR4 pathways, which were not observed when acetylcholine was administered alone. Our findings propose the combination of acetylcholine+preconditioning as a feasible and highly protective strategy to reduce the adverse effects of brain death and to ultimately improve liver graft quality. Copyright © 2014 European Association for the Study of the Liver. Published by

M-step preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

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.

Blind equalization and automatic modulation classification based on subspace for subcarrier MPSK optical communications

NASA Astrophysics Data System (ADS)

Chen, Dan; Guo, Lin-yuan; Wang, Chen-hao; Ke, Xi-zheng

2017-07-01

Equalization can compensate channel distortion caused by channel multipath effects, and effectively improve convergent of modulation constellation diagram in optical wireless system. In this paper, the subspace blind equalization algorithm is used to preprocess M-ary phase shift keying (MPSK) subcarrier modulation signal in receiver. Mountain clustering is adopted to get the clustering centers of MPSK modulation constellation diagram, and the modulation order is automatically identified through the k-nearest neighbor (KNN) classifier. The experiment has been done under four different weather conditions. Experimental results show that the convergent of constellation diagram is improved effectively after using the subspace blind equalization algorithm, which means that the accuracy of modulation recognition is increased. The correct recognition rate of 16PSK can be up to 85% in any kind of weather condition which is mentioned in paper. Meanwhile, the correct recognition rate is the highest in cloudy and the lowest in heavy rain condition.

PIXIE3D: A Parallel, Implicit, eXtended MHD 3D Code

NASA Astrophysics Data System (ADS)

Chacon, Luis

2006-10-01

We report on the development of PIXIE3D, a 3D parallel, fully implicit Newton-Krylov extended MHD code in general curvilinear geometry. PIXIE3D employs a second-order, finite-volume-based spatial discretization that satisfies remarkable properties such as being conservative, solenoidal in the magnetic field to machine precision, non-dissipative, and linearly and nonlinearly stable in the absence of physical dissipation. PIXIE3D employs fully-implicit Newton-Krylov methods for the time advance. Currently, second-order implicit schemes such as Crank-Nicolson and BDF2 (2^nd order backward differentiation formula) are available. PIXIE3D is fully parallel (employs PETSc for parallelism), and exhibits excellent parallel scalability. A parallel, scalable, MG preconditioning strategy, based on physics-based preconditioning ideas, has been developed for resistive MHD, and is currently being extended to Hall MHD. In this poster, we will report on progress in the algorithmic formulation for extended MHD, as well as the the serial and parallel performance of PIXIE3D in a variety of problems and geometries. L. Chac'on, Comput. Phys. Comm., 163 (3), 143-171 (2004) L. Chac'on et al., J. Comput. Phys. 178 (1), 15- 36 (2002); J. Comput. Phys., 188 (2), 573-592 (2003) L. Chac'on, 32nd EPS Conf. Plasma Physics, Tarragona, Spain, 2005 L. Chac'on et al., 33rd EPS Conf. Plasma Physics, Rome, Italy, 2006

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-01-01

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method. PMID:24573313

Moving Sound Source Localization Based on Sequential Subspace Estimation in Actual Room Environments

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Suyama, Kenji

This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-02-25

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method.

Development of Subspace-based Hybrid Monte Carlo-Deterministric Algorithms for Reactor Physics Calculations

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

Abdel-Khalik, Hany S.; Zhang, Qiong

2014-05-20

The development of hybrid Monte-Carlo-Deterministic (MC-DT) approaches, taking place over the past few decades, have primarily focused on shielding and detection applications where the analysis requires a small number of responses, i.e. at the detector locations(s). This work further develops a recently introduced global variance reduction approach, denoted by the SUBSPACE approach is designed to allow the use of MC simulation, currently limited to benchmarking calculations, for routine engineering calculations. By way of demonstration, the SUBSPACE approach is applied to assembly level calculations used to generate the few-group homogenized cross-sections. These models are typically expensive and need to be executedmore » in the order of 10 3 - 10 5 times to properly characterize the few-group cross-sections for downstream core-wide calculations. Applicability to k-eigenvalue core-wide models is also demonstrated in this work. Given the favorable results obtained in this work, we believe the applicability of the MC method for reactor analysis calculations could be realized in the near future.« less

MIBPB: A software package for electrostatic analysis

PubMed Central

Chen, Duan; Chen, Zhan; Chen, Changjun; Geng, Weihua; Wei, Guo-Wei

2010-01-01

The Poisson-Boltzmann equation (PBE) is an established model for the electrostatic analysis of biomolecules. The development of advanced computational techniques for the solution of the PBE has been an important topic in the past two decades. This paper presents a matched interface and boundary (MIB) based PBE software package, the MIBPB solver, for electrostatic analysis. The MIBPB has a unique feature that it is the first interface technique based PBE solver that rigorously enforces the solution and flux continuity conditions at the dielectric interface between the biomolecule and the solvent. For protein molecular surfaces which may possess troublesome geometrical singularities, the MIB scheme makes the MIBPB by far the only existing PBE solver that is able to deliver the second order convergence, i.e., the accuracy increases four times when the mesh size is halved. The MIBPB method is also equipped with a Dirichlet-to-Neumann mapping (DNM) technique, that builds a Green's function approach to analytically resolve the singular charge distribution in biomolecules in order to obtain reliable solutions at meshes as coarse as 1Å — while it usually takes other traditional PB solvers 0.25Å to reach similar level of reliability. The present work further accelerates the rate of convergence of linear equation systems resulting from the MIBPB by utilizing the Krylov subspace (KS) techniques. Condition numbers of the MIBPB matrices are significantly reduced by using appropriate Krylov subspace solver and preconditioner combinations. Both linear and nonlinear PBE solvers in the MIBPB package are tested by protein-solvent solvation energy calculations and analysis of salt effects on protein-protein binding energies, respectively. PMID:20845420

Parallel computing techniques for rotorcraft aerodynamics

NASA Astrophysics Data System (ADS)

Ekici, Kivanc

The modification of unsteady three-dimensional Navier-Stokes codes for application on massively parallel and distributed computing environments is investigated. The Euler/Navier-Stokes code TURNS (Transonic Unsteady Rotor Navier-Stokes) was chosen as a test bed because of its wide use by universities and industry. For the efficient implementation of TURNS on parallel computing systems, two algorithmic changes are developed. First, main modifications to the implicit operator, Lower-Upper Symmetric Gauss Seidel (LU-SGS) originally used in TURNS, is performed. Second, application of an inexact Newton method, coupled with a Krylov subspace iterative method (Newton-Krylov method) is carried out. Both techniques have been tried previously for the Euler equations mode of the code. In this work, we have extended the methods to the Navier-Stokes mode. Several new implicit operators were tried because of convergence problems of traditional operators with the high cell aspect ratio (CAR) grids needed for viscous calculations on structured grids. Promising results for both Euler and Navier-Stokes cases are presented for these operators. For the efficient implementation of Newton-Krylov methods to the Navier-Stokes mode of TURNS, efficient preconditioners must be used. The parallel implicit operators used in the previous step are employed as preconditioners and the results are compared. The Message Passing Interface (MPI) protocol has been used because of its portability to various parallel architectures. It should be noted that the proposed methodology is general and can be applied to several other CFD codes (e.g. OVERFLOW).

Finding Chemical Reaction Paths with a Multilevel Preconditioning Protocol

PubMed Central

2015-01-01

Finding transition paths for chemical reactions can be computationally costly owing to the level of quantum-chemical theory needed for accuracy. Here, we show that a multilevel preconditioning scheme that was recently introduced (Tempkin et al. J. Chem. Phys.2014, 140, 184114) can be used to accelerate quantum-chemical string calculations. We demonstrate the method by finding minimum-energy paths for two well-characterized reactions: tautomerization of malonaldehyde and Claissen rearrangement of chorismate to prephanate. For these reactions, we show that preconditioning density functional theory (DFT) with a semiempirical method reduces the computational cost for reaching a converged path that is an optimum under DFT by several fold. The approach also shows promise for free energy calculations when thermal noise can be controlled. PMID:25516726

Investigation of Reperfusion Injury and Ischemic Preconditioning in Microsurgry

PubMed Central

Wang, Wei Zhong

2008-01-01

Ischemia/reperfusion (I/R) is inevitable in many vascular and musculoskeletal traumas, diseases, free tissue transfers, and during time-consuming reconstructive surgeries in the extremities. Salvage of a prolonged ischemic extremity or flap still remains a challenge for the microvascular surgeon. One of the common complications after microsurgery is I/R-induced tissue death or I/R injury. Twenty years after the discovery, ischemic preconditioning (IPC) has emerged as a powerful method for attenuating I/R injury in a variety of organs or tissues. However, its therapeutic expectations still need to be fulfilled. In this article, the author reviews some important experimental evidences of I/R injury as well as preconditioning-induced protection in the fields relevant to microsurgery. PMID:18946882

Implicit Plasma Kinetic Simulation Using The Jacobian-Free Newton-Krylov Method

NASA Astrophysics Data System (ADS)

Taitano, William; Knoll, Dana; Chacon, Luis

2009-11-01

The use of fully implicit time integration methods in kinetic simulation is still area of algorithmic research. A brute-force approach to simultaneously including the field equations and the particle distribution function would result in an intractable linear algebra problem. A number of algorithms have been put forward which rely on an extrapolation in time. They can be thought of as linearly implicit methods or one-step Newton methods. However, issues related to time accuracy of these methods still remain. We are pursuing a route to implicit plasma kinetic simulation which eliminates extrapolation, eliminates phase-space from the linear algebra problem, and converges the entire nonlinear system within a time step. We accomplish all this using the Jacobian-Free Newton-Krylov algorithm. The original research along these lines considered particle methods to advance the distribution function [1]. In the current research we are advancing the Vlasov equations on a grid. Results will be presented which highlight algorithmic details for single species electrostatic problems and coupled ion-electron electrostatic problems. [4pt] [1] H. J. Kim, L. Chac'on, G. Lapenta, ``Fully implicit particle in cell algorithm,'' 47th Annual Meeting of the Division of Plasma Physics, Oct. 24-28, 2005, Denver, CO

40 CFR 86.132-00 - Vehicle preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 18 2011-07-01 2011-07-01 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 86.132-96 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 19 2012-07-01 2012-07-01 false Vehicle preconditioning. 86.132-96... (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 86.132-96 - Vehicle preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 19 2014-07-01 2014-07-01 false Vehicle preconditioning. 86.132-96... (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 86.132-00 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 19 2013-07-01 2013-07-01 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 86.132-00 - Vehicle preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 19 2014-07-01 2014-07-01 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 86.132-00 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 19 2012-07-01 2012-07-01 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...

Revealing Preconditions for Trustful Collaboration in CSCL

ERIC Educational Resources Information Center

Gerdes, Anne

2010-01-01

This paper analyses preconditions for trust in virtual learning environments. The concept of trust is discussed with reference to cases reporting trust in cyberspace and through a philosophical clarification holding that trust in the form of self-surrender is a common characteristic of all human co-existence. In virtual learning environments,…

33 CFR 183.220 - Preconditioning for tests.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) BOATING SAFETY BOATS AND ASSOCIATED EQUIPMENT Flotation Requirements for Outboard Boats Rated for Engines of More Than 2 Horsepower General § 183.220 Preconditioning for tests. A boat must meet the... boat. (b) The boat must be loaded with a quantity of weight that, when submerged, is equal to the sum...

Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing

NASA Astrophysics Data System (ADS)

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

2013-12-01

Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for

PRECONDITIONED CONJUGATE-GRADIENT 2 (PCG2), a computer program for solving ground-water flow equations

USGS Publications Warehouse

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.

40 CFR 1066.407 - Vehicle preparation and preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Vehicle preparation and...) AIR POLLUTION CONTROLS VEHICLE-TESTING PROCEDURES Vehicle Preparation and Running a Test § 1066.407 Vehicle preparation and preconditioning. This section describes steps to take before measuring exhaust...

40 CFR 1066.407 - Vehicle preparation and preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Vehicle preparation and...) AIR POLLUTION CONTROLS VEHICLE-TESTING PROCEDURES Vehicle Preparation and Running a Test § 1066.407 Vehicle preparation and preconditioning. This section describes steps to take before measuring exhaust...

40 CFR 86.532-78 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle shall be moved to the test area and the following operations performed: (1) The fuel tank(s) shall be drained through the provided fuel tank(s) drain(s) and charged with the specified test fuel, § 86.513, to...

40 CFR 86.532-78 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle shall be moved to the test area and the following operations performed: (1) The fuel tank(s) shall be drained through the provided fuel tank(s) drain(s) and charged with the specified test fuel, § 86.513, to...

40 CFR 86.532-78 - Vehicle preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle shall be moved to the test area and the following operations performed: (1) The fuel tank(s) shall be drained through the provided fuel tank(s) drain(s) and charged with the specified test fuel, § 86.513, to...

40 CFR 86.532-78 - Vehicle preconditioning.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle shall be moved to the test area and the following operations performed: (1) The fuel tank(s) shall be drained through the provided fuel tank(s) drain(s) and charged with the specified test fuel, § 86.513, to...

40 CFR 86.532-78 - Vehicle preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 1978 and Later New Motorcycles; Test Procedures § 86.532-78 Vehicle preconditioning. (a) The vehicle shall be moved to the test area and the following operations performed: (1) The fuel tank(s) shall be drained through the provided fuel tank(s) drain(s) and charged with the specified test fuel, § 86.513, to...

A stopping criterion for the iterative solution of partial differential equations

NASA Astrophysics Data System (ADS)

Rao, Kaustubh; Malan, Paul; Perot, J. Blair

2018-01-01

A stopping criterion for iterative solution methods is presented that accurately estimates the solution error using low computational overhead. The proposed criterion uses information from prior solution changes to estimate the error. When the solution changes are noisy or stagnating it reverts to a less accurate but more robust, low-cost singular value estimate to approximate the error given the residual. This estimator can also be applied to iterative linear matrix solvers such as Krylov subspace or multigrid methods. Examples of the stopping criterion's ability to accurately estimate the non-linear and linear solution error are provided for a number of different test cases in incompressible fluid dynamics.

Ginkgolide B preconditioning protects neurons against ischaemia-induced apoptosis.

PubMed

Wu, Xiaomei; Qian, Zhongming; Ke, Ya; Du, Fang; Zhu, Li

2009-01-01

Ischaemic preconditioning (IP) has been reported to protect the brain against subsequent lethal ischaemia, but it has not been used clinically to prevent ischaemic injury because of safety concerns. The aim of the present study was to see whether Ginkgolide B (GB) is capable of preconditioning as IP to protect neurons against ischaemic injury; if so, which mechanism is involved. Cultured mouse cortical neurons at day 8 were pre-treated with GB (120 micromol/l) for 24 hrs or exposed to short-term ischaemia (1 hr) followed by 24-hr normal culture to induce IP before being treated with severe ischaemia (5 hrs). GB and IP significantly increased cell viability, expression of hypoxia-inducible factor-1 alpha (HIF-1alpha), erythropoietin (EPO), phosphorylated Bad at serine 136 (136p-Bad) and phosphorylated glycogen synthase kinase- 3beta at serine 9 (p-GSK-3beta), and decreased the percentage of apoptotic cells and the level of active caspase-3 in severely ischaemic neurons. Moreover, LY294002 that is a specific inhibitor of phosphatidylinositol 3-kinase (PI3K) significantly reduced the enhanced expression of HIF-1alpha, EPO and 136p-Bad induced by GB and IP. These results suggest that GB, like IP in neurons, is capable of preconditioning against ischaemia-induced apoptosis, the mechanism of which may involve the PI3K signalling pathway.

Ginkgolide B preconditioning protects neurons against ischaemia-induced apoptosis

PubMed Central

Wu, Xiaomei; Qian, Zhongming; Ke, Ya; Du, Fang; Zhu, Li

2009-01-01

Ischaemic preconditioning (IP) has been reported to protect the brain against subsequent lethal ischaemia, but it has not been used clinically to prevent ischaemic injury because of safety concerns. The aim of the present study was to see whether Ginkgolide B (GB) is capable of preconditioning as IP to protect neurons against ischaemic injury; if so, which mechanism is involved. Cultured mouse cortical neurons at day 8 were pre-treated with GB (120 μmol/l) for 24 hrs or exposed to short-term ischaemia (1 hr) followed by 24-hr normal culture to induce IP before being treated with severe ischaemia (5 hrs). GB and IP significantly increased cell viability, expression of hypoxia-inducible factor-1 alpha (HIF-1α), erythropoietin (EPO), phosphorylated Bad at serine 136 (136p-Bad) and phosphorylated glycogen synthase kinase- 3β at serine 9 (p-GSK-3β), and decreased the percentage of apoptotic cells and the level of active caspase-3 in severely ischaemic neurons. Moreover, LY294002 that is a specific inhibitor of phosphatidylinositol 3-kinase (PI3K) significantly reduced the enhanced expression of HIF-1α, EPO and 136p-Bad induced by GB and IP. These results suggest that GB, like IP in neurons, is capable of preconditioning against ischaemia-induced apoptosis, the mechanism of which may involve the PI3K signalling pathway. PMID:19602048

Use of the preconditioned conjugate gradient algorithm as a generic solver for mixed-model equations in animal breeding applications.

PubMed

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

Ischemic preconditioning enhances integrity of coronary endothelial tight junctions

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

Li, Zhao; Jin, Zhu-Qiu, E-mail: zhu-qiu.jin@sdstate.edu

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 cardiacmore » 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

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.

PubMed

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.

Finding Chemical Reaction Paths with a Multilevel Preconditioning Protocol

DOE PAGES

Kale, Seyit; Sode, Olaseni; Weare, Jonathan; ...

2014-11-07

Finding transition paths for chemical reactions can be computationally costly owing to the level of quantum-chemical theory needed for accuracy. Here, we show that a multilevel preconditioning scheme that was recently introduced (Tempkin et al. J. Chem. Phys. 2014, 140, 184114) can be used to accelerate quantum-chemical string calculations. We demonstrate the method by finding minimum-energy paths for two well-characterized reactions: tautomerization of malonaldehyde and Claissen rearrangement of chorismate to prephanate. For these reactions, we show that preconditioning density functional theory (DFT) with a semiempirical method reduces the computational cost for reaching a converged path that is an optimum undermore » DFT by several fold. In conclusion, the approach also shows promise for free energy calculations when thermal noise can be controlled.« less

Shape reanalysis and sensitivities utilizing preconditioned iterative boundary solvers

NASA Technical Reports Server (NTRS)

Guru Prasad, K.; Kane, J. H.

1992-01-01

The computational advantages associated with the utilization of preconditined iterative equation solvers are quantified for the reanalysis of perturbed shapes using continuum structural boundary element analysis (BEA). Both single- and multi-zone three-dimensional problems are examined. Significant reductions in computer time are obtained by making use of previously computed solution vectors and preconditioners in subsequent analyses. The effectiveness of this technique is demonstrated for the computation of shape response sensitivities required in shape optimization. Computer times and accuracies achieved using the preconditioned iterative solvers are compared with those obtained via direct solvers and implicit differentiation of the boundary integral equations. It is concluded that this approach employing preconditioned iterative equation solvers in reanalysis and sensitivity analysis can be competitive with if not superior to those involving direct solvers.

Preconditioned characteristic boundary conditions based on artificial compressibility method for solution of incompressible flows

NASA Astrophysics Data System (ADS)

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.

Preconditioning electromyographic data for an upper extremity model using neural networks

NASA Technical Reports Server (NTRS)

Roberson, D. J.; Fernjallah, M.; Barr, R. E.; Gonzalez, R. V.

1994-01-01

A back propagation neural network has been employed to precondition the electromyographic signal (EMG) that drives a computational model of the human upper extremity. This model is used to determine the complex relationship between EMG and muscle activation, and generates an optimal muscle activation scheme that simulates the actual activation. While the experimental and model predicted results of the ballistic muscle movement are very similar, the activation function between the start and the finish is not. This neural network preconditions the signal in an attempt to more closely model the actual activation function over the entire course of the muscle movement.

A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2003-08-01

This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too.

Wavelet subspace decomposition of thermal infrared images for defect detection in artworks

NASA Astrophysics Data System (ADS)

Ahmad, M. Z.; Khan, A. A.; Mezghani, S.; Perrin, E.; Mouhoubi, K.; Bodnar, J. L.; Vrabie, V.

2016-07-01

Health of ancient artworks must be routinely monitored for their adequate preservation. Faults in these artworks may develop over time and must be identified as precisely as possible. The classical acoustic testing techniques, being invasive, risk causing permanent damage during periodic inspections. Infrared thermometry offers a promising solution to map faults in artworks. It involves heating the artwork and recording its thermal response using infrared camera. A novel strategy based on pseudo-random binary excitation principle is used in this work to suppress the risks associated with prolonged heating. The objective of this work is to develop an automatic scheme for detecting faults in the captured images. An efficient scheme based on wavelet based subspace decomposition is developed which favors identification of, the otherwise invisible, weaker faults. Two major problems addressed in this work are the selection of the optimal wavelet basis and the subspace level selection. A novel criterion based on regional mutual information is proposed for the latter. The approach is successfully tested on a laboratory based sample as well as real artworks. A new contrast enhancement metric is developed to demonstrate the quantitative efficiency of the algorithm. The algorithm is successfully deployed for both laboratory based and real artworks.

Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images

NASA Astrophysics Data System (ADS)

Zhai, Han; Zhang, Hongyan; Zhang, Liangpei; Li, Pingxiang

2016-10-01

Considering the inevitable obstacles faced by the pixel-based clustering methods, such as salt-and-pepper noise, high computational complexity, and the lack of spatial information, a reweighted mass center based object-oriented sparse subspace clustering (RMC-OOSSC) algorithm for hyperspectral images (HSIs) is proposed. First, the mean-shift segmentation method is utilized to oversegment the HSI to obtain meaningful objects. Second, a distance reweighted mass center learning model is presented to extract the representative and discriminative features for each object. Third, assuming that all the objects are sampled from a union of subspaces, it is natural to apply the SSC algorithm to the HSI. Faced with the high correlation among the hyperspectral objects, a weighting scheme is adopted to ensure that the highly correlated objects are preferred in the procedure of sparse representation, to reduce the representation errors. Two widely used hyperspectral datasets were utilized to test the performance of the proposed RMC-OOSSC algorithm, obtaining high clustering accuracies (overall accuracy) of 71.98% and 89.57%, respectively. The experimental results show that the proposed method clearly improves the clustering performance with respect to the other state-of-the-art clustering methods, and it significantly reduces the computational time.

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

A Poisson nonnegative matrix factorization method with parameter subspace clustering constraint for endmember extraction in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Ma, Jun; Yang, Gang; Du, Bo; Zhang, Liangpei

2017-06-01

A new Bayesian method named Poisson Nonnegative Matrix Factorization with Parameter Subspace Clustering Constraint (PNMF-PSCC) has been presented to extract endmembers from Hyperspectral Imagery (HSI). First, the method integrates the liner spectral mixture model with the Bayesian framework and it formulates endmember extraction into a Bayesian inference problem. Second, the Parameter Subspace Clustering Constraint (PSCC) is incorporated into the statistical program to consider the clustering of all pixels in the parameter subspace. The PSCC could enlarge differences among ground objects and helps finding endmembers with smaller spectrum divergences. Meanwhile, the PNMF-PSCC method utilizes the Poisson distribution as the prior knowledge of spectral signals to better explain the quantum nature of light in imaging spectrometer. Third, the optimization problem of PNMF-PSCC is formulated into maximizing the joint density via the Maximum A Posterior (MAP) estimator. The program is finally solved by iteratively optimizing two sub-problems via the Alternating Direction Method of Multipliers (ADMM) framework and the FURTHESTSUM initialization scheme. Five state-of-the art methods are implemented to make comparisons with the performance of PNMF-PSCC on both the synthetic and real HSI datasets. Experimental results show that the PNMF-PSCC outperforms all the five methods in Spectral Angle Distance (SAD) and Root-Mean-Square-Error (RMSE), and especially it could identify good endmembers for ground objects with smaller spectrum divergences.

Teko: A block preconditioning capability with concrete example applications in Navier--Stokes and MHD

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

Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.

This study describes the design of Teko, an object-oriented C++ library for implementing advanced block preconditioners. Mathematical design criteria that elucidate the needs of block preconditioning libraries and techniques are explained and shown to motivate the structure of Teko. For instance, a principal design choice was for Teko to strongly reflect the mathematical statement of the preconditioners to reduce development burden and permit focus on the numerics. Additional mechanisms are explained that provide a pathway to developing an optimized production capable block preconditioning capability with Teko. Finally, Teko is demonstrated on fluid flow and magnetohydrodynamics applications. In addition to highlightingmore » the features of the Teko library, these new results illustrate the effectiveness of recent preconditioning developments applied to advanced discretization approaches.« less

Teko: A block preconditioning capability with concrete example applications in Navier--Stokes and MHD

DOE PAGES

Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.

2016-10-27

This study describes the design of Teko, an object-oriented C++ library for implementing advanced block preconditioners. Mathematical design criteria that elucidate the needs of block preconditioning libraries and techniques are explained and shown to motivate the structure of Teko. For instance, a principal design choice was for Teko to strongly reflect the mathematical statement of the preconditioners to reduce development burden and permit focus on the numerics. Additional mechanisms are explained that provide a pathway to developing an optimized production capable block preconditioning capability with Teko. Finally, Teko is demonstrated on fluid flow and magnetohydrodynamics applications. In addition to highlightingmore » the features of the Teko library, these new results illustrate the effectiveness of recent preconditioning developments applied to advanced discretization approaches.« less

High resolution through-the-wall radar image based on beamspace eigenstructure subspace methods

NASA Astrophysics Data System (ADS)

Yoon, Yeo-Sun; Amin, Moeness G.

2008-04-01

Through-the-wall imaging (TWI) is a challenging problem, even if the wall parameters and characteristics are known to the system operator. Proper target classification and correct imaging interpretation require the application of high resolution techniques using limited array size. In inverse synthetic aperture radar (ISAR), signal subspace methods such as Multiple Signal Classification (MUSIC) are used to obtain high resolution imaging. In this paper, we adopt signal subspace methods and apply them to the 2-D spectrum obtained from the delay-andsum beamforming image. This is in contrast to ISAR, where raw data, in frequency and angle, is directly used to form the estimate of the covariance matrix and array response vector. Using beams rather than raw data has two main advantages, namely, it improves the signal-to-noise ratio (SNR) and can correctly image typical indoor extended targets, such as tables and cabinets, as well as point targets. The paper presents both simulated and experimental results using synthesized and real data. It compares the performance of beam-space MUSIC and Capon beamformer. The experimental data is collected at the test facility in the Radar Imaging Laboratory, Villanova University.

Deep Long-period Seismicity Beneath the Executive Committee Range, Marie Byrd Land, Antarctica, Studied Using Subspace Detection

NASA Astrophysics Data System (ADS)

Aster, R. C.; McMahon, N. D.; Myers, E. K.; Lough, A. C.

2015-12-01

Lough et al. (2014) first detected deep sub-icecap magmatic events beneath the Executive Committee Range volcanoes of Marie Byrd Land. Here, we extend the identification and analysis of these events in space and time utilizing subspace detection. Subspace detectors provide a highly effective methodology for studying events within seismic swarms that have similar moment tensor and Green's function characteristics and are particularly effective for identifying low signal-to-noise events. Marie Byrd Land (MBL) is an extremely remote continental region that is nearly completely covered by the West Antarctic Ice Sheet (WAIS). The southern extent of Marie Byrd Land lies within the West Antarctic Rift System (WARS), which includes the volcanic Executive Committee Range (ECR). The ECR shows north-to-south progression of volcanism across the WARS during the Holocene. In 2013, the POLENET/ANET seismic data identified two swarms of seismic activity in 2010 and 2011. These events have been interpreted as deep, long-period (DLP) earthquakes based on depth (25-40 km) and low frequency content. The DLP events in MBL lie beneath an inferred sub-WAIS volcanic edifice imaged with ice penetrating radar and have been interpreted as a present location of magmatic intrusion. The magmatic swarm activity in MBL provides a promising target for advanced subspace detection and temporal, spatial, and event size analysis of an extensive deep long period earthquake swarm using a remote seismographic network. We utilized a catalog of 1,370 traditionally identified DLP events to construct subspace detectors for the six nearest stations and analyzed two years of data spanning 2010-2011. Association of these detections into events resulted in an approximate ten-fold increase in number of locatable earthquakes. In addition to the two previously identified swarms during early 2010 and early 2011, we find sustained activity throughout the two years of study that includes several previously

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

PubMed

Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

2018-02-01

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

Preconditioned conjugate-gradient methods for low-speed flow calculations

NASA Technical Reports Server (NTRS)

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 is 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 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 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 Conjugate Gradient methods for low speed flow calculations

NASA Technical Reports Server (NTRS)

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.

Financial preconditions for successful community initiatives for the uninsured.

PubMed

Song, Paula H; Smith, Dean G

2007-01-01

Community-based initiatives are increasingly being implemented as a strategy to address the health needs of the community, with a growing body of evidence on successes of various initiatives. This study addresses financial status indicators (preconditions) that might predict where community-based initiatives might have a better chance for success. We evaluated five community-based initiatives funded by the Communities in Charge (CIC) program sponsored by the Robert Wood Johnson Foundation. These initiatives focus on increasing access by easing financial barriers to care for the uninsured. At each site, we collected information on financial status indicators and interviewed key personnel from health services delivery and financing organizations. With full acknowledgment of the caveats associated with generalizations based on a small number of observations, we suggest four financial preconditions associated with successful initiation of CIC programs: (1) uncompensated care levels that negatively affect profitability, (2) reasonable financial stability of providers, (3) stable health insurance market, and (4) the potential to create new sources of funding. In general, sites that demonstrate successful program initiation are financially stressed enough by uncompensated care to gain the attention of local healthcare providers. However, they are not so strained and so concerned about revenue sources that they cannot afford to participate in the initiative. In addition to political and managerial indicators, we suggest that planning for community-based initiatives should include financial indicators of current health services delivery and financing organizations and consideration of whether they meet preconditions for success.

Using Chebyshev polynomials and approximate inverse triangular factorizations for preconditioning the conjugate gradient method

NASA Astrophysics Data System (ADS)

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.

S{sub 2}SA preconditioning for the S{sub n} equations with strictly non negative spatial discretization

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

Bruss, D. E.; Morel, J. E.; Ragusa, J. C.

2013-07-01

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{sub 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 amore » linear diffusion equation has important implications for preconditioning the S{sub n} equations with a strictly non negative spatial discretization in multiple dimensions. (authors)« less

Subspace techniques to remove artifacts from EEG: a quantitative analysis.

PubMed

Teixeira, A R; Tome, A M; Lang, E W; Martins da Silva, A

2008-01-01

In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.

HMC algorithm with multiple time scale integration and mass preconditioning

NASA Astrophysics Data System (ADS)

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.

Antidepressant-like effects of mild hypoxia preconditioning in the learned helplessness model in rats.

PubMed

Rybnikova, Elena; Mironova, Vera; Pivina, Svetlana; Tulkova, Ekaterina; Ordyan, Natalia; Vataeva, Ludmila; Vershinina, Elena; Abritalin, Eugeny; Kolchev, Alexandr; Nalivaeva, Natalia; Turner, Anthony J; Samoilov, Michail

2007-05-07

The effects of preconditioning using mild repetitive hypobaric hypoxia (360 Torr for 2 h each of 3 days) have been studied in the learned helplessness model of depression in rats. Male Wistar rats displayed persistent depressive symptoms (depressive-like behaviour in open field, increased anxiety levels in elevated plus maze, ahedonia, elevated plasma glucocorticoids and impaired dexamethasone test) following the exposure to unpredictable and inescapable footshock in the learned helplessness paradigm. Antidepressant treatment (ludiomil, 5 mg/kg i.p.) augmented the development of the depressive state. The hypoxic preconditioning had a clear antidepressive action returning the behavioural and hormonal parameters to the control values and was equally effective in terms of our study as the antidepressant. The findings suggest hypoxic preconditioning as an effective tool for the prophylaxis of post-stress affective pathologies in humans.

Morphine Preconditioning Downregulates MicroRNA-134 Expression Against Oxygen-Glucose Deprivation Injuries in Cultured Neurons of Mice.

PubMed

Meng, Fanjun; Li, Yan; Chi, Wenying; Li, Junfa

2016-07-01

Brain protection by narcotics such as morphine is clinically relevant due to the extensive use of narcotics in the perioperative period. Morphine preconditioning induces neuroprotection in neurons, but it remains uncertain whether microRNA-134 (miR-134) is involved in morphine preconditioning against oxygen-glucose deprivation-induced injuries in primary cortical neurons of mice. The present study examined this issue. After cortical neurons of mice were cultured in vitro for 6 days, the neurons were transfected by respective virus vector, such as lentiviral vector (LV)-miR-control-GFP, LV-pre-miR-134-GFP, LV-pre-miR-134-inhibitor-GFP for 24 hours; after being normally cultured for 3 days again, morphine preconditioning was performed by incubating the transfected primary neurons with morphine (3 μM) for 1 hour, and then neuronal cells were exposed to oxygen-glucose deprivation (OGD) for 1 hour and oxygen-glucose recovery for 12 hours. The neuronal cells survival rate and the amount of apoptotic neurons were determined by MTT assay or TUNEL staining at designated time; and the expression levels of miR-134 were detected using real-time reverse transcription polymerase chain reaction at the same time. The neuronal cell survival rate was significantly higher, and the amount of apoptotic neurons was significantly decreased in neurons preconditioned with morphine before OGD than that of OGD alone. The neuroprotection induced by morphine preconditioning was partially blocked by upregulating miR-134 expression, and was enhanced by downregulating miR-134 expression. The expression of miR-134 was significantly decreased in morphine-preconditioned neurons alone without transfection. By downregulating miR-134 expression, morphine preconditioning protects primary cortical neurons of mice against injuries induced by OGD.

Efficient numerical calculation of MHD equilibria with magnetic islands, with particular application to saturated neoclassical tearing modes

NASA Astrophysics Data System (ADS)

Raburn, Daniel Louis

We have developed a preconditioned, globalized Jacobian-free Newton-Krylov (JFNK) solver for calculating equilibria with magnetic islands. The solver has been developed in conjunction with the Princeton Iterative Equilibrium Solver (PIES) and includes two notable enhancements over a traditional JFNK scheme: (1) globalization of the algorithm by a sophisticated backtracking scheme, which optimizes between the Newton and steepest-descent directions; and, (2) adaptive preconditioning, wherein information regarding the system Jacobian is reused between Newton iterations to form a preconditioner for our GMRES-like linear solver. We have developed a formulation for calculating saturated neoclassical tearing modes (NTMs) which accounts for the incomplete loss of a bootstrap current due to gradients of multiple physical quantities. We have applied the coupled PIES-JFNK solver to calculate saturated island widths on several shots from the Tokamak Fusion Test Reactor (TFTR) and have found reasonable agreement with experimental measurement.

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

Effects and interaction, of cariporide and preconditioning on cardiac arrhythmias and infarction in rat in vivo

PubMed Central

Aye, Nu Nu; Komori, Sadayoshi; Hashimoto, Keitaro

1999-01-01

Although Na+-H+ exchange (NHE) inhibitors are reported to protect the myocardium against ischaemic injury, NHE activation has also been proposed as a potential mechanism of ischaemic preconditioning-induced protection. This study was performed to test any modifiable effect of cariporide, an NHE inhibitor, on cardioprotective effects of preconditioning.Anaesthetized rats were subjected to 30 min of coronary artery occlusion and 150 min of reperfusion. The preconditioning (PC) was induced by 3 min of ischaemia and 10 min of reperfusion (1PC) or three episodes of 3 min ischaemia and 5 min reperfusion (3PC). Cariporide (0.3 mg kg−1) an NHE inhibitor, was administered 30 min (cari(30)) or 45 min (cari(45)) before coronary ligation (n=8–11 for each group).Ventricular arrhythmias during 30 min ischaemia and infarct size (measured by triphenyltetrazolium (TTC) and expressed as a per cent area at risk (%AAR)) were determined. Cari(30) reduced ventricular fibrillation (VF) incidence and infarct size (from 45 to 0% and 34±4 to 9±2%; each P<0.05), whereas cari(45) did not. Likewise, 3PC reduced these variables (to 0% and 10±2%; P<0.05 in each case) whereas 1PC did not. Moreover, subthreshold preconditioning (1PC) and cariporide (cari(45)), when combined, reduced VF incidence and infarct size (to 0% and 15+3%; each P<0.05).In conclusion, changes in NHE activity do not seem to be responsible for the cardioprotective action of ischaemic preconditioning. Protective effects of NHE inhibition and subthreshold preconditioning appear to act additively. PMID:10433514

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a

[Effects of xenon preconditioning against ischemia/reperfusion injury and oxidative stress in immature heart].

PubMed

Li, Qian; Lian, Chun-Wei; Fang, Li-Qun; Liu, Bin; Yang, Bo

2014-09-01

To investigate whether xenon preconditioning (PC) could protect immature myocardium against ischemia-reperfusion (I/R) injury in a dose-dependent manner and clarify the role of xenon PC on oxidative stress. Forty-eight isolated perfused immature rabbit hearts were randomly divided into four groups (n = 12): The sham group had the hearts perfused continuously for 300 min. In I/R group, the hearts were subjected to 60 min perfusion followed by 60 min ischemia and 180 min reperfusion. In 1 minimum alveolar concentration (MAC) and 0.5 MAC xenon PC groups, the hearts were preconditioned with 1 MAC or 0.5 MAC xenon respectively, following 60 min ischemia and 180 min reperfusion. The cardiac function, myocardial infarct size, mitochondrial structure, superoxide dismutase (SOD) activity and malondialdehyde (MDA) level in each group were determined after reperfusion. Compared with I/R group, both 1 MAC and 0. 5 MAC xenon preconditioning significantly improved cardiac function (P < 0.01), reduced myocardial infarct size (P < 0.01) and mitochondrial damage, increased SOD activity and decreased MDA level (P < 0.01). There were no differences between 1 MAC group and 0.5 MAC xenon group (P > 0.05). Xenon preconditioning at 0. 5 and 1 MAC produce similar cardioprotective effects against I/R injury in isolated perfused immature heart.

Gadolinium and ruthenium red attenuate remote hind limb preconditioning-induced cardioprotection: possible role of TRP and especially TRPV channels.

PubMed

Randhawa, Puneet Kaur; Jaggi, Amteshwar Singh

2016-08-01

Remote ischemic preconditioning is a well reported therapeutic strategy that induces cardioprotective effects but the underlying intracellular mechanisms have not been widely explored. The current study was designed to investigate the involvement of TRP and especially TRPV channels in remote hind limb preconditioning-induced cardioprotection. Remote hind limb preconditioning stimulus (4 alternate cycles of inflation and deflation of 5 min each) was delivered using a blood pressure cuff tied on the hind limb of the anesthetized rat. Using Langendorff's system, the heart was perfused and subjected to 30-min ischemia and 120-min reperfusion. The myocardial injury was assessed by measuring infarct size, lactate dehydrogenase (LDH), creatine kinase (CK), LVDP, +dp/dtmax, -dp/dtmin, heart rate, and coronary flow rate. Gadolinium, TRP blocker, and ruthenium red, TRPV channel blocker, were employed as pharmacological tools. Remote hind limb preconditioning significantly reduced the infarct size, LDH release, CK release and improved coronary flow rate, hemodynamic parameters including LVDP, +dp/dtmax, -dp/dtmin, and heart rate. However, gadolinium (7.5 and 15 mg kg(-1)) and ruthenium red (4 and 8 mg kg(-1)) significantly attenuated the cardioprotective effects suggesting the involvement of TRP especially TRPV channels in mediating remote hind limb preconditioning-induced cardioprotection. Remote hind limb preconditioning stimulus possibly activates TRPV channels on the heart or sensory nerve fibers innervating the heart to induce cardioprotective effects. Alternatively, remote hind limb preconditioning stimulus may also activate the mechanosensitive TRP and especially TRPV channels on the sensory nerve fibers innervating the skeletal muscles to trigger cardioprotective neurogenic signaling cascade. The cardioprotective effects of remote hind limb preconditioning may be mediated via activation of mechanosensitive TRP and especially TRPV channels.

Evidence that the adenosine A3 receptor may mediate the protection afforded by preconditioning in the isolated rabbit heart.

PubMed

Liu, G S; Richards, S C; Olsson, R A; Mullane, K; Walsh, R S; Downey, J M

1994-07-01

Agonists selective for the A1 adenosine receptor mimic the protective effect of ischaemic preconditioning against infarction in the rabbit heart. Unselective adenosine antagonists block this protection but, paradoxically, the A1 adenosine receptor selective antagonist 8-cyclopentyl- 1,3-dipropylxanthine (DPCPX) does not. The aim of this study was to test the hypothesis that the newly described A3 adenosine receptor, which has an agonist profile similar to the A1 receptor but is insensitive to DPCPX, might mediate preconditioning. Isolated rabbit hearts perfused with Krebs buffer experienced 30 min of regional ischaemia followed by 120 min of reperfusion. Infarct size was measured by tetrazolium staining. In control hearts infarction was 32.2(SEM 1.5)% of the risk zone. Preconditioning by 5 min ischaemia and 10 min reperfusion reduced infarct size to 8.8(2.3)%. Replacing the regional ischaemia with 5 min perfusion with 10 microM adenosine or 65 nM N6-[2-(4-aminophenyl)ethyl]adenosine (APNEA), an adenosine A3 receptor agonist, was equally protective. The unselective antagonist 8-p-sulphophenyl theophylline at 100 microM abolished protection by preconditioning, adenosine, and APNEA, but 200 nM DPCPX did not block protection by any of the interventions. Likewise the potent but unselective A3 receptor antagonist 8-(4-carboxyethenylphenyl)-1,3-dipropylxanthine (BW A1433) completely blocked protection from ischaemic preconditioning. Because protection against infarction afforded by ischaemic preconditioning, adenosine, or the A3 receptor agonist APNEA could not be blocked by DPCPX and because the potent A3 receptor antagonist BW A1433 blocked protection from ischaemic preconditioning, these data indicate that the protection of preconditioning is not exclusively mediated by the adenosine A1 receptor in rabbit heart and could involve the A3 receptor.

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Pre-test procedures and... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Pre-test procedures and... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Pre-test procedures and... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Pre-test procedures and... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

40 CFR 85.2218 - Preconditioned idle test-EPA 91.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Preconditioned idle test-EPA 91. 85.2218 Section 85.2218 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM MOBILE SOURCES Emission Control System Performance Warranty Short...

ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces.

PubMed

Ivannikov, Andriy; Kalyakin, Igor; Hämäläinen, Jarmo; Leppänen, Paavo H T; Ristaniemi, Tapani; Lyytinen, Heikki; Kärkkäinen, Tommi

2009-06-15

In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The interpretation of the results and the performance of the proposed method under conditions, when the basic assumptions are violated - e.g. the problem is underdetermined - are also discussed. Moreover, we study how the factors of the number of channels and trials used by the method influence the effectiveness of ERP/noise subspaces separation. In addition, we explore also the impact of different data resampling strategies on the performance of the considered algorithm. The results can help in determining the optimal parameters of the equipment/methods used to elicit and reliably estimate ERPs.

Preconditioning mesenchymal stem cells with the mood stabilizers lithium and valproic acid enhances therapeutic efficacy in a mouse model of Huntington's disease.

PubMed

Linares, Gabriel R; Chiu, Chi-Tso; Scheuing, Lisa; Leng, Yan; Liao, Hsiao-Mei; Maric, Dragan; Chuang, De-Maw

2016-07-01

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by CAG repeat expansions in the huntingtin gene. Although, stem cell-based therapy has emerged as a potential treatment for neurodegenerative diseases, limitations remain, including optimizing delivery to the brain and donor cell loss after transplantation. One strategy to boost cell survival and efficacy is to precondition cells before transplantation. Because the neuroprotective actions of the mood stabilizers lithium and valproic acid (VPA) induce multiple pro-survival signaling pathways, we hypothesized that preconditioning bone marrow-derived mesenchymal stem cells (MSCs) with lithium and VPA prior to intranasal delivery to the brain would enhance their therapeutic efficacy, and thereby facilitate functional recovery in N171-82Q HD transgenic mice. MSCs were treated in the presence or absence of combined lithium and VPA, and were then delivered by brain-targeted single intranasal administration to eight-week old HD mice. Histological analysis confirmed the presence of MSCs in the brain. Open-field test revealed that ambulatory distance and mean velocity were significantly improved in HD mice that received preconditioned MSCs, compared to HD vehicle-control and HD mice transplanted with non-preconditioned MSCs. Greater benefits on motor function were observed in HD mice given preconditioned MSCs, while HD mice treated with non-preconditioned MSCs showed no functional benefits. Moreover, preconditioned MSCs reduced striatal neuronal loss and huntingtin aggregates in HD mice. Gene expression profiling of preconditioned MSCs revealed a robust increase in expression of genes involved in trophic effects, antioxidant, anti-apoptosis, cytokine/chemokine receptor, migration, mitochondrial energy metabolism, and stress response signaling pathways. Consistent with this finding, preconditioned MSCs demonstrated increased survival after transplantation into the brain compared to non-preconditioned cells

pyCTQW: A continuous-time quantum walk simulator on distributed memory computers

NASA Astrophysics Data System (ADS)

Izaac, Josh A.; Wang, Jingbo B.

2015-01-01

In the general field of quantum information and computation, quantum walks are playing an increasingly important role in constructing physical models and quantum algorithms. We have recently developed a distributed memory software package pyCTQW, with an object-oriented Python interface, that allows efficient simulation of large multi-particle CTQW (continuous-time quantum walk)-based systems. In this paper, we present an introduction to the Python and Fortran interfaces of pyCTQW, discuss various numerical methods of calculating the matrix exponential, and demonstrate the performance behavior of pyCTQW on a distributed memory cluster. In particular, the Chebyshev and Krylov-subspace methods for calculating the quantum walk propagation are provided, as well as methods for visualization and data analysis.

Wide-angle full-vector beam propagation method based on an alternating direction implicit preconditioner

NASA Astrophysics Data System (ADS)

Chui, Siu Lit; Lu, Ya Yan

2004-03-01

Wide-angle full-vector beam propagation methods (BPMs) for three-dimensional wave-guiding structures can be derived on the basis of rational approximants of a square root operator or its exponential (i.e., the one-way propagator). While the less accurate BPM based on the slowly varying envelope approximation can be efficiently solved by the alternating direction implicit (ADI) method, the wide-angle variants involve linear systems that are more difficult to handle. We present an efficient solver for these linear systems that is based on a Krylov subspace method with an ADI preconditioner. The resulting wide-angle full-vector BPM is used to simulate the propagation of wave fields in a Y branch and a taper.

Wide-angle full-vector beam propagation method based on an alternating direction implicit preconditioner.

PubMed

Chui, Siu Lit; Lu, Ya Yan

2004-03-01

Wide-angle full-vector beam propagation methods (BPMs) for three-dimensional wave-guiding structures can be derived on the basis of rational approximants of a square root operator or its exponential (i.e., the one-way propagator). While the less accurate BPM based on the slowly varying envelope approximation can be efficiently solved by the alternating direction implicit (ADI) method, the wide-angle variants involve linear systems that are more difficult to handle. We present an efficient solver for these linear systems that is based on a Krylov subspace method with an ADI preconditioner. The resulting wide-angle full-vector BPM is used to simulate the propagation of wave fields in a Y branch and a taper.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

PubMed

Ye, Jinzuo; Chi, Chongwei; Xue, Zhenwen; Wu, Ping; An, Yu; Xu, Han; Zhang, Shuang; Tian, Jie

2014-02-01

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

PubMed

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

Role of Phosphatidylinositol-3 Kinase Pathway in NMDA Preconditioning: Different Mechanisms for Seizures and Hippocampal Neuronal Degeneration Induced by Quinolinic Acid.

PubMed

Constantino, Leandra C; Binder, Luisa B; Vandresen-Filho, Samuel; Viola, Giordano G; Ludka, Fabiana K; Lopes, Mark W; Leal, Rodrigo B; Tasca, Carla I

2018-04-20

N-methyl D-aspartate (NMDA) preconditioning is evoked by the administration of a subtoxic dose of NMDA and is protective against neuronal excitotoxicity. This effect may involve a diversity of targets and cell signaling cascades associated to neuroprotection. Phosphatidylinositol-3 kinase/protein kinase B (PI3K/Akt) and mitogen-activated protein kinases (MAPKs) such as extracellular regulated protein kinase 1/2 (ERK1/2) and p38 MAPK pathways play a major role in neuroprotective mechanisms. However, their involvement in NMDA preconditioning was not yet fully investigated. The present study aimed to evaluate the effect of NMDA preconditioning on PI3K/Akt, ERK1/2, and p38 MAPK pathways in the hippocampus of mice and characterize the involvement of PI3K on NMDA preconditioning-evoked prevention of seizures and hippocampal cell damage induced by quinolinic acid (QA). Thus, mice received wortmannin (a PI3K inhibitor) and 15 min later a subconvulsant dose of NMDA (preconditioning) or saline. After 24 h of this treatment, an intracerebroventricular QA infusion was administered. Phosphorylation levels and total content of Akt, glycogen synthase protein kinase-3β (GSK-3β), ERK1/2, and p38 MAPK were not altered after 24 h of NMDA preconditioning with or without wortmmanin pretreatment. Moreover, after QA administration, behavioral seizures, hippocampal neuronal degeneration, and Akt activation were evaluated. Inhibition of PI3K pathway was effective in abolishing the protective effect of NMDA preconditioning against QA-induced seizures, but did not modify neuronal protection promoted by preconditioning as evaluated by Fluoro-Jade B staining. The study confirms that PI3K participates in the mechanism of protection induced by NMDA preconditioning against QA-induced seizures. Conversely, NMDA preconditioning-evoked protection against neuronal degeneration is not altered by PI3K signaling pathway inhibition. These results point to differential mechanisms regarding protection

Solving large test-day models by iteration on data and preconditioned conjugate gradient.

PubMed

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.

Cardioprotection of ischaemic preconditioning is associated with inhibition of translocation of MLKL within the plasma membrane.

PubMed

Szobi, Adrián; Farkašová-Ledvényiová, Veronika; Lichý, Martin; Muráriková, Martina; Čarnická, Slávka; Ravingerová, Tatiana; Adameová, Adriana

2018-06-19

Necroptosis, a form of cell loss involving the RIP1-RIP3-MLKL axis, has been identified in cardiac pathologies while its inhibition is cardioprotective. We investigated whether the improvement of heart function because of ischaemic preconditioning is associated with mitigation of necroptotic signaling, and these effects were compared with a pharmacological antinecroptotic approach targeting RIP1. Langendorff-perfused rat hearts were subjected to ischaemic preconditioning with or without a RIP1 inhibitor (Nec-1s). Necroptotic signaling and the assessment of oxidative damage and a putative involvement of CaMKII in this process were analysed in whole tissue and subcellular fractions. Ischaemic preconditioning, Nec-1s and their combination improved postischaemic heart function recovery and reduced infarct size to a similar degree what was in line with the prevention of MLKL oligomerization and translocation to the membrane. On the other hand, membrane peroxidation and apoptosis were unchanged by either approach. Ischaemic preconditioning failed to ameliorate ischaemia-reperfusion-induced increase in RIP1 and RIP3 while pSer229-RIP3 levels were reduced only by Nec-1s. In spite of the additive phosphorylation of CaMKII and PLN because of ditherapy, the postischaemic contractile force and relaxation was comparably improved in all the intervention groups while antiarrhythmic effects were observed in the ischaemic preconditioning group only. Necroptosis inhibition seems to be involved in cardioprotection of ischaemic preconditioning and is comparable but not intensified by an anti-RIP1 agent. Changes in oxidative stress nor CaMKII signaling are unlikely to explain the beneficial effects. © 2018 Comenius University in Bratislava, Faculty of Pharmacy. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Isoflurane preconditioning protects neurons from male and female mice against oxygen and glucose deprivation and is modulated by estradiol only in neurons from female mice.

PubMed

Johnsen, D; Murphy, S J

2011-12-29

The volatile anesthetic, isoflurane, can protect the brain if administered before an insult such as an ischemic stroke. However, this protective "preconditioning" response to isoflurane is specific to males, with females showing an increase in brain damage following isoflurane preconditioning and subsequent focal cerebral ischemia. Innate cell sex is emerging as an important player in neuronal cell death, but its role in the sexually dimorphic response to isoflurane preconditioning has not been investigated. We used an in vitro model of isoflurane preconditioning and ischemia (oxygen and glucose deprivation, OGD) to test the hypotheses that innate cell sex dictates the response to isoflurane preconditioning and that 17β-estradiol attenuates any protective effect from isoflurane preconditioning in neurons via nuclear estrogen receptors. Sex-segregated neuron cultures derived from postnatal day 0-1 mice were exposed to either 0% or 3% isoflurane preconditioning for 1 h. In separate experiments, 17β-estradiol and the non-selective estrogen receptor antagonist ICI 182,780 were added 24 h before preconditioning and then removed at the end of the preconditioning period. Twenty-three hours after preconditioning, all cultures underwent 2 h of OGD. Twenty-four hours following OGD, cell viability was quantified using calcein-AM fluorescence. We observed that isoflurane preconditioning increased cell survival following subsequent OGD regardless of innate cell sex, but that the presence of 17β-estradiol before and during isoflurane preconditioning attenuated this protection only in female neurons independent of nuclear estrogen receptors. We also found that independent of preconditioning treatment, female neurons were less sensitive to OGD compared with male neurons and that transient treatment with 17β-estradiol protected both male and female neurons from subsequent OGD. More studies are needed to determine how cell type, cell sex, and sex steroids like 17β-estradiol may

Flagellin preconditioning enhances the efficacy of mesenchymal stem cells in an irradiation-induced proctitis model.

PubMed

Linard, Christine; Strup-Perrot, Carine; Lacave-Lapalun, Jean-Victor; Benderitter, Marc

2016-09-01

The success of mesenchymal stem cell transplantation for proctitis depends not only on cell donors but also on host microenvironmental factors, which play a major role in conditioning mesenchymal stem cell immunosuppressive action and repair. This study sought to determine if flagellin, a TLR5 ligand, can enhance the mesenchymal stem cell treatment efficacy in radiation-induced proctitis. With the use of a colorectal model of 27 Gy irradiation in rats, we investigated and compared the effects on immune capacity and remodeling at 28 d after irradiation of the following: 1) systemic mesenchymal stem cell (5 × 10(6)) administration at d 7 after irradiation, 2) administration of flagellin at d 3 and systemic mesenchymal stem cell administration at d 7, and 3) in vitro preconditioning of mesenchymal stem cells with flagellin, 24 h before their administration on d 7. The mucosal CD8(+) T cell population was normalized after treatment with flagellin-preconditioned mesenchymal stem cells or flagellin plus mesenchymal stem cells, whereas mesenchymal stem cells alone did not alter the radiation-induced elevation of CD8(+) T cell frequency. Mesenchymal stem cell treatment returned the irradiation-elevated frequency of CD25(+) cells in the mucosa-to-control levels, whereas both flagellin-preconditioned mesenchymal stem cell and flagellin-plus-mesenchymal stem cell treatment each significantly increased not only CD25(+) cell frequency but also forkhead box p3 and IL-2Rα expression. Specifically, IL-10 was overexpressed after flagellin-preconditioned mesenchymal stem cell treatment. Analysis of collagen expression showed that the collagen type 1/collagen type 3 ratio, an indicator of wound-healing maturation, was low in the irradiated and mesenchymal stem cell-treated groups and returned to the normal level only after the flagellin-preconditioned mesenchymal stem cell treatment. This was associated with a reduction in myofibroblast accumulation. In a proctitis model, flagellin-preconditioned

Margin-Wide Earthquake Subspace Scanning Along the Cascadia Subduction Zone Using the Cascadia Initiative Amphibious Dataset

NASA Astrophysics Data System (ADS)

Morton, E.; Bilek, S. L.; Rowe, C. A.

2017-12-01

Understanding the spatial extent and behavior of the interplate contact in the Cascadia Subduction Zone (CSZ) may prove pivotal to preparation for future great earthquakes, such as the M9 event of 1700. Current and historic seismic catalogs are limited in their integrity by their short duration, given the recurrence rate of great earthquakes, and by their rather high magnitude of completeness for the interplate seismic zone, due to its offshore distance from these land-based networks. This issue is addressed via the 2011-2015 Cascadia Initiative (CI) amphibious seismic array deployment, which combined coastal land seismometers with more than 60 ocean-bottom seismometers (OBS) situated directly above the presumed plate interface. We search the CI dataset for small, previously undetected interplate earthquakes to identify seismic patches on the megathrust. Using the automated subspace detection method, we search for previously undetected events. Our subspace comprises eigenvectors derived from CI OBS and on-land waveforms extracted for existing catalog events that appear to have occurred on the plate interface. Previous work focused on analysis of two repeating event clusters off the coast of Oregon spanning all 4 years of deployment. Here we expand earlier results to include detection and location analysis to the entire CSZ margin during the first year of CI deployment, with more than 200 new events detected for the central portion of the margin. Template events used for subspace scanning primarily occurred beneath the land surface along the coast, at the downdip edge of modeled high slip patches for the 1700 event, with most concentrated at the northwestern edge of the Olympic Peninsula.

Preconditioned alternating projection algorithms for maximum a posteriori ECT reconstruction

NASA Astrophysics Data System (ADS)

Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng

2012-11-01

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.

Xenon Preconditioning Protects against Renal Ischemic-Reperfusion Injury via HIF-1α Activation

PubMed Central

Ma, Daqing; Lim, Ta; Xu, Jing; Tang, Haidy; Wan, Yanjie; Zhao, Hailin; Hossain, Mahmuda; Maxwell, Patrick H.; Maze, Mervyn

2009-01-01

The mortality rate from acute kidney injury after major cardiovascular operations can be as high as 60%, and no therapies have been proved to prevent acute kidney injury in this setting. Here, we show that preconditioning with the anesthetic gas xenon activates hypoxia-inducible factor 1α (HIF-1α) and its downstream effectors erythropoietin and vascular endothelial growth factor in a time-dependent manner in the kidneys of adult mice. Xenon increased the efficiency of HIF-1α translation via modulation of the mammalian target of rapamycin pathway. In a model of renal ischemia-reperfusion injury, xenon provided morphologic and functional renoprotection; hydrodynamic injection of HIF-1α small interfering RNA demonstrated that this protection is HIF-1α dependent. These results suggest that xenon preconditioning is a natural inducer of HIF-1α and that administration of xenon before renal ischemia can prevent acute renal failure. If these data are confirmed in the clinical setting, then preconditioning with xenon may be beneficial before procedures that temporarily interrupt renal perfusion. PMID:19144758

Preconditioned upwind methods to solve 3-D incompressible Navier-Stokes equations for viscous flows

NASA Technical Reports Server (NTRS)

Hsu, C.-H.; Chen, Y.-M.; Liu, C. H.

1990-01-01

A computational method for calculating low-speed viscous flowfields is developed. The method uses the implicit upwind-relaxation finite-difference algorithm with a nonsingular eigensystem to solve the preconditioned, three-dimensional, incompressible Navier-Stokes equations in curvilinear coordinates. The technique of local time stepping is incorporated to accelerate the rate of convergence to a steady-state solution. An extensive study of optimizing the preconditioned system is carried out for two viscous flow problems. Computed results are compared with analytical solutions and experimental data.

Recovery Discontinuous Galerkin Jacobian-free Newton-Krylov Method for all-speed flows

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

HyeongKae Park; Robert Nourgaliev; Vincent Mousseau

2008-07-01

There is an increasing interest to develop the next generation simulation tools for the advanced nuclear energy systems. These tools will utilize the state-of-art numerical algorithms and computer science technology in order to maximize the predictive capability, support advanced reactor designs, reduce uncertainty and increase safety margins. In analyzing nuclear energy systems, we are interested in compressible low-Mach number, high heat flux flows with a wide range of Re, Ra, and Pr numbers. Under these conditions, the focus is placed on turbulent heat transfer, in contrast to other industries whose main interest is in capturing turbulent mixing. Our objective ismore » to develop singlepoint turbulence closure models for large-scale engineering CFD code, using Direct Numerical Simulation (DNS) or Large Eddy Simulation (LES) tools, requireing very accurate and efficient numerical algorithms. The focus of this work is placed on fully-implicit, high-order spatiotemporal discretization based on the discontinuous Galerkin method solving the conservative form of the compressible Navier-Stokes equations. The method utilizes a local reconstruction procedure derived from weak formulation of the problem, which is inspired by the recovery diffusion flux algorithm of van Leer and Nomura [?] and by the piecewise parabolic reconstruction [?] in the finite volume method. The developed methodology is integrated into the Jacobianfree Newton-Krylov framework [?] to allow a fully-implicit solution of the problem.« less

EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Ashari, Rehab Bahaaddin

Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. This dissertation studies and examines different ideas using principal angles and subspaces concepts. It introduces a novel mathematical approach for comparing sets of EEG signals for use in new BCI technology. The success of the presented results show that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. In this application, the appearance of a subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Smoothing the signals before using them is the only preprocessing step that was implemented in this study. The smoothing process based on minimizing the second derivative in time is implemented to increase the classification accuracy instead of using the bandpass filter that relies on assumptions on the frequency content of EEG. This study examines four different ways of removing outliers that are based on the principal angles and shows that the outlier removal methods did not help in the presented situations. One of the concepts that this dissertation focused on is the effect of the number of trials on the classification accuracies. The achievement of the good classification results by using a small number of trials starting from two trials only

Numerical Aspects of Nonhydrostatic Implementations Applied to a Parallel Finite Element Tsunami Model

NASA Astrophysics Data System (ADS)

Fuchs, A.; Androsov, A.; Harig, S.; Hiller, W.; Rakowsky, N.

2012-04-01

Based on the jeopardy of devastating tsunamis and the unpredictability of such events, tsunami modelling as part of warning systems is still a contemporary topic. The tsunami group of Alfred Wegener Institute developed the simulation tool TsunAWI as contribution to the Early Warning System in Indonesia. Although the precomputed scenarios for this purpose qualify for satisfying deliverables, the study of further improvements continues. While TsunAWI is governed by the Shallow Water Equations, an extension of the model is based on a nonhydrostatic approach. At the arrival of a tsunami wave in coastal regions with rough bathymetry, the term containing the nonhydrostatic part of pressure, that is neglected in the original hydrostatic model, gains in importance. In consideration of this term, a better approximation of the wave is expected. Differences of hydrostatic and nonhydrostatic model results are contrasted in the standard benchmark problem of a solitary wave runup on a plane beach. The observation data provided by Titov and Synolakis (1995) serves as reference. The nonhydrostatic approach implies a set of equations that are similar to the Shallow Water Equations, so the variation of the code can be implemented on top. However, this additional routines cause a lot of issues you have to cope with. So far the computations of the model were purely explicit. In the nonhydrostatic version the determination of an additional unknown and the solution of a large sparse system of linear equations is necessary. The latter constitutes the lion's share of computing time and memory requirement. Since the corresponding matrix is only symmetric in structure and not in values, an iterative Krylov Subspace Method is used, in particular the restarted Generalized Minimal Residual Algorithm GMRES(m). With regard to optimization, we present a comparison of several combinations of sequential and parallel preconditioning techniques respective number of iterations and setup

Thermal preconditioning of mountain permafrost towards instability

NASA Astrophysics Data System (ADS)

Hauck, Christian; Etzelmüller, Bernd; Hilbich, Christin; Isaksen, Ketil; Mollaret, Coline; Pellet, Cécile; Westermann, Sebastian

2017-04-01

Warming permafrost has been detected worldwide in recent years and is projected to continue during the next century as shown in many modelling studies from the polar and mountain regions. In mountain regions, this can lead to potentially hazardous impacts on short time-scales by an increased tendency for slope instabilities. However, the time scale of permafrost thaw and the role of the ice content for determining the strength and rate of permafrost warming and degradation (= development of talik) are still unclear, especially in highly heterogeneous terrain. Observations of permafrost temperatures near the freezing point show complex inter-annual responses to climate forcing due to latent heat effects during thawing and the influence of the snow-cover, which is formed and modulated by highly non-linear processes itself. These effects are complicated by 3-dimensional hydrological processes and interactions between snow melt, infiltration and drainage which may also play an important role in the triggering of mass movements in steep permafrost slopes. In this contribution we demonstrate for the first time a preconditioning effect within near-surface layers in mountain permafrost that causes non-linear degradation and accelerates permafrost thaw. We hypothesise that an extreme regional or global temperature anomaly, such as the Central European summers 2003 and 2015 or the Northern European summers 2006 and 2014, will enhance permafrost degradation if the active layer and the top of the permafrost layer are already preconditioned, i.e. have reduced latent heat content. This preconditioning can already be effectuated by a singular warm year, leading to exceptionally strong melting of the ground ice in the near-surface layers. On sloping terrain and in a context of quasi-continuous atmospheric warming, this ice-loss can be considered as irreversible, as a large part of the melted water will drain/evaporate during the process, and the build-up of an equivalent amount of

Possible role of thromboxane A2 in remote hind limb preconditioning-induced cardioprotection.

PubMed

Sharma, Roohani; Randhawa, Puneet Kaur; Singh, Nirmal; Jaggi, Amteshwar Singh

2016-01-01

Remote hind limb preconditioning (RIPC) is a protective strategy in which short episodes of ischemia and reperfusion in a remote organ (hind limb) protects the target organ (heart) against sustained ischemic reperfusion injury. The present study was designed to investigate the possible role of thromboxane A2 in RIPC-induced cardioprotection in rats. Remote hind limb preconditioning was performed by four episodes of 5 min of inflation and 5 min of deflation of pressure cuff. Occlusion of the hind limb with blood pressure cuff is most feasible, non-invasive, clinically relevant, and safe method for inducing RIPC. Isolated rat hearts were perfused on Langendorff apparatus and were subjected to global ischemia for 30 min followed by 120-min reperfusion. The levels of lactate dehydrogenase (LDH) and creatine kinase (CK) were measured in coronary effluent to assess the degree of myocardial injury. The extent of myocardial infarct size along with the functional parameters including left ventricular developed pressure (LVDP), dp/dtmax, and dp/dtmin were also measured. Ozagrel (thromboxane synthase inhibitor) and seratrodast (thromboxane A2 receptor antagonist) were employed as pharmacological modulators of thromboxane A2. Remote hind limb preconditioning significantly attenuated ischemia/reperfusion-induced myocardial injury and produced cardioprotective effects. However, administration of ozagrel and seratrodast completely abolished the cardioprotective effects of RIPC suggesting the key role of thromboxane A2 in RIPC-induced cardioprotection. It may be concluded that brief episodes of preconditioning ischemia and reperfusion activates the thromboxane synthase enzyme that produces thromboxane A2, which may elicit cardioprotection either involving humoral or neurogenic pathway.

On coupling fluid plasma and kinetic neutral physics models

DOE PAGES

Joseph, I.; Rensink, M. E.; Stotler, D. P.; ...

2017-03-01

The coupled fluid plasma and kinetic neutral physics equations are analyzed through theory and simulation of benchmark cases. It is shown that coupling methods that do not treat the coupling rates implicitly are restricted to short time steps for stability. Fast charge exchange, ionization and recombination coupling rates exist, even after constraining the solution by requiring that the neutrals are at equilibrium. For explicit coupling, the present implementation of Monte Carlo correlated sampling techniques does not allow for complete convergence in slab geometry. For the benchmark case, residuals decay with particle number and increase with grid size, indicating that theymore » scale in a manner that is similar to the theoretical prediction for nonlinear bias error. Progress is reported on implementation of a fully implicit Jacobian-free Newton–Krylov coupling scheme. The present block Jacobi preconditioning method is still sensitive to time step and methods that better precondition the coupled system are under investigation.« less

Equivalent cardioprotection induced by ischemic and hypoxic preconditioning.

PubMed

Xiang, Xujin; Lin, Haixia; Liu, Jin; Duan, Zeyan

2013-04-01

We aimed to compare cardioprotection induced by various hypoxic preconditioning (HPC) and ischemic preconditioning (IPC) protocols. Isolated rat hearts were randomly divided into 7 groups (n = 7 per group) and received 3 or 5 cycles of 3-minute ischemia or hypoxia followed by 3-minute reperfusion (IPC33 or HPC33 or IPC53 or HPC53 group), 3 cycles of 5-minute ischemia or hypoxia followed by 5-minute reperfusion (IPC35 group or HPC35 group), or 30-minute perfusion (ischemic/reperfusion group), respectively. Then all the hearts were subjected to 50-minute ischemia and 120-minute reperfusion. Cardiac function, infarct size, and coronary flow rate (CFR) were evaluated. Recovery of cardiac function and CFR in IPC35, HPC35, and HPC53 groups was significantly improved as compared with I/R group (p < 0.01). There were no significant differences in cardiac function parameters between IPC35 and HPC35 groups. Consistently, infarct size was significantly reduced in IPC35, HPC35, and HPC53 groups compared with ischemic/reperfusion group. Multiple-cycle short duration HPC exerted cardioprotection, which was as powerful as that of IPC. Georg Thieme Verlag KG Stuttgart · New York.

Arctic atmospheric preconditioning: do not rule out shortwave radiation just yet

NASA Astrophysics Data System (ADS)

Sedlar, J.

2017-12-01

Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus in recent years. A general consensus points to enhanced poleward atmospheric transport of moisture and heat during spring, effectively increasing the emission of longwave radiation to the surface. Studies have essentially ruled out the role of shortwave radiation as an effective preconditioning mechanism because of the relatively weak incident solar radiation and high surface albedo from sea ice and snow during spring. These conclusions, however, are derived primarily from atmospheric reanalysis data, which may not always represent an accurate depiction of the Arctic climate system. Here, observations of top of atmosphere radiation from state of the art satellite sensors are examined and compared with reanalysis and climate model data to examine the differences in the spring radiative budget over the Arctic Ocean for years with extreme low/high ice extent at the end of the ice melt season (September). Distinct biases are observed between satellite-based measurements and reanalysis/models, particularly for the amount of shortwave radiation trapped (warming effect) within the Arctic climate system during spring months. A connection between the differences in reanalysis/model surface albedo representation and the albedo observed by satellite is discussed. These results suggest that shortwave radiation should not be overlooked as a significant contributing mechanism to springtime Arctic atmospheric preconditioning.

Pigments identification of paintings using subspace distance unmixing algorithm

NASA Astrophysics Data System (ADS)

Li, Bin; Lyu, Shuqiang; Zhang, Dafeng; Dong, Qinghao

2018-04-01

In the digital protection of the cultural relics, the identification of the pigment mixtures on the surface of the painting has been the research spot for many years. In this paper, as a hyperspectral unmixing algorithm, sub-space distance unmixing is introduced to solve the problem of recognition of pigments mixture in paintings. Firstly, some mixtures of different pigments are designed to measure their reflectance spectra using spectrometer. Moreover, the factors affecting the unmixing accuracy of pigments' mixtures are discussed. The unmixing results of two cases with and without rice paper and its underlay as endmembers are compared. The experiment results show that the algorithm is able to unmixing the pigments effectively and the unmixing accuracy can be improved after considering the influence of spectra of the rich paper and the underlaying material.

Neuroprotective Effect of Antioxidants and Moderate Hypoxia as Combined Preconditioning in Cerebral Ischemia.

PubMed

Levchenkova, O S; Novikov, V E; Parfenov, E A; Kulagin, K N

2016-12-01

We studied combined effect of moderate hypoxia and compounds pQ-4, pQ-915, pQ-1032, and pQ-1104 on neurological deficit and survival of rats after bilateral ligation of common carotid arteries. Preconditioning including moderate hypoxia and treatment with compound pQ-4 produced a neuroprotective effect and increased animal survival during the early (by 51%) and late (by 33.5%) periods of modeled ischemia and reduced neurological deficit (by 50% and 41%, respectively). Moreover, this combination of preconditioning factors prevented postischemic excessive activation of free radical oxidation in brain hemispheres and blood serum.

Ischemic Preconditioning Increases the Tolerance of Fatty Liver to Hepatic Ischemia-Reperfusion Injury in the Rat

PubMed Central

Serafín, Anna; Roselló-Catafau, Joan; Prats, Neus; Xaus, Carme; Gelpí, Emilio; Peralta, Carmen

2002-01-01

Hepatic steatosis is a major risk factor in ischemia-reperfusion. The present study evaluates whether preconditioning, demonstrated to be effective in normal livers, could also confer protection in the presence of steatosis and investigates the potential underlying protective mechanisms. Fatty rats had increased hepatic injury and decreased survival after 60 minutes of ischemia compared with lean rats. Fatty livers showed a degree of neutrophil accumulation and microcirculatory alterations similar to that of normal livers. However, in presence of steatosis, an increased lipid peroxidation that could be reduced with glutathione-ester pretreatment was observed after hepatic reperfusion. Ischemic preconditioning reduced hepatic injury and increased animal survival. Both in normal and fatty livers, this endogenous protective mechanism was found to control lipid peroxidation, hepatic microcirculation failure, and neutrophil accumulation, reducing the subsequent hepatic injury. These beneficial effects could be mediated by nitric oxide, because the inhibition of nitric oxide synthesis and nitric oxide donor pretreatment abolished and simulated, respectively, the benefits of preconditioning. Thus, ischemic preconditioning could be an effective surgical strategy to reduce the hepatic ischemia-reperfusion injury in normal and fatty livers under normothermic conditions, including hepatic resections, and liver transplantation. PMID:12163383

Exploiting active subspaces to quantify uncertainty in the numerical simulation of the HyShot II scramjet

NASA Astrophysics Data System (ADS)

Constantine, P. G.; Emory, M.; Larsson, J.; Iaccarino, G.

2015-12-01

We present a computational analysis of the reactive flow in a hypersonic scramjet engine with focus on effects of uncertainties in the operating conditions. We employ a novel methodology based on active subspaces to characterize the effects of the input uncertainty on the scramjet performance. The active subspace identifies one-dimensional structure in the map from simulation inputs to quantity of interest that allows us to reparameterize the operating conditions; instead of seven physical parameters, we can use a single derived active variable. This dimension reduction enables otherwise infeasible uncertainty quantification, considering the simulation cost of roughly 9500 CPU-hours per run. For two values of the fuel injection rate, we use a total of 68 simulations to (i) identify the parameters that contribute the most to the variation in the output quantity of interest, (ii) estimate upper and lower bounds on the quantity of interest, (iii) classify sets of operating conditions as safe or unsafe corresponding to a threshold on the output quantity of interest, and (iv) estimate a cumulative distribution function for the quantity of interest.

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

PubMed

Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

A Least-Squares Commutator in the Iterative Subspace Method for Accelerating Self-Consistent Field Convergence.

PubMed

Li, Haichen; Yaron, David J

2016-11-08

A least-squares commutator in the iterative subspace (LCIIS) approach is explored for accelerating self-consistent field (SCF) calculations. LCIIS is similar to direct inversion of the iterative subspace (DIIS) methods in that the next iterate of the density matrix is obtained as a linear combination of past iterates. However, whereas DIIS methods find the linear combination by minimizing a sum of error vectors, LCIIS minimizes the Frobenius norm of the commutator between the density matrix and the Fock matrix. This minimization leads to a quartic problem that can be solved iteratively through a constrained Newton's method. The relationship between LCIIS and DIIS is discussed. Numerical experiments suggest that LCIIS leads to faster convergence than other SCF convergence accelerating methods in a statistically significant sense, and in a number of cases LCIIS leads to stable SCF solutions that are not found by other methods. The computational cost involved in solving the quartic minimization problem is small compared to the typical cost of SCF iterations and the approach is easily integrated into existing codes. LCIIS can therefore serve as a powerful addition to SCF convergence accelerating methods in computational quantum chemistry packages.

A Robust Locally Preconditioned Semi-Coarsening Multigrid Algorithm for the 2-D Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Cain, Michael D.

1999-01-01

The goal of this thesis is to develop an efficient and robust locally preconditioned semi-coarsening multigrid algorithm for the two-dimensional Navier-Stokes equations. This thesis examines the performance of the multigrid algorithm with local preconditioning for an upwind-discretization of the Navier-Stokes equations. A block Jacobi iterative scheme is used because of its high frequency error mode damping ability. At low Mach numbers, the performance of a flux preconditioner is investigated. The flux preconditioner utilizes a new limiting technique based on local information that was developed by Siu. Full-coarsening and-semi-coarsening are examined as well as the multigrid V-cycle and full multigrid. The numerical tests were performed on a NACA 0012 airfoil at a range of Mach numbers. The tests show that semi-coarsening with flux preconditioning is the most efficient and robust combination of coarsening strategy, and iterative scheme - especially at low Mach numbers.

A Gaussian-based rank approximation for subspace clustering

NASA Astrophysics Data System (ADS)

Xu, Fei; Peng, Chong; Hu, Yunhong; He, Guoping

2018-04-01

Low-rank representation (LRR) has been shown successful in seeking low-rank structures of data relationships in a union of subspaces. Generally, LRR and LRR-based variants need to solve the nuclear norm-based minimization problems. Beyond the success of such methods, it has been widely noted that the nuclear norm may not be a good rank approximation because it simply adds all singular values of a matrix together and thus large singular values may dominant the weight. This results in far from satisfactory rank approximation and may degrade the performance of lowrank models based on the nuclear norm. In this paper, we propose a novel nonconvex rank approximation based on the Gaussian distribution function, which has demanding properties to be a better rank approximation than the nuclear norm. Then a low-rank model is proposed based on the new rank approximation with application to motion segmentation. Experimental results have shown significant improvements and verified the effectiveness of our method.

Exercise preconditioning improves behavioral functions following transient cerebral ischemia induced by 4-vessel occlusion (4-VO) in rats.

PubMed

Tahamtan, Mahshid; Allahtavakoli, Mohammad; Abbasnejad, Mehdi; Roohbakhsh, Ali; Taghipour, Zahra; Taghavi, Mohsen; Khodadadi, Hassan; Shamsizadeh, Ali

2013-12-01

There is evidence that exercise decreases ischemia/reperfusion injury in rats. Since behavioral deficits are the main outcome in patients after stroke, our study was designed to investigate whether exercise preconditioning improves the acute behavioral functions and also brain inflammatory injury following cerebral ischemia. Male rats weighing 250-300 g were randomly allocated into five experimental groups. Exercise was performed on a treadmill 30min/day for 3 weeks. Ischemia was induced by 4-vessel occlusion method. Recognition memory was assessed by novel object recognition task (NORT) and step-through passive avoidance task. Sensorimotor function and motor movements were evaluated by adhesive removal test and ledged beam-walking test, respectively. Brain inflammatory injury was evaluated by histological assessment. In NORT, the discrimination ratio was decreased after ischemia (P < 0.05) and exercise preconditioning improved it in ischemic animals. In the passive avoidance test, a significant reduction in response latency was observed in the ischemic group. Exercise preconditioning significantly decreased the response latency in the ischemic rats (P < 0.001). In the adhesive removal test, latency to touch and remove the sticky labels from forepaw was increased following induction of ischemia (all P < 0.001) and exercise preconditioning decreased these indices compared to the ischemic group (all P < 0.001). In the ledged beam-walking test, the slip ratio was increased following ischemia (P < 0.05).  In the ischemia group, marked neuronal injury in hippocampus was observed. These neuropathological changes were attenuated by exercise preconditioning (P < 0.001). Our results showed that exercise preconditioning improves behavioral functions and maintains more viable cells in the dorsal hippocampus of the ischemic brain.

Towards automatic music transcription: note extraction based on independent subspace analysis

NASA Astrophysics Data System (ADS)

Wellhausen, Jens; Hoynck, Michael

2005-01-01

Due to the increasing amount of music available electronically the need of automatic search, retrieval and classification systems for music becomes more and more important. In this paper an algorithm for automatic transcription of polyphonic piano music into MIDI data is presented, which is a very interesting basis for database applications, music analysis and music classification. The first part of the algorithm performs a note accurate temporal audio segmentation. In the second part, the resulting segments are examined using Independent Subspace Analysis to extract sounding notes. Finally, the results are used to build a MIDI file as a new representation of the piece of music which is examined.

Towards automatic music transcription: note extraction based on independent subspace analysis

NASA Astrophysics Data System (ADS)

Wellhausen, Jens; Höynck, Michael

2004-12-01

Due to the increasing amount of music available electronically the need of automatic search, retrieval and classification systems for music becomes more and more important. In this paper an algorithm for automatic transcription of polyphonic piano music into MIDI data is presented, which is a very interesting basis for database applications, music analysis and music classification. The first part of the algorithm performs a note accurate temporal audio segmentation. In the second part, the resulting segments are examined using Independent Subspace Analysis to extract sounding notes. Finally, the results are used to build a MIDI file as a new representation of the piece of music which is examined.

Preconditioning Triggered by Carbon Monoxide (CO) Provides Neuronal Protection Following Perinatal Hypoxia-Ischemia

PubMed Central

Widerøe, Marius; Alves, Paula M.; Vercelli, Alessandro; Vieira, Helena L. A.

2012-01-01

Perinatal hypoxia-ischemia is a major cause of acute mortality in newborns and cognitive and motor impairments in children. Cerebral hypoxia-ischemia leads to excitotoxicity and necrotic and apoptotic cell death, in which mitochondria play a major role. Increased resistance against major damage can be achieved by preconditioning triggered by subtle insults. CO, a toxic molecule that is also generated endogenously, may have a role in preconditioning as low doses can protect against inflammation and apoptosis. In this study, the role of CO-induced preconditioning on neurons was addressed in vitro and in vivo. The effect of 1 h of CO treatment on neuronal death (plasmatic membrane permeabilization and chromatin condensation) and bcl-2 expression was studied in cerebellar granule cells undergoing to glutamate-induced apoptosis. CO's role was studied in vivo in the Rice-Vannucci model of neonatal hypoxia-ischemia (common carotid artery ligature +75 min at 8% oxygen). Apoptotic cells, assessed by Nissl staining were counted with a stereological approach and cleaved caspase 3-positive profiles in the hippocampus were assessed. Apoptotic hallmarks were analyzed in hippocampal extracts by Western Blot. CO inhibited excitotoxicity-induced cell death and increased Bcl-2 mRNA in primary cultures of neurons. In vivo, CO prevented hypoxia-ischemia induced apoptosis in the hippocampus, limited cytochrome c released from mitochondria and reduced activation of caspase-3. Still, Bcl-2 protein levels were higher in hippocampus of CO pre-treated rat pups. Our results show that CO preconditioning elicits a molecular cascade that limits neuronal apoptosis. This could represent an innovative therapeutic strategy for high-risk cerebral hypoxia-ischemia patients, in particular neonates. PMID:22952602

Voltage Preconditioning Allows Modulated Gene Expression in Neurons Using PEI-complexed siRNA

PubMed Central

Sridharan, Arati; Patel, Chetan; Muthuswamy, Jit

2013-01-01

We present here a high efficiency, high viability siRNA-delivery method using a voltage-controlled chemical transfection strategy to achieve modulated delivery of polyethylenimine (PEI) complexed with siRNA in an in vitro culture of neuro2A cells and neurons. Low voltage pulses were applied to adherent cells before the administration of PEI-siRNA complexes. Live assays of neuro2a cells transfected with fluorescently tagged siRNA showed an increase in transfection efficiency from 62 ± 14% to 98 ± 3.8% (after −1 V). In primary hippocampal neurons, transfection efficiencies were increased from 30 ± 18% to 76 ± 18% (after −1 V). Negligible or low-level transfection was observed after preconditioning at higher voltages, suggesting an inverse relationship with applied voltage. Experiments with propidium iodide ruled out the role of electroporation in the transfection of siRNAs suggesting an alternate electro-endocytotic mechanism. In addition, image analysis of preconditioned and transfected cells demonstrates siRNA uptake and loading that is tuned to preconditioning voltage levels. There is approximately a fourfold increase in siRNA loading after preconditioning at −1 V compared with the same at ±2–3 V. Modulated gene expression is demonstrated in a functional knockdown of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in neuro2A cells using siRNA. Cell density and dendritic morphological changes are also demonstrated in modulated knockdown of brain derived neurotrophic factor (BDNF) in primary hippocampal neurons. The method reported here has potential applications in the development of high-throughput screening systems for large libraries of siRNA molecules involving difficult-to-transfect cells like neurons. PMID:23531602

Preconditioning methods influence tumor property in an orthotopic bladder urothelial carcinoma rat model

PubMed Central

MIYAZAKI, KOZO; MORIMOTO, YUJI; NISHIYAMA, NOBUHIRO; SATOH, HIROYUKI; TANAKA, MASAMITSU; SHINOMIYA, NARIYOSHI; ITO, KEIICHI

2014-01-01

Urothelial carcinoma (UC) is an extremely common type of cancer that occurs in the bladder. It has a particularly high rate of recurrence. Therefore, preclinical studies using animal models are essential to determine effective forms of treatment. In the present study, in order to establish an orthotopic bladder UC animal model with clinical relevance, the effects of preconditioning methods on properties of the developed tumor were evaluated. The bladder cavity was pretreated with phosphate-buffered saline (PBS), acid-base, trypsin (TRY) or poly (L-lysine) (PLL) and then rat UC cells (AY-27) (4×106 cells) were inoculated. The results demonstrated that, two weeks later, the tumorigenic rate (88%) and tumor count (2.3 per rat) were not significantly different among the preconditioning methods, whereas tumor volume and invasion depth into bladder tissue were significantly different. Average tumor volumes were >50 mm3 in the PBS and acid-base-treated groups and <10 mm3 in the TRY- and PLL-treated groups. The percentage of invasive tumors (T2 or more advanced stage) was ∼75% of total tumors in the PBS- and acid-base-treated groups, whereas the percentages were reduced in the TRY- and PLL-treated groups (58 and 32%, respectively). Non-invasive tumors (Ta or T1) accounted for 54% of tumors in the PLL-treated group, which was 2-5-fold higher than the percentages in the remaining groups. Properties of the developed tumor in the rat orthotopic UC model were different depending on preconditioning methods. Therefore, different animal models suitable for a discrete preclinical examination may be established by using the appropriate preconditioning condition. PMID:24649309

Hypoxic preconditioning protects photoreceptors against light damage independently of hypoxia inducible transcription factors in rods.

PubMed

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.

Audiovisual preconditioning enhances the efficacy of an anatomical dissection course: A randomised study.

PubMed

Collins, Anne M; Quinlan, Christine S; Dolan, Roisin T; O'Neill, Shane P; Tierney, Paul; Cronin, Kevin J; Ridgway, Paul F

2015-07-01

The benefits of incorporating audiovisual materials into learning are well recognised. The outcome of integrating such a modality in to anatomical education has not been reported previously. The aim of this randomised study was to determine whether audiovisual preconditioning is a useful adjunct to learning at an upper limb dissection course. Prior to instruction participants completed a standardised pre course multiple-choice questionnaire (MCQ). The intervention group was subsequently shown a video with a pre-recorded commentary. Following initial dissection, both groups completed a second MCQ. The final MCQ was completed at the conclusion of the course. Statistical analysis confirmed a significant improvement in the performance in both groups over the duration of the three MCQs. The intervention group significantly outperformed their control group counterparts immediately following audiovisual preconditioning and in the post course MCQ. Audiovisual preconditioning is a practical and effective tool that should be incorporated in to future course curricula to optimise learning. Level of evidence This study appraises an intervention in medical education. Kirkpatrick Level 2b (modification of knowledge). Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Parallel Cartesian grid refinement for 3D complex flow simulations

NASA Astrophysics Data System (ADS)

Angelidis, Dionysios; Sotiropoulos, Fotis

2013-11-01

A second order accurate method for discretizing the Navier-Stokes equations on 3D unstructured Cartesian grids is presented. Although the grid generator is based on the oct-tree hierarchical method, fully unstructured data-structure is adopted enabling robust calculations for incompressible flows, avoiding both the need of synchronization of the solution between different levels of refinement and usage of prolongation/restriction operators. The current solver implements a hybrid staggered/non-staggered grid layout, employing the implicit fractional step method to satisfy the continuity equation. The pressure-Poisson equation is discretized by using a novel second order fully implicit scheme for unstructured Cartesian grids and solved using an efficient Krylov subspace solver. The momentum equation is also discretized with second order accuracy and the high performance Newton-Krylov method is used for integrating them in time. Neumann and Dirichlet conditions are used to validate the Poisson solver against analytical functions and grid refinement results to a significant reduction of the solution error. The effectiveness of the fractional step method results in the stability of the overall algorithm and enables the performance of accurate multi-resolution real life simulations. This material is based upon work supported by the Department of Energy under Award Number DE-EE0005482.

Robust parallel iterative solvers for linear and least-squares problems, Final Technical Report

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

Saad, Yousef

2014-01-16

The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners formore » solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered

PBMC: Pre-conditioned Backward Monte Carlo code for radiative transport in planetary atmospheres

NASA Astrophysics Data System (ADS)

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.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

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

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Regulated production of free radicals by the mitochondrial electron transport chain: Cardiac ischemic preconditioning.

PubMed

Matsuzaki, Satoshi; Szweda, Pamela A; Szweda, Luke I; Humphries, Kenneth M

2009-11-30

Excessive production of free radicals by mitochondria is associated with, and likely contributes to, the progression of numerous pathological conditions. Nevertheless, the production of free radicals by the mitochondria may have important biological functions under normal or stressed conditions by activating or modulating redox-sensitive cellular signaling pathways. This raises the intriguing possibility that regulated mitochondrial free radical production occurs via mechanisms that are distinct from pathologies associated with oxidative damage. Indeed, the capacity of mitochondria to produce free radicals in a limited manner may play a role in ischemic preconditioning, the phenomenon whereby short bouts of ischemia protect from subsequent prolonged ischemia and reperfusion. Ischemic preconditioning can thus serve as an important model system for defining regulatory mechanisms that allow for transient, signal-inducing, production of free radicals by mitochondria. Defining how these mechanism(s) occur will provide insight into therapeutic approaches that minimize oxidative damage without altering normal cellular redox biology. The aim of this review is to present and discuss evidence for the regulated production of superoxide by the electron transport chain within the ischemic preconditioning paradigm of redox regulation.

Ischemic preconditioning provides both acute and delayed protection against renal ischemia and reperfusion injury in mice.

PubMed

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.

The anti-apoptotic effect of fluid mechanics preconditioning by cells membrane and mitochondria in rats brain microvascular endothelial cells.

PubMed

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.

The U.S. Geological Survey Modular Ground-Water Model - PCGN: A Preconditioned Conjugate Gradient Solver with Improved Nonlinear Control

USGS Publications Warehouse

Naff, Richard L.; Banta, Edward R.

2008-01-01

The preconditioned conjugate gradient with improved nonlinear control (PCGN) package provides addi-tional means by which the solution of nonlinear ground-water flow problems can be controlled as compared to existing solver packages for MODFLOW. Picard iteration is used to solve nonlinear ground-water flow equations by iteratively solving a linear approximation of the nonlinear equations. The linear solution is provided by means of the preconditioned conjugate gradient algorithm where preconditioning is provided by the modi-fied incomplete Cholesky algorithm. The incomplete Cholesky scheme incorporates two levels of fill, 0 and 1, in which the pivots can be modified so that the row sums of the preconditioning matrix and the original matrix are approximately equal. A relaxation factor is used to implement the modified pivots, which determines the degree of modification allowed. The effects of fill level and degree of pivot modification are briefly explored by means of a synthetic, heterogeneous finite-difference matrix; results are reported in the final section of this report. The preconditioned conjugate gradient method is coupled with Picard iteration so as to efficiently solve the nonlinear equations associated with many ground-water flow problems. The description of this coupling of the linear solver with Picard iteration is a primary concern of this document.

TIGAR contributes to ischemic tolerance induced by cerebral preconditioning through scavenging of reactive oxygen species and inhibition of apoptosis

PubMed Central

Zhou, Jun-Hao; Zhang, Tong-Tong; Song, Dan-Dan; Xia, Yun-Fei; Qin, Zheng-Hong; Sheng, Rui

2016-01-01

Previous study showed that TIGAR (TP53-induced glycolysis and apoptosis regulator) protected ischemic brain injury via enhancing pentose phosphate pathway (PPP) flux and preserving mitochondria function. This study was aimed to study the role of TIGAR in cerebral preconditioning. The ischemic preconditioning (IPC) and isoflurane preconditioning (ISO) models were established in primary cultured cortical neurons and in mice. Both IPC and ISO increased TIGAR expression in cortical neurons. Preconditioning might upregulate TIGAR through SP1 transcription factor. Lentivirus mediated knockdown of TIGAR significantly abolished the ischemic tolerance induced by IPC and ISO. ISO also increased TIGAR in mouse cortex and hippocampus and alleviated subsequent brain ischemia-reperfusion injury, while the ischemic tolerance induced by ISO was eliminated with TIGAR knockdown in mouse brain. ISO increased the production of NADPH and glutathione (GSH), and scavenged reactive oxygen species (ROS), while TIGAR knockdown decreased GSH and NADPH production and increased the level of ROS. Supplementation of ROS scavenger NAC and PPP product NADPH effectively rescue the neuronal injury caused by TIGAR deficiency. Notably, TIGAR knockdown inhibited ISO-induced anti-apoptotic effects in cortical neurons. These results suggest that TIGAR participates in the cerebral preconditioning through reduction of ROS and subsequent cell apoptosis. PMID:27256465

A Jacobian-free Newton Krylov method for mortar-discretized thermomechanical contact problems

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

Hansen, Glen, E-mail: Glen.Hansen@inl.gov

2011-07-20

Multibody contact problems are common within the field of multiphysics simulation. Applications involving thermomechanical contact scenarios are also quite prevalent. Such problems can be challenging to solve due to the likelihood of thermal expansion affecting contact geometry which, in turn, can change the thermal behavior of the components being analyzed. This paper explores a simple model of a light water reactor nuclear fuel rod, which consists of cylindrical pellets of uranium dioxide (UO{sub 2}) fuel sealed within a Zircalloy cladding tube. The tube is initially filled with helium gas, which fills the gap between the pellets and cladding tube. Themore » accurate modeling of heat transfer across the gap between fuel pellets and the protective cladding is essential to understanding fuel performance, including cladding stress and behavior under irradiated conditions, which are factors that affect the lifetime of the fuel. The thermomechanical contact approach developed here is based on the mortar finite element method, where Lagrange multipliers are used to enforce weak continuity constraints at participating interfaces. In this formulation, the heat equation couples to linear mechanics through a thermal expansion term. Lagrange multipliers are used to formulate the continuity constraints for both heat flux and interface traction at contact interfaces. The resulting system of nonlinear algebraic equations are cast in residual form for solution of the transient problem. A Jacobian-free Newton Krylov method is used to provide for fully-coupled solution of the coupled thermal contact and heat equations.« less

A Jacobian-Free Newton Krylov Method for Mortar-Discretized Thermomechanical Contact Problems

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

Glen Hansen

2011-07-01

Multibody contact problems are common within the field of multiphysics simulation. Applications involving thermomechanical contact scenarios are also quite prevalent. Such problems can be challenging to solve due to the likelihood of thermal expansion affecting contact geometry which, in turn, can change the thermal behavior of the components being analyzed. This paper explores a simple model of a light water reactor nuclear reactor fuel rod, which consists of cylindrical pellets of uranium dioxide (UO2) fuel sealed within a Zircalloy cladding tube. The tube is initially filled with helium gas, which fills the gap between the pellets and cladding tube. Themore » accurate modeling of heat transfer across the gap between fuel pellets and the protective cladding is essential to understanding fuel performance, including cladding stress and behavior under irradiated conditions, which are factors that affect the lifetime of the fuel. The thermomechanical contact approach developed here is based on the mortar finite element method, where Lagrange multipliers are used to enforce weak continuity constraints at participating interfaces. In this formulation, the heat equation couples to linear mechanics through a thermal expansion term. Lagrange multipliers are used to formulate the continuity constraints for both heat flux and interface traction at contact interfaces. The resulting system of nonlinear algebraic equations are cast in residual form for solution of the transient problem. A Jacobian-free Newton Krylov method is used to provide for fully-coupled solution of the coupled thermal contact and heat equations.« less

On optimal improvements of classical iterative schemes for Z-matrices

NASA Astrophysics Data System (ADS)

Noutsos, D.; Tzoumas, M.

2006-04-01

Many researchers have considered preconditioners, applied to linear systems, whose matrix coefficient is a Z- or an M-matrix, that make the associated Jacobi and Gauss-Seidel methods converge asymptotically faster than the unpreconditioned ones. Such preconditioners are chosen so that they eliminate the off-diagonal elements of the same column or the elements of the first upper diagonal [Milaszewicz, LAA 93 (1987) 161-170], Gunawardena et al. [LAA 154-156 (1991) 123-143]. In this work we generalize the previous preconditioners to obtain optimal methods. "Good" Jacobi and Gauss-Seidel algorithms are given and preconditioners, that eliminate more than one entry per row, are also proposed and analyzed. Moreover, the behavior of the above preconditioners to the Krylov subspace methods is studied.

Preconditioning with the traditional Chinese medicine Huang-Lian-Jie-Du-Tang initiates HIF-1α-dependent neuroprotection against cerebral ischemia in rats.

PubMed

Zhang, Qichun; Bian, Huimin; Li, Yu; Guo, Liwei; Tang, Yuping; Zhu, Huaxu

2014-06-11

Huang-Lian-Jie-Du-Tang (HLJDT) is a classical heat-clearing and detoxicating formula of traditional Chinese medicine that is widely used to treat stroke. The present study was designed to investigate the effects of HLJDT preconditioning on neurons under oxygen and glucose deprivation (OGD) and rats subjected to middle cerebral artery occlusion (MCAO). A stroke model of rats was obtained through MCAO. Following HLJDT preconditioning, the cerebral infarction volume, cerebral water content, and neurological deficient score were determined. Cerebral cortical neurons cultured in vitro were preconditioned with HLJDT and then subjected to OGD treatment. The release of lactate dehydrogenase (LDH) from neurons was detected. The levels of hypoxia-inducible factor-1α (HIF-1α) and PI3K/Akt signaling were analyzed by western blotting, and the levels of erythropoietin (EPO) and vascular endothelial growth factor (VEGF) in the supernatant of the neurons and the plasma of MCAO rats were measured through a radioimmunological assay. The apoptosis and proliferation of neurons were analyzed by immunohistochemistry. HLJDT preconditioning significantly reduced the cerebral infarction volume and cerebral water content and ameliorated the neurological deficient score of MCAO rats. In addition, HLJDT preconditioning protected neurons against OGD. Increased HIF-1α, EPO, and VEGF levels and the activation of PI3K/Akt signaling were observed as a result of HLJDT preconditioning. Furthermore, HLJDT preconditioning was found to inhibit ischemia-induced neuron apoptosis and to promote neuron proliferation under conditions of ischemia/reperfusion. Both rats and neurons subjected to HLJDT preconditioning were able to resist ischemia/reperfusion or hypoxia injury through the inhibition of apoptosis and the enhancement of proliferation, and these effects were primarily dependent on the activation of the PI3K/Akt signaling pathway and HIF-1α. Copyright © 2014 Elsevier Ireland Ltd. All rights

On the selection of user-defined parameters in data-driven stochastic subspace identification

NASA Astrophysics Data System (ADS)

Priori, C.; De Angelis, M.; Betti, R.

2018-02-01

The paper focuses on the time domain output-only technique called Data-Driven Stochastic Subspace Identification (DD-SSI); in order to identify modal models (frequencies, damping ratios and mode shapes), the role of its user-defined parameters is studied, and rules to determine their minimum values are proposed. Such investigation is carried out using, first, the time histories of structural responses to stationary excitations, with a large number of samples, satisfying the hypothesis on the input imposed by DD-SSI. Then, the case of non-stationary seismic excitations with a reduced number of samples is considered. In this paper, partitions of the data matrix different from the one proposed in the SSI literature are investigated, together with the influence of different choices of the weighting matrices. The study is carried out considering two different applications: (1) data obtained from vibration tests on a scaled structure and (2) in-situ tests on a reinforced concrete building. Referring to the former, the identification of a steel frame structure tested on a shaking table is performed using its responses in terms of absolute accelerations to a stationary (white noise) base excitation and to non-stationary seismic excitations of low intensity. Black-box and modal models are identified in both cases and the results are compared with those from an input-output subspace technique. With regards to the latter, the identification of a complex hospital building is conducted using data obtained from ambient vibration tests.

Pre-Conditioning with Low-Level Laser (Light) Therapy: Light Before the Storm

PubMed Central

Agrawal, Tanupriya; Gupta, Gaurav K.; Rai, Vikrant; Carroll, James D.; Hamblin, Michael R.

2014-01-01

Pre-conditioning by ischemia, hyperthermia, hypothermia, hyperbaric oxygen (and numerous other modalities) is a rapidly growing area of investigation that is used in pathological conditions where tissue damage may be expected. The damage caused by surgery, heart attack, or stroke can be mitigated by pre-treating the local or distant tissue with low levels of a stress-inducing stimulus, that can induce a protective response against subsequent major damage. Low-level laser (light) therapy (LLLT) has been used for nearly 50 years to enhance tissue healing and to relieve pain, inflammation and swelling. The photons are absorbed in cytochrome(c) oxidase (unit four in the mitochondrial respiratory chain), and this enzyme activation increases electron transport, respiration, oxygen consumption and ATP production. A complex signaling cascade is initiated leading to activation of transcription factors and up- and down-regulation of numerous genes. Recently it has become apparent that LLLT can also be effective if delivered to normal cells or tissue before the actual insult or trauma, in a pre-conditioning mode. Muscles are protected, nerves feel less pain, and LLLT can protect against a subsequent heart attack. These examples point the way to wider use of LLLT as a pre-conditioning modality to prevent pain and increase healing after surgical/medical procedures and possibly to increase athletic performance. PMID:25552961

Voltage Preconditioning Allows Modulated Gene Expression in Neurons Using PEI-complexed siRNA.

PubMed

Sridharan, Arati; Patel, Chetan; Muthuswamy, Jit

2013-03-26

We present here a high efficiency, high viability siRNA-delivery method using a voltage-controlled chemical transfection strategy to achieve modulated delivery of polyethylenimine (PEI) complexed with siRNA in an in vitro culture of neuro2A cells and neurons. Low voltage pulses were applied to adherent cells before the administration of PEI-siRNA complexes. Live assays of neuro2a cells transfected with fluorescently tagged siRNA showed an increase in transfection efficiency from 62 ± 14% to 98 ± 3.8% (after -1 V). In primary hippocampal neurons, transfection efficiencies were increased from 30 ± 18% to 76 ± 18% (after -1 V). Negligible or low-level transfection was observed after preconditioning at higher voltages, suggesting an inverse relationship with applied voltage. Experiments with propidium iodide ruled out the role of electroporation in the transfection of siRNAs suggesting an alternate electro-endocytotic mechanism. In addition, image analysis of preconditioned and transfected cells demonstrates siRNA uptake and loading that is tuned to preconditioning voltage levels. There is approximately a fourfold increase in siRNA loading after preconditioning at -1 V compared with the same at ±2-3 V. Modulated gene expression is demonstrated in a functional knockdown of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in neuro2A cells using siRNA. Cell density and dendritic morphological changes are also demonstrated in modulated knockdown of brain derived neurotrophic factor (BDNF) in primary hippocampal neurons. The method reported here has potential applications in the development of high-throughput screening systems for large libraries of siRNA molecules involving difficult-to-transfect cells like neurons.Molecular Therapy-Nucleic Acids (2013) 2, e82; doi:10.1038/mtna.2013.10; published online 26 March 2013.

Comparison of bacterial attachment to platelet bags with and without preconditioning with plasma.

PubMed

Loza-Correa, M; Kalab, M; Yi, Q-L; Eltringham-Smith, L J; Sheffield, W P; Ramirez-Arcos, S

2017-07-01

Canadian Blood Services produces apheresis and buffy coat pooled platelet concentrates (PCs) stored in bags produced by two different manufacturers (A and B, respectively), both made of polyvinyl chloride-butyryl trihexyl citrate. This study was aimed at comparing Staphylococcus epidermidis adhesion to the inner surface of both bag types in the presence or absence of plasma factors. Sets (N = 2-6) of bags type A and B were left non-coated (control) or preconditioned with platelet-rich, platelet-poor or defibrinated plasma (PRP, PPP and DefibPPP, respectively). Each bag was inoculated with a 200-ml S. epidermidis culture adjusted to 0·5 colony-forming units/ml. Bags were incubated under platelet storage conditions for 7 days. After culture removal, bacteria attached to the plastic surface were either dislodged by sonication for bacterial quantification or examined in situ by scanning electron microscopy (SEM). Higher bacterial adhesion was observed to preconditioned PC bags than control containers for both bag types (P < 0·0001). Bacterial attachment to preconditioned bags was confirmed by SEM. Bacteria adhered equally to both types of containers in the presence of PRP, PPP and DefibPPP residues (P > 0·05). By contrast, a significant increase in bacterial adherence was observed to type A bags compared with type B bags in the absence of plasma (P < 0·05) [Correction added on 16 June 2017, after first online publication: this sentence has been corrected]. The ability of S. epidermidis to adhere to preconditioned platelet collection bags depends on the presence of plasma factors. Future efforts should be focused on reducing plasma proteins' attachment to platelet storage containers to decrease subsequent bacterial adhesion. © 2017 International Society of Blood Transfusion.

Effects of ischemic preconditioning and iloprost on myocardial ischemia-reperfusion damage in rats.

PubMed

Ay, Yasin; Kara, Ibrahim; Aydin, Cemalettin; Ay, Nuray Kahraman; Teker, Melike Elif; Senol, Serkan; Inan, Bekir; Basel, Halil; Uysal, Omer; Zeybek, Rahmi

2013-01-01

This study investigates the effects of cardiac ischemic preconditioning and iloprost on reperfusion damage in rats with myocardial ischemia/reperfusion. 38 male Wistar Albino rats used in this study were divided into 5 groups. The control group (Group 1) (n=6), ischemia/reperfusion (IR) group (Group 2) (n=8), cardiac ischemic preconditioning (CIP) group (Group 3) (n=8), iloprost (ILO) group (Group 4) (n=8), and cardiac ischemic preconditioning + iloprost (CIP+ILO) group (Group 5) (n=8). Pre-ischemia, 15 minutes post-ischemia, 45 minutes post-reperfusion, mean blood pressure (MBP), and heart rates (HR) were recorded. The rate-pressure product (RPP) was calculated. Post-reperfusion plasma creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), troponin (cTn) vlaues, and infarct size/area at risk (IS/AAR) were calculated from myocardial tissue samples. Arrhythmia and ST segment elevations were evaluated during the ischemia and reperfusion stages. Although the MBP, HR, RPP values, biochemical parameters of CK-MB and LDH levels, IS/AAR rates, ST segment elevation values were found to be similar in CIP and CIP+ILO groups and the IR and ILO groups (p>0.05), CIP-containing group values had a positively meaningful difference (p<0.05) compared with the IR and ILO group. While mild-moderate findings of damage were observed in Group 3 and Group 5, severely findings of damage were releaved in Group 2 and Group 4. The arrhythmia score of the ILO group was meaningfully lower (F: 41.4, p<0.001) than the IR group. We can conclude that the effects of myocardial reperfusion damage can be reduced by cardiac ischemic preconditioning, intravenous iloprost reduced the incidence of ventricular arrhythmia associated with reperfusion, and its use with CIP caused no additional changes.

A Molecular Approach to Epilepsy Management: from Current Therapeutic Methods to Preconditioning Efforts.

PubMed

Amini, Elham; Rezaei, Mohsen; Mohamed Ibrahim, Norlinah; Golpich, Mojtaba; Ghasemi, Rasoul; Mohamed, Zahurin; Raymond, Azman Ali; Dargahi, Leila; Ahmadiani, Abolhassan

2015-08-01

Epilepsy is the most common and chronic neurological disorder characterized by recurrent unprovoked seizures. The key aim in treating patients with epilepsy is the suppression of seizures. An understanding of focal changes that are involved in epileptogenesis may therefore provide novel approaches for optimal treatment of the seizure. Although the actual pathogenesis of epilepsy is still uncertain, recently growing lines of evidence declare that microglia and astrocyte activation, oxidative stress and reactive oxygen species (ROS) production, mitochondria dysfunction, and damage of blood-brain barrier (BBB) are involved in its pathogenesis. Impaired GABAergic function in the brain is probably the most accepted hypothesis regarding the pathogenesis of epilepsy. Clinical neuroimaging of patients and experimental modeling have demonstrated that seizures may induce neuronal apoptosis. Apoptosis signaling pathways are involved in the pathogenesis of several types of epilepsy such as temporal lobe epilepsy (TLE). The quality of life of patients is seriously affected by treatment-related problems and also by unpredictability of epileptic seizures. Moreover, the available antiepileptic drugs (AED) are not significantly effective to prevent epileptogenesis. Thus, novel therapies that are proficient to control seizure in people who are suffering from epilepsy are needed. The preconditioning method promises to serve as an alternative therapeutic approach because this strategy has demonstrated the capability to curtail epileptogenesis. For this reason, understanding of molecular mechanisms underlying brain tolerance induced by preconditioning is crucial to delineate new neuroprotective ways against seizure damage and epileptogenesis. In this review, we summarize the work to date on the pathogenesis of epilepsy and discuss recent therapeutic strategies in the treatment of epilepsy. We will highlight that novel therapy targeting such as preconditioning process holds great

Time-derivative preconditioning for viscous flows

NASA Technical Reports Server (NTRS)

Choi, Yunho; Merkle, Charles L.

1991-01-01

A time-derivative preconditioning algorithm that is effective over a wide range of flow conditions from inviscid to very diffusive flows and from low speed to supersonic flows was developed. This algorithm uses a viscous set of primary dependent variables to introduce well-conditioned eigenvalues and to avoid having a nonphysical time reversal for viscous flow. The resulting algorithm also provides a mechanism for controlling the inviscid and viscous time step parameters to be of order one for very diffusive flows, thereby ensuring rapid convergence at very viscous flows as well as for inviscid flows. Convergence capabilities are demonstrated through computation of a wide variety of problems.

Hypoxia preconditioning of mesenchymal stromal cells enhances PC3 cell lymphatic metastasis accompanied by VEGFR-3/CCR7 activation.

PubMed

Huang, Xin; Su, Kunkai; Zhou, Limin; Shen, Guofang; Dong, Qi; Lou, Yijia; Zheng, Shu

2013-12-01

Mesenchymal stromal cells (MSCs) in bone marrow may enhance tumor metastases through the secretion of chemokines. MSCs have been reported to home toward the hypoxic tumor microenvironment in vivo. In this study, we investigated prostate cancer PC3 cell behavior under the influence of hypoxia preconditioned MSCs and explored the related mechanism of prostate cancer lymphatic metastases in mice. Transwell assays revealed that VEGF-C receptor, VEGFR-3, as well as chemokine CCL21 receptor, CC chemokine receptor 7 (CCR7), were responsible for the migration of PC3 cells toward hypoxia preconditioned MSCs. Knock-in Ccr7 in PC3 cells also improved cell migration in vitro. Furthermore, when PC3 cells were labeled using the hrGfp-lentiviral vector, and were combined with hypoxia preconditioned MSCs for xenografting, it resulted in an enhancement of lymph node metastases accompanied by up-regulation of VEGFR-3 and CCR7 in primary tumors. Both PI3K/Akt/IκBα and JAK2/STAT3 signaling pathways were activated in xenografts in the presence of hypoxia-preconditioned MSCs. Unexpectedly, the p-VEGFR-2/VEGFR-2 ratio was attenuated accompanied by decreased JAK1 expression, indicating a switching-off of potential vascular signal within xenografts in the presence of hypoxia-preconditioned MSCs. Unlike results from other studies, VEGF-C maintained a stable expression in both conditions, which indicated that hypoxia preconditioning of MSCs did not influence VEGF-C secretion. Our results provide the new insights into the functional molecular events and signalings influencing prostate tumor metastases, suggesting a hopeful diagnosis and treatment in new approaches. © 2013 Wiley Periodicals, Inc.

Exact solution of mean-field plus an extended T = 1 nuclear pairing Hamiltonian in the seniority-zero symmetric subspace

NASA Astrophysics Data System (ADS)

Pan, Feng; Ding, Xiaoxue; Launey, Kristina D.; Dai, Lianrong; Draayer, Jerry P.

2018-05-01

An extended pairing Hamiltonian that describes multi-pair interactions among isospin T = 1 and angular momentum J = 0 neutron-neutron, proton-proton, and neutron-proton pairs in a spherical mean field, such as the spherical shell model, is proposed based on the standard T = 1 pairing formalism. The advantage of the model lies in the fact that numerical solutions within the seniority-zero symmetric subspace can be obtained more easily and with less computational time than those calculated from the mean-field plus standard T = 1 pairing model. Thus, large-scale calculations within the seniority-zero symmetric subspace of the model is feasible. As an example of the application, the average neutron-proton interaction in even-even N ∼ Z nuclei that can be suitably described in the f5 pg9 shell is estimated in the present model, with a focus on the role of np-pairing correlations.

Hypoxic-Preconditioned Bone Marrow Stem Cell Medium Significantly Improves Outcome After Retinal Ischemia in Rats

PubMed Central

Roth, Steven; Dreixler, John C.; Mathew, Biji; Balyasnikova, Irina; Mann, Jacob R.; Boddapati, Venkat; Xue, Lai; Lesniak, Maciej S.

2016-01-01

Purpose We have previously demonstrated the protective effect of bone marrow stem cell (BMSC)-conditioned medium in retinal ischemic injury. We hypothesized here that hypoxic preconditioning of stem cells significantly enhances the neuroprotective effect of the conditioned medium and thereby augments the protective effect in ischemic retina. Methods Rats were subjected to retinal ischemia by increasing intraocular pressure to 130 to 135 mm Hg for 55 minutes. Hypoxic-preconditioned, hypoxic unconditioned, or normoxic medium was injected into the vitreous 24 hours after ischemia ended. Recovery was assessed 7 days after injections by comparing electroretinography measurements, histologic examination, and apoptosis (TUNEL, terminal deoxynucleotidyl transferase–mediated dUTP nick end labeling assay). To compare proteins secreted into the medium in the groups and the effect of hypoxic exposure, we used rat cytokine arrays. Results Eyes injected with hypoxic BMSC–conditioned medium 24 hours after ischemia demonstrated significantly enhanced return of retinal function, decreased retinal ganglion cell layer loss, and attenuated apoptosis compared to those administered normoxic or hypoxic unconditioned medium. Hypoxic-preconditioned medium had 21 significantly increased protein levels compared to normoxic medium. Conclusions The medium from hypoxic-preconditioned BMSCs robustly restored retinal function and prevented cell loss after ischemia when injected 24 hours after ischemia. The protective effect was even more pronounced than in our previous studies of normoxic conditioned medium. Prosurvival signals triggered by the secretome may play a role in this neuroprotective effect. PMID:27367588

Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.

Investigation of Volcanic Seismo-Acoustic Signals: Applying Subspace Detection to Lava Fountain Activity at Etna Volcano

NASA Astrophysics Data System (ADS)

Sciotto, M.; Rowe, C. A.; Cannata, A.; Arrowsmith, S.; Privitera, E.; Gresta, S.

2011-12-01

The current eruption of Mount Etna, which began in January, 2011, has produced numerous energetic episodes of lava fountaining, which have bee recorded by the INGV seismic and acoustic sensors located on and around the volcano. The source of these events was the pit crater on the east flank of the Southeast crater of Etna. Simultaneously, small levels of activity were noted in the Bocca Nuova as well, prior to its lava fountaining activity. We will present an analysis of seismic and acoustic signals related to the 2011 activity wherein we apply the method of subspace detection to determine whether the source exhibits a temporal evolution within or between fountaining events, or otherwise produces repeating, classifiable events occurring through the continuous explosive degassing. We will examine not only the raw waveforms, but also spectral variations in time as well as time-varying statistical functions such as signal skewness and kurtosis. These results will be compared to straightforward cross-correlation analysis. In addition to classification performance, the subspace method has promise to outperform standard STA/LTA methods for real-time event detection in cases where similar events can be expected.

Bilirubin nanoparticle preconditioning protects against hepatic ischemia-reperfusion injury.

PubMed

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.

Parallelization of the preconditioned IDR solver for modern multicore computer systems

NASA Astrophysics Data System (ADS)

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).

Skin subspace color modeling for daytime and nighttime group activity recognition in confined operational spaces

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Poshtyar, Azin; Chan, Alex; Hu, Shuowen

2016-05-01

In many military and homeland security persistent surveillance applications, accurate detection of different skin colors in varying observability and illumination conditions is a valuable capability for video analytics. One of those applications is In-Vehicle Group Activity (IVGA) recognition, in which significant changes in observability and illumination may occur during the course of a specific human group activity of interest. Most of the existing skin color detection algorithms, however, are unable to perform satisfactorily in confined operational spaces with partial observability and occultation, as well as under diverse and changing levels of illumination intensity, reflection, and diffraction. In this paper, we investigate the salient features of ten popular color spaces for skin subspace color modeling. More specifically, we examine the advantages and disadvantages of each of these color spaces, as well as the stability and suitability of their features in differentiating skin colors under various illumination conditions. The salient features of different color subspaces are methodically discussed and graphically presented. Furthermore, we present robust and adaptive algorithms for skin color detection based on this analysis. Through examples, we demonstrate the efficiency and effectiveness of these new color skin detection algorithms and discuss their applicability for skin detection in IVGA recognition applications.

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

PubMed Central

Huang, Li

2017-01-01

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L1-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction. PMID:29253885

Effective matrix-free preconditioning for the augmented immersed interface method

NASA Astrophysics Data System (ADS)

Xia, Jianlin; Li, Zhilin; Ye, Xin

2015-12-01

We present effective and efficient matrix-free preconditioning techniques for the augmented immersed interface method (AIIM). AIIM has been developed recently and is shown to be very effective for interface problems and problems on irregular domains. GMRES is often used to solve for the augmented variable(s) associated with a Schur complement A in AIIM that is defined along the interface or the irregular boundary. The efficiency of AIIM relies on how quickly the system for A can be solved. For some applications, there are substantial difficulties involved, such as the slow convergence of GMRES (particularly for free boundary and moving interface problems), and the inconvenience in finding a preconditioner (due to the situation that only the products of A and vectors are available). Here, we propose matrix-free structured preconditioning techniques for AIIM via adaptive randomized sampling, using only the products of A and vectors to construct a hierarchically semiseparable matrix approximation to A. Several improvements over existing schemes are shown so as to enhance the efficiency and also avoid potential instability. The significance of the preconditioners includes: (1) they do not require the entries of A or the multiplication of AT with vectors; (2) constructing the preconditioners needs only O (log ⁡ N) matrix-vector products and O (N) storage, where N is the size of A; (3) applying the preconditioners needs only O (N) flops; (4) they are very flexible and do not require any a priori knowledge of the structure of A. The preconditioners are observed to significantly accelerate the convergence of GMRES, with heuristical justifications of the effectiveness. Comprehensive tests on several important applications are provided, such as Navier-Stokes equations on irregular domains with traction boundary conditions, interface problems in incompressible flows, mixed boundary problems, and free boundary problems. The preconditioning techniques are also useful for

Pharmacological preconditioning by milrinone: memory preserving and neuroprotective effect in ischemia-reperfusion injury in mice.

PubMed

Saklani, Reetu; Jaggi, Amteshwar; Singh, Nirmal

2010-07-01

We tested the neuroprotective effect of milrinone, a phosphodiesterase III inhibitor, in pharmacological preconditioning. Bilateral carotid artery occlusion for 12 min followed by reperfusion for 24 h produced ischemia-reperfusion (I/R) cerebral injury in male Swiss albino mice. Cerebral infarct size was measured using triphenyltetrazolium chloride staining. Memory was assessed using the Morris water maze test, and motor coordination was evaluated using the inclined beam walking test, rota-rod test, and lateral push test. Milrinone (50 microg/kg & 100 microg/kg i.v.) was administered 24 h before surgery in a separate group of animals to induce pharmacological preconditioning. I/R increased cerebral infarct size and impaired memory and motor coordination. Milrinone treatment significantly decreased cerebral infarct size and reversed I/R-induced impairments in memory and motor coordination. This neuroprotective effect was blocked by ruthenium red (3 mg/kg, s.c.), an intracellular ryanodine receptor blocker. These findings indicate that milrinone preconditioning exerts a marked neuroprotective effect on the ischemic brain, putatively due to increased intracellular calcium levels activating calcium-sensitive signal transduction cascades.

Peri-operative anaesthetic myocardial preconditioning and protection – cellular mechanisms and clinical relevance in cardiac anaesthesia

PubMed Central

Kunst, G; Klein, A A

2015-01-01

Preconditioning has been shown to reduce myocardial damage caused by ischaemia–reperfusion injury peri-operatively. Volatile anaesthetic agents have the potential to provide myocardial protection by anaesthetic preconditioning and, in addition, they also mediate renal and cerebral protection. A number of proof-of-concept trials have confirmed that the experimental evidence can be translated into clinical practice with regard to postoperative markers of myocardial injury; however, this effect has not been ubiquitous. The clinical trials published to date have also been too small to investigate clinical outcome and mortality. Data from recent meta-analyses in cardiac anaesthesia are also not conclusive regarding intra-operative volatile anaesthesia. These inconclusive clinical results have led to great variability currently in the type of anaesthetic agent used during cardiac surgery. This review summarises experimentally proposed mechanisms of anaesthetic preconditioning, and assesses randomised controlled clinical trials in cardiac anaesthesia that have been aimed at translating experimental results into the clinical setting. PMID:25764404

Beneficial effects of remote organ ischemic preconditioning on micro-rheological parameters during liver ischemia-reperfusion in the rat.

PubMed

Magyar, Zsuzsanna; Mester, Anita; Nadubinszky, Gabor; Varga, Gabor; Ghanem, Souleiman; Somogyi, Viktoria; Tanczos, Bence; Deak, Adam; Bidiga, Laszlo; Oltean, Mihai; Peto, Katalin; Nemeth, Norbert

2018-04-14

Remote ischemic preconditioning (RIPC) can be protective against the damage. However, there is no consensus on the optimal amount of tissue, the number and duration of the ischemic cycles, and the timing of the preconditioning. The hemorheological background of the process is also unknown. To investigate the effects of remote organ ischemic preconditioning on micro-rheological parameters during liver ischemia-reperfusion in rats. In anesthetized rats 60-minute partial liver ischemia was induced with 120-minute reperfusion (Control, n = 7). In the preconditioned groups a tourniquet was applied on the left thigh for 3×10 minutes 1 hour (RIPC-1, n = 7) or 24 hours (RIPC-24, n = 7) prior to the liver ischemia. Blood samples were taken before the operation and during the reperfusion. Acid-base, hematological parameters, erythrocyte aggregation and deformability were tested. Lactate concentration significantly increased by the end of the reperfusion. Erythrocyte deformability was improved in the RIPC-1 group, erythrocyte aggregation increased during the reperfusion, particularly in the RIPC-24 group. RIPC alleviated several hemorheological changes caused by the liver I/R. However, the optimal timing of the RIPC cannot be defined based on these results.

A Three Year Comparison of Acute Respiratory Disease, Shrink and Weight Gain in Preconditioned and Non-preconditioned Illinois Beef Calves Sold at the Same Auction and Mixed in a Feedlot

PubMed Central

Woods, G. T.; Mansfield, M. E.; Webb, R. J.

1973-01-01

During 1969 to 1971, 78 preconditioned (PC) and 79 non-preconditioned (NPC) beef calves were purchased at the same auction and mixed in a feedlot. Preconditioned calves were weaned 30 days before the sale, used to drinking from a tank, and vaccinated against blackleg, malignant edema, infectious bovine rhinotracheitis (IBR), parainfluenza-3 (PI3) and bovine virus diarrhea (BVD) in 1970 and 1971, and Pasteurella hemolytica and multocida in 1971. All vaccinations were completed two to three weeks before the sale. PC calves were given thiabenzadole. PC calves had significantly less shrink after shipment and in 1971 significantly more rapid daily gain during the first weeks of the feeding period. In 1969 more PC calves were treated for acute respiratory disease than NPC calves during an outbreak of PI3 and BVD infection. In 1970 and 1971 fewer PC than NPC calves were treated for acute respiratory tract disease during outbreaks of PI3 infection. The differences in clinical respiratory disease were significant in 1971. Inclusion of two doses of P. hemolytica and P. multocida bacterin before the sale in 1971 and use of an intranasal PI3 vaccine was considered to improve the PC program. Fecal egg counts for gastrointestinal nematodes were much lower in PC calves treated with thiabenzadole than untreated NPC calves. PMID:4355470

The mechanism of protection from 5 (N-ethyl-N-isopropyl)amiloride differs from that of ischemic preconditioning in rabbit heart.

PubMed

Sato, H; Miki, T; Vallabhapurapu, R P; Wang, P; Liu, G S; Cohen, M V; Downey, J M

1997-10-01

We investigated the effects of 5-(N-ethyl-N-isopropyl)amiloride (EIPA) on infarction in isolated rabbit hearts and cardiomyocytes. Thirty min of regional ischemia caused 29.6 +/- 2.8% of the risk zone to infarct in untreated Krebs buffer-perfused hearts. Treatment with EIPA (1 microM) for 20 min starting either 15 min before ischemia or 15 min after the onset of ischemia significantly reduced infarction to 5.4 +/- 2.0% and 7.0 +/- 1.0%, respectively (p < 0.01 versus untreated hearts). In both cases salvage was very similar to that seen with ischemic preconditioning (PC) (7.1 +/- 1.5% infarction). Unlike the case with ischemic preconditioning, however, protection from EIPA was not blocked by 50 microM polymyxin B, a PKC inhibitor, or 1 microM glibenclamide, a KATP channel blocker. Forty-five min of regional ischemia caused 51.0 +/- 2.9% infarction in untreated hearts. Ischemic preconditioning reduced infarction to 23.4 +/- 3.1% (p < 0.001 versus untreated hearts). In these hearts with longer periods of ischemia pretreatment with EIPA reduced infarction similarly to 28.8 +/- 2.1% (p < 0.01 versus untreated hearts). However, when EIPA was combined with ischemic PC, no further reduction in infarction was seen (23.8 +/- 3.5% infarction). To further elucidate the mechanism of EIPA's cardioprotective effect, this agent was also examined in isolated rabbit cardiomyocytes. Preconditioning caused a delay of about 30 min in the progressive increase in osmotic fragility that occurs during simulated ischemia. In contrast, EIPA had no effect on the time course of ischemia-induced osmotic fragility. Furthermore, EIPA treatment did not alter the salutary effect of ischemic preconditioning when the two were combined in this model. We conclude that Na+/H+ exchange inhibition limits myocardial infarction in the isolated rabbit heart by a mechanism which is quite different from that of ischemic preconditioning. Despite the apparently divergent mechanisms, EIPA's cardioprotective

Functional recovery in rat spinal cord injury induced by hyperbaric oxygen preconditioning.

PubMed

Lu, Pei-Gang; Hu, Sheng-Li; Hu, Rong; Wu, Nan; Chen, Zhi; Meng, Hui; Lin, Jiang-Kai; Feng, Hua

2012-12-01

It is a common belief that neurosurgical interventions can cause inevitable damage resulting from the procedure itself in surgery especially for intramedullary spinal cord tumors. The present study was designed to examine if hyperbaric oxygen preconditioning (HBO-PC) was neuroprotective against surgical injuries using a rat model of spinal cord injury (SCI). Sprague-Dawley rats were randomly divided into three groups: HBO-PC group, hypobaric hypoxic preconditioning (HH-PC) control group, and normobaric control group. All groups were subjected to SCI by weight drop device. Rats from each group were examined for neurological behavior and electrophysiological function. Tissue sections were analyzed by using immunohistochemistry, TdT-mediated dUTP-biotin nick end labeling, and axonal tract tracing. Significant neurological deficits were observed after SCI and HBO-PC and HH-PC improved neurological deficits 1 week post-injury. The latencies of motor-evoked potential and somatosensory-evoked potential were significantly delayed after SCI, which was attenuated by HBO-PC and HH-PC. Compared with normobaric control group, pretreatment with HBO and hypobaric hypoxia significantly reduced the number of TdT-mediated dUTP-biotin nick end labeling-positive cells, and increased nestin-positive cells. HBO-PC and HH-PC enhanced axonal growth after SCI. In conclusion, preconditioning with HBO and hypobaric hypoxia can facilitate functional recovery and suppress cell apoptosis after SCI and may prove to be a useful preventive strategy to neurosurgical SCI.

An M-step preconditioned conjugate gradient method for parallel computation

NASA Technical Reports Server (NTRS)

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.

Microglial ablation and lipopolysaccharide preconditioning affects pilocarpine-induced seizures in mice

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

Mirrione, M.M.; Mirrione, M.M.; Konomosa, D.K.

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 activationmore » 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.« less

Mesenchymal Stem/Stromal Cells in Regenerative Medicine: Can Preconditioning Strategies Improve Therapeutic Efficacy?

PubMed

Schäfer, Richard; Spohn, Gabriele; Baer, Patrick C

2016-07-01

Mesenchymal stem/stromal cells (MSCs) are becoming increasingly important for the development of cell therapeutics in regenerative medicine. Featuring immunomodulatory potential as well as secreting a variety of trophic factors, MSCs showed remarkable therapeutic effects in numerous preclinical disease models. However, sustainable translation of MSC therapies to the clinic is hampered by heterogeneity of MSCs and non-standardized in vitro culture technologies. Moreover, potent MSC therapeutics require MSCs with maximum regenerative capacity. There is growing evidence that in vitro preconditioning strategies of MSCs can optimize their therapeutic potential. In the following we will discuss achievements and challenges of the development of MSC therapies in regenerative medicine highlighting specific in vitro preconditioning strategies prior to cell transplantation to increase their therapeutic efficacy.

Mesenchymal Stem/Stromal Cells in Regenerative Medicine: Can Preconditioning Strategies Improve Therapeutic Efficacy?

PubMed Central

Schäfer, Richard; Spohn, Gabriele; Baer, Patrick C.

2016-01-01

Mesenchymal stem/stromal cells (MSCs) are becoming increasingly important for the development of cell therapeutics in regenerative medicine. Featuring immunomodulatory potential as well as secreting a variety of trophic factors, MSCs showed remarkable therapeutic effects in numerous preclinical disease models. However, sustainable translation of MSC therapies to the clinic is hampered by heterogeneity of MSCs and non-standardized in vitro culture technologies. Moreover, potent MSC therapeutics require MSCs with maximum regenerative capacity. There is growing evidence that in vitro preconditioning strategies of MSCs can optimize their therapeutic potential. In the following we will discuss achievements and challenges of the development of MSC therapies in regenerative medicine highlighting specific in vitro preconditioning strategies prior to cell transplantation to increase their therapeutic efficacy. PMID:27721701

Low-energy shock wave preconditioning reduces renal ischemic reperfusion injury caused by renal artery occlusion.

PubMed

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.

Decomposition of Near-Infrared Spectroscopy Signals Using Oblique Subspace Projections: Applications in Brain Hemodynamic Monitoring.

PubMed

Caicedo, Alexander; Varon, Carolina; Hunyadi, Borbala; Papademetriou, Maria; Tachtsidis, Ilias; Van Huffel, Sabine

2016-01-01

Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS) and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP), assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression model y = Ax + ϵ . SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP) with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first 3 days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen saturation from the

Involvement of SIRT1 in hypoxic down-regulation of c-Myc and β-catenin and hypoxic preconditioning effect of polyphenols

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

Hong, Kyung-Soo; Research Center for Ischemic Tissue regeneration, Pusan National University School of Medicine, Yangsan; Park, Jun-Ik

2012-03-01

SIRT1 has been found to function as a Class III deacetylase that affects the acetylation status of histones and other important cellular nonhistone proteins involved in various cellular pathways including stress responses and apoptosis. In this study, we investigated the role of SIRT1 signaling in the hypoxic down-regulations of c-Myc and β-catenin and hypoxic preconditioning effect of the red wine polyphenols such as piceatannol, myricetin, quercetin and resveratrol. We found that the expression of SIRT1 was significantly increased in hypoxia-exposed or hypoxic preconditioned HepG2 cells, which was closely associated with the up-regulation of HIF-1α and down-regulation of c-Myc and β-cateninmore » expression via deacetylation of these proteins. In addition, blockade of SIRT1 activation using siRNA or amurensin G, a new potent SIRT1 inhibitor, abolished hypoxia-induced HIF-1α expression but increased c-Myc and β-catenin expression. SIRT1 was also found to stabilize HIF-1α protein and destabilize c-Myc, β-catenin and PHD2 under hypoxia. We also found that myricetin, quercetin, piceatannol and resveratrol up-regulated HIF-1α and down-regulated c-Myc, PHD2 and β-catenin expressions via SIRT1 activation, in a manner that mimics hypoxic preconditioning. This study provides new insights of the molecular mechanisms of hypoxic preconditioning and suggests that polyphenolic SIRT1 activators could be used to mimic hypoxic/ischemic preconditioning. -- Graphical abstract: Polyphenols mimicked hypoxic preconditioning by up-regulating HIF-1α and SIRT1 and down-regulating c-Myc, PHD2, and β-catenin. HepG2 cells were pretreated with the indicated doses of myricetin (MYR; A), quercetin (QUR; B), or piceatannol (PIC; C) for 4 h and then exposed to hypoxia for 4 h. Levels of HIF-1α, SIRT1, c-Myc, β-catenin, and PHD2 were determined by western blot analysis. The data are representative of three individual experiments. Highlights: ► SIRT1 expression is increased in

A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness.

PubMed

Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E

2017-06-01

The purpose of this paper is to present a structural decomposition subspace (SDSS) method for decomposition of the joint torque to intrinsic, reflexive, and voluntary torques and identification of joint dynamic stiffness. First, it formulates a novel state-space representation for the joint dynamic stiffness modeled by a parallel-cascade structure with a concise parameter set that provides a direct link between the state-space representation matrices and the parallel-cascade parameters. Second, it presents a subspace method for the identification of the new state-space model that involves two steps: 1) the decomposition of the intrinsic and reflex pathways and 2) the identification of an impulse response model of the intrinsic pathway and a Hammerstein model of the reflex pathway. Extensive simulation studies demonstrate that SDSS has significant performance advantages over some other methods. Thus, SDSS was more robust under high noise conditions, converging where others failed; it was more accurate, giving estimates with lower bias and random errors. The method also worked well in practice and yielded high-quality estimates of intrinsic and reflex stiffnesses when applied to experimental data at three muscle activation levels. The simulation and experimental results demonstrate that SDSS accurately decomposes the intrinsic and reflex torques and provides accurate estimates of physiologically meaningful parameters. SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.

Toll-like receptor 3 pre-conditioning increases the therapeutic efficacy of umbilical cord mesenchymal stromal cells in a dextran sulfate sodium-induced colitis model.

PubMed

Fuenzalida, Patricia; Kurte, Mónica; Fernández-O'ryan, Catalina; Ibañez, Cristina; Gauthier-Abeliuk, Melanie; Vega-Letter, Ana María; Gonzalez, Paz; Irarrázabal, Carlos; Quezada, Nataly; Figueroa, Fernando; Carrión, Flavio

2016-05-01

Immunomodulatory properties of human umbilical cord-derived mesenchymal stromal cells (UCMSCs) can be differentially modulated by toll-like receptors (TLR) agonists. Here, the therapeutic efficacy of short TLR3 and TLR4 pre-conditioning of UCMSCs was evaluated in a dextran sulfate sodium (DSS)-induced colitis in mice. The novelty of this study is that although modulation of human MSCs activity by TLRs is not a new concept, this is the first time that short TLR pre-conditioning has been carried out in a murine inflammatory model of acute colitis. C57BL/6 mice were exposed to 2.5% dextran sulfate sodium (DSS) in drinking water ad libitum for 7 days. At days 1 and 3, mice were injected intraperitoneally with 1 × 10(6) UCMSCs untreated or TLR3 and TLR4 pre-conditioned UCMSCs. UCMSCs were pre-conditioned with poly(I:C) for TLR3 and LPS for TLR4 for 1 h at 37°C and 5% CO2. We evaluated clinical signs of disease and body weights daily. At the end of the experiment, colon length and histological changes were assessed. poly(I:C) pre-conditioned UCMSCs significantly ameliorated the clinical and histopathological severity of DSS-induced colitis compared with UCMSCs or LPS pre-conditioned UCMSCs. In contrast, infusion of LPS pre-conditioned UCMSCs significantly increased clinical signs of disease, colon shortening and histological disease index in DSS-induced colitis. These results show that short in vitro TLR3 pre-conditioning with poly(I:C) enhances the therapeutic efficacy of UCMSCs, which is a major breakthrough for developing improved treatments to patients with inflammatory bowel disease. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Neuroprotective effects of ischemic preconditioning on hippocampal CA1 pyramidal neurons through maintaining calbindin D28k immunoreactivity following subsequent transient cerebral ischemia

PubMed Central

Kim, In Hye; Jeon, Yong Hwan; Lee, Tae-Kyeong; Cho, Jeong Hwi; Lee, Jae-Chul; Park, Joon Ha; Ahn, Ji Hyeon; Shin, Bich-Na; Kim, Yang Hee; Hong, Seongkweon; Yan, Bing Chun; Won, Moo-Ho; Lee, Yun Lyul

2017-01-01

Ischemic preconditioning elicited by a non-fatal brief occlusion of blood flow has been applied for an experimental therapeutic strategy against a subsequent fatal ischemic insult. In this study, we investigated the neuroprotective effects of ischemic preconditioning (2-minute transient cerebral ischemia) on calbindin D28k immunoreactivity in the gerbil hippocampal CA1 area following a subsequent fatal transient ischemic insult (5-minute transient cerebral ischemia). A large number of pyramidal neurons in the hippocampal CA1 area died 4 days after 5-minute transient cerebral ischemia. Ischemic preconditioning reduced the death of pyramidal neurons in the hippocampal CA1 area. Calbindin D28k immunoreactivity was greatly attenuated at 2 days after 5-minute transient cerebral ischemia and it was hardly detected at 5 days post-ischemia. Ischemic preconditioning maintained calbindin D28k immunoreactivity after transient cerebral ischemia. These findings suggest that ischemic preconditioning can attenuate transient cerebral ischemia-caused damage to the pyramidal neurons in the hippocampal CA1 area through maintaining calbindin D28k immunoreactivity. PMID:28761424

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking

PubMed Central

Chargé, Pascal; Bazzi, Oussama; Ding, Yuehua

2018-01-01

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods. PMID:29734797

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking.

PubMed

Mohydeen, Ali; Chargé, Pascal; Wang, Yide; Bazzi, Oussama; Ding, Yuehua

2018-05-06

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit⁻receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit⁻receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit⁻receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.

Acetylcholine but not adenosine triggers preconditioning through PI3-kinase and a tyrosine kinase.

PubMed

Qin, Qining; Downey, James M; Cohen, Michael V

2003-02-01

Adenosine and acetylcholine (ACh) trigger preconditioning by different signaling pathways. The involvement of phosphatidylinositol 3-kinase (PI3-kinase), a protein tyrosine kinase, and Src family tyrosine kinase in preconditioning was evaluated in isolated rabbit hearts. Either wortmannin (PI3-kinase blocker), genistein (tyrosine kinase blocker), lavendustin A (tyrosine kinase blocker), or 4-amino-5-(4-chlorophenyl)-7-(t-butyl)pyrazolol[3,4-d]pyrimidine (PP2; Src family tyrosine kinase blocker) was given for 15 min to bracket a 5-min infusion of either adenosine or ACh (trigger phase). The hearts then underwent 30 min of regional ischemia. Infarct size for ACh alone was 9.3 +/- 3.5% of the risk zone versus 34.3 +/- 4.1% in controls. All four inhibitors blocked ACh-induced protection. When wortmannin or PP2 was infused only during the 30-min ischemic period (mediator phase), ACh-induced protection was not affected (7.4 +/- 2.1% and 9.7 +/- 1.7% infarction, respectively). Adenosine-triggered protection was not blocked by any of the inhibitors. Therefore, PI3-kinase and at least one protein tyrosine kinase, probably Src kinase, are involved in the trigger phase of ACh-induced, but not adenosine-induced, preconditioning. Neither PI3-kinase nor Src kinase is a mediator of the protection of ACh.

IMPLEMENTATION AND VALIDATION OF A FULLY IMPLICIT ACCUMULATOR MODEL IN RELAP-7

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

Zhao, Haihua; Zou, Ling; Zhang, Hongbin

2016-01-01

This paper presents the implementation and validation of an accumulator model in RELAP-7 under the framework of preconditioned Jacobian free Newton Krylov (JFNK) method, based on the similar model used in RELAP5. RELAP-7 is a new nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 is a fully implicit system code. The JFNK and preconditioning methods used in RELAP-7 is briefly discussed. The slightly modified accumulator model is summarized for completeness. The implemented model was validated with LOFT L3-1 test and benchmarked with RELAP5 results. RELAP-7 and RELAP5 had almost identical results for themore » accumulator gas pressure and water level, although there were some minor difference in other parameters such as accumulator gas temperature and tank wall temperature. One advantage of the JFNK method is its easiness to maintain and modify models due to fully separation of numerical methods from physical models. It would be straightforward to extend the current RELAP-7 accumulator model to simulate the advanced accumulator design.« less

A geometric multigrid preconditioning strategy for DPG system matrices

DOE PAGES

Roberts, Nathan V.; Chan, Jesse

2017-08-23

Here, the discontinuous Petrov–Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan (2010, 2011) guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. A key question that has not yet been answered in general – though there are some results for Poisson, e.g.– is how best to precondition the DPG system matrix, so that iterative solvers may be used to allow solution of large-scale problems.

Realization of preconditioned Lanczos and conjugate gradient algorithms on optical linear algebra processors.

PubMed

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.

Hypoxic Preconditioning Promotes the Bioactivities of Mesenchymal Stem Cells via the HIF-1α-GRP78-Akt Axis.

PubMed

Lee, Jun Hee; Yoon, Yeo Min; Lee, Sang Hun

2017-06-21

Mesenchymal stem cells (MSC) are ideal materials for stem cell-based therapy. As MSCs reside in hypoxic microenvironments (low oxygen tension of 1% to 7%), several studies have focused on the beneficial effects of hypoxic preconditioning on MSC survival; however, the mechanisms underlying such effects remain unclear. This study aimed to uncover the potential mechanism involving 78-kDa glucose-regulated protein (GRP78) to explain the enhanced MSC bioactivity and survival in hindlimb ischemia. Under hypoxia (2% O₂), the expression of GRP78 was significantly increased via hypoxia-inducible factor (HIF)-1α. Hypoxia-induced GRP78 promoted the proliferation and migration potential of MSCs through the HIF-1α-GRP78-Akt signal axis. In a murine hind-limb ischemia model, hypoxic preconditioning enhanced the survival and proliferation of transplanted MSCs through suppression of the cell death signal pathway and augmentation of angiogenic cytokine secretion. These effects were regulated by GRP78. Our findings indicate that hypoxic preconditioning promotes survival, proliferation, and angiogenic cytokine secretion of MSCs via the HIF-1α-GRP78-Akt signal pathway, suggesting that hypoxia-preconditioned MSCs might provide a therapeutic strategy for MSC-based therapies and that GRP78 represents a potential target for the development of functional MSCs.

Exercise Preconditioning Protects against Spinal Cord Injury in Rats by Upregulating Neuronal and Astroglial Heat Shock Protein 72

PubMed Central

Chang, Cheng-Kuei; Chou, Willy; Lin, Hung-Jung; Huang, Yi-Ching; Tang, Ling-Yu; Lin, Mao-Tsun; Chang, Ching-Ping

2014-01-01

The heat shock protein 72 (HSP 72) is a universal marker of stress protein whose expression can be induced by physical exercise. Here we report that, in a localized model of spinal cord injury (SCI), exercised rats (given pre-SCI exercise) had significantly higher levels of neuronal and astroglial HSP 72, a lower functional deficit, fewer spinal cord contusions, and fewer apoptotic cells than did non-exercised rats. pSUPER plasmid expressing HSP 72 small interfering RNA (SiRNA-HSP 72) was injected into the injured spinal cords. In addition to reducing neuronal and astroglial HSP 72, the (SiRNA-HSP 72) significantly attenuated the beneficial effects of exercise preconditioning in reducing functional deficits as well as spinal cord contusion and apoptosis. Because exercise preconditioning induces increased neuronal and astroglial levels of HSP 72 in the gray matter of normal spinal cord tissue, exercise preconditioning promoted functional recovery in rats after SCI by upregulating neuronal and astroglial HSP 72 in the gray matter of the injured spinal cord. We reveal an important function of neuronal and astroglial HSP 72 in protecting neuronal and astroglial apoptosis in the injured spinal cord. We conclude that HSP 72-mediated exercise preconditioning is a promising strategy for facilitating functional recovery from SCI. PMID:25334068

Enhanced cell volume regulation: a key protective mechanism of ischemic preconditioning in rabbit ventricular myocytes.

PubMed

Diaz, Roberto J; Armstrong, Stephen C; Batthish, Michelle; Backx, Peter H; Ganote, Charles E; Wilson, Gregory J

2003-01-01

Accumulation of osmotically active metabolites, which create an osmotic gradient estimated at ~60 mOsM, and cell swelling are prominent features of ischemic myocardial cell death. This study tests the hypothesis that reduction of ischemic swelling by enhanced cell volume regulation is a key mechanism in the delay of ischemic myocardial cell death by ischemic preconditioning (IPC). Experimental protocols address whether: (i) IPC triggers a cell volume regulation mechanism that reduces cardiomyocyte swelling during subsequent index ischemia; (ii) this reduction in ischemic cell swelling is sufficient in magnitude to account for the IPC protection; (iii) the molecular mechanism that mediates IPC also mediates cell volume regulation. Two experimental models with rabbit ventricular myocytes were studied: freshly isolated pelleted myocytes and 48-h cultured myocytes. Myocytes were preconditioned either by distinct short simulated ischemia (SI)/simulated reperfusion protocols (IPC), or by subjecting myocytes to a pharmacological preconditioning (PPC) protocol (1 microM calyculin A, or 1 microM N(6)-2-(4-aminophenyl)ethyladenosine (APNEA), prior to subjecting them to either different durations of long SI or 30 min hypo-osmotic stress. Cell death (percent blue square myocytes) was monitored by trypan blue staining. Cell swelling was determined by either the bromododecane cell flotation assay (qualitative) or video/confocal microscopy (quantitative). Simulated ischemia induced myocyte swelling in both the models. In pelleted myocytes, IPC or PPC with either calyculin A or APNEA produced a marked reduction of ischemic cell swelling as determined by the cell floatation assay. In cultured myocytes, IPC substantially reduced ischemic cell swelling (P < 0.001). This IPC effect on ischemic cell swelling was related to an IPC and PPC (with APNEA) mediated triggering of cell volume regulatory decrease (RVD). IPC and APNEA also significantly (P < 0.001) reduced hypo-osmotic cell

Preconditioning potential of purmorphamine: a hedgehog activator against ischaemic reperfusion injury in ovariectomised rat heart.

PubMed

Sharma, Shweta; Kaur, Avileen; Sharma, Saurabh

2018-04-01

The present study was been designed to investigate the role and pharmacological potential of hedgehog in oestrogen-deficient rat heart. Oestrogen deficiency was produced in female Wistar rats by the surgical removal of both ovaries and these animals were used four weeks later. Isolated rat heart was subjected to 30 min ischaemia followed by 120 min of reperfusion (I/R). The heart was subjected to pharmacological preconditioning with the hedgehog agonist purmorphamine (1μM) and GDC-0449, a hedgehog antagonist, in the last episode of reperfusion before I/R. Myocardial infarction was assessed in terms of the increase in lactate dehydrogenase (LDH), creatinine kinase-MB (CK-MB), myeloperoxidase (MPO) level and infarct size (triphenyltetrazolium chloride staining). Immunohistochemistry analysis was done for the assessment of tumour necrosis factor (TNF)-α level in cardiac tissue. eNOS expression was estimated by rt-PCR. Pharmacological preconditioning with purmorphamine significantly attenuated I/R-induced myocardial infarction, TNF-α, MPO level and release of LDH and CK-MB compared to the I/R control group. However, GDC-0449 prevented the ameliorative preconditioning effect of estradiol. It may be concluded that the hedgehog agonist purmorphamine prevents the ovariectomised heart from ischaemic reperfusion injury.

AFMPB: An adaptive fast multipole Poisson-Boltzmann solver for calculating electrostatics in biomolecular systems

NASA Astrophysics Data System (ADS)

Lu, Benzhuo; Cheng, Xiaolin; Huang, Jingfang; McCammon, J. Andrew

2010-06-01

A Fortran program package is introduced for rapid evaluation of the electrostatic potentials and forces in biomolecular systems modeled by the linearized Poisson-Boltzmann equation. The numerical solver utilizes a well-conditioned boundary integral equation (BIE) formulation, a node-patch discretization scheme, a Krylov subspace iterative solver package with reverse communication protocols, and an adaptive new version of fast multipole method in which the exponential expansions are used to diagonalize the multipole-to-local translations. The program and its full description, as well as several closely related libraries and utility tools are available at http://lsec.cc.ac.cn/~lubz/afmpb.html and a mirror site at http://mccammon.ucsd.edu/. This paper is a brief summary of the program: the algorithms, the implementation and the usage. Program summaryProgram title: AFMPB: Adaptive fast multipole Poisson-Boltzmann solver Catalogue identifier: AEGB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL 2.0 No. of lines in distributed program, including test data, etc.: 453 649 No. of bytes in distributed program, including test data, etc.: 8 764 754 Distribution format: tar.gz Programming language: Fortran Computer: Any Operating system: Any RAM: Depends on the size of the discretized biomolecular system Classification: 3 External routines: Pre- and post-processing tools are required for generating the boundary elements and for visualization. Users can use MSMS ( http://www.scripps.edu/~sanner/html/msms_home.html) for pre-processing, and VMD ( http://www.ks.uiuc.edu/Research/vmd/) for visualization. Sub-programs included: An iterative Krylov subspace solvers package from SPARSKIT by Yousef Saad ( http://www-users.cs.umn.edu/~saad/software/SPARSKIT/sparskit.html), and the fast multipole methods subroutines from FMMSuite ( http

Involvement of Erythropoietin in Retinal Ischemic Preconditioning

PubMed Central

Dreixler, John C.; Hagevik, Sarah; Hemmert, Jonathan W.; Shaikh, Afzhal R.; Rosenbaum, Daniel M.; Roth, Steven

2009-01-01

Background The purpose of this study was to examine the role of erythropoietin in retinal ischemic preconditioning (IPC). Methods Rats were subjected to retinal ischemia after IPC. Electroretinography assessed functional recovery after ischemia; retinal sections were examined to determine loss of retinal ganglion cells, and Terminal Deoxynucleotidyl Transferase Mediated dUTP Nick End Labeling was used to assess apoptosis. Levels of downstream mediators were measured in retinal homogenates by Western blotting. To assess the involvement of erythropoietin in IPC, we measured levels of erythropoietin and its receptor (EPO-R) in retinal homogenates following IPC, using Western blotting. To examine erythropoietin’s role in IPC, we studied the impact of blocking erythropoietin via intravitreal injection of soluble EPO-R (sEPO-R) before IPC. Results Erythropoietin levels did not change following IPC, but EPO-R increased. Intravitreal injection of sEPO-R significantly attenuated both the functional and histological neuroprotection produced by IPC in comparison to control injection of denatured sEPO-R. Apoptotic damage after ischemia was enhanced in the sEPO-R treated retinas as indicated by fluorescent Terminal Deoxynucleotidyl Transferase Mediated dUTP Nick End Labeling. Phosphorylated extracellular-signal-regulated kinase (ERK) and heat shock protein 27 (Hsp27), but not protein kinase B (Akt), upregulated in denatured sEPO-R treated retinae, were attenuated in eyes injected with sEPO-R. Conclusions These results indicate that EPO-R upregulation is a critical component of the functional, histological, and anti-apoptotic protective effect of ischemic preconditioning on ischemia in the retina and that several downstream effectors may be involved in the neuroprotective actions of erythropoietin. PMID:19322943

Coupling Schemes for Multiphysics Reactor Simulation

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

Vijay Mahadeven; Jean Ragusa

2007-11-01

This report documents the progress of the student Vijay S. Mahadevan from the Nuclear Engineering Department of Texas A&M University over the summer of 2007 during his visit to the INL. The purpose of his visit was to investigate the physics-based preconditioned Jacobian-free Newton-Krylov method applied to physics relevant to nuclear reactor simulation. To this end he studied two test problems that represented reaction-diffusion and advection-reaction. These two test problems will provide the basis for future work in which neutron diffusion, nonlinear heat conduction, and a twophase flow model will be tightly coupled to provide an accurate model of amore » BWR core.« less

Acidic preconditioning of endothelial colony-forming cells (ECFC) promote vasculogenesis under proinflammatory and high glucose conditions in vitro and in vivo.

PubMed

Mena, Hebe Agustina; Zubiry, Paula Romina; Dizier, Blandine; Schattner, Mirta; Boisson-Vidal, Catherine; Negrotto, Soledad

2018-05-02

We have previously demonstrated that acidic preconditioning of human endothelial colony-forming cells (ECFC) increased proliferation, migration, and tubulogenesis in vitro, and increased their regenerative potential in a murine model of hind limb ischemia without baseline disease. We now analyze whether this strategy is also effective under adverse conditions for vasculogenesis, such as the presence of ischemia-related toxic molecules or diabetes, one of the main target diseases for cell therapy due to their well-known healing impairments. Cord blood-derived CD34 + cells were seeded in endothelial growth culture medium (EGM2) and ECFC colonies were obtained after 14-21 days. ECFC were exposed at pH 6.6 (preconditioned) or pH 7.4 (nonpreconditioned) for 6 h, and then pH was restored at 7.4. A model of type 2 diabetes induced by a high-fat and high-sucrose diet was developed in nude mice and hind limb ischemia was induced in these animals by femoral artery ligation. A P value < 0.05 was considered statistically significant (by one-way analysis of variance). We found that acidic preconditioning increased ECFC adhesion and the release of pro-angiogenic molecules, and protected ECFC from the cytotoxic effects of monosodium urate crystals, histones, and tumor necrosis factor (TNF)α, which induced necrosis, pyroptosis, and apoptosis, respectively. Noncytotoxic concentrations of high glucose, TNFα, or their combination reduced ECFC proliferation, stromal cell-derived factor (SDF)1-driven migration, and tubule formation on a basement membrane matrix, whereas almost no inhibition was observed in preconditioned ECFC. In type 2 diabetic mice, intravenous administration of preconditioned ECFC significantly induced blood flow recovery at the ischemic limb as measured by Doppler, compared with the phosphate-buffered saline (PBS) and nonpreconditioned ECFC groups. Moreover, the histologic analysis of gastrocnemius muscles showed an increased vascular density and reduced

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Li, Xiaoye; Heber, Gerd; Biswas, Rupak

2000-01-01

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Effect of preconditioning on silver leaching and bromide removal properties of silver-impregnated activated carbon (SIAC).

PubMed

Rajaeian, Babak; Allard, Sébastien; Joll, Cynthia; Heitz, Anna

2018-07-01

Silver impregnated activated carbon (SIAC) has been found to be effective in mitigating the formation of brominated-disinfection by products during drinking water treatment. However, there are still uncertainties regarding its silver leaching properties, and strategies for the prevention of silver leaching have remained elusive. This study focused on the evaluation of one type of commercially available SIAC for its ability to remove bromide while minimising silver leaching from the material. Both synthetic and real water matrices were tested. Depending on solution pH, it was found that changing the surface charge properties of SIAC, as measured by the point of zero charge pH, can result in additional bromide removal while minimising the extent of silver leaching. To better understand the mechanism of silver leaching from the SIAC, eight preconditioning environments, i.e. variable pH and ionic strength were tested for a fixed amount of SIAC and two preconditioning environments were selected for a more detailed investigation. Experiments carried out in synthetic water showed that preconditioning at pH 10.4 did not deteriorate the capacity of SIAC to remove bromide, but significantly decreased the release of silver in the form of ionic silver (Ag + ), silver bromide (AgBr) and silver chloride (AgCl) from 40% for the pristine to 3% for the treated SIAC. This was confirmed using a groundwater sample. These results suggest that preconditioned SIAC has the potential to be an effective method for bromide removal with minimised silver leaching in a long-term field application for drinking water production. Copyright © 2018 Elsevier Ltd. All rights reserved.

Human Bone Marrow-Derived Mesenchymal Stem Cells Display Enhanced Clonogenicity but Impaired Differentiation With Hypoxic Preconditioning

PubMed Central

Boyette, Lisa B.; Creasey, Olivia A.; Guzik, Lynda; Lozito, Thomas

2014-01-01

Stem cells are promising candidate cells for regenerative applications because they possess high proliferative capacity and the potential to differentiate into other cell types. Mesenchymal stem cells (MSCs) are easily sourced but do not retain their proliferative and multilineage differentiative capabilities after prolonged ex vivo propagation. We investigated the use of hypoxia as a preconditioning agent and in differentiating cultures to enhance MSC function. Culture in 5% ambient O2 consistently enhanced clonogenic potential of primary MSCs from all donors tested. We determined that enhanced clonogenicity was attributable to increased proliferation, increased vascular endothelial growth factor secretion, and increased matrix turnover. Hypoxia did not impact the incidence of cell death. Application of hypoxia to osteogenic cultures resulted in enhanced total mineral deposition, although this effect was detected only in MSCs preconditioned in normoxic conditions. Osteogenesis-associated genes were upregulated in hypoxia, and alkaline phosphatase activity was enhanced. Adipogenic differentiation was inhibited by exposure to hypoxia during differentiation. Chondrogenesis in three-dimensional pellet cultures was inhibited by preconditioning with hypoxia. However, in cultures expanded under normoxia, hypoxia applied during subsequent pellet culture enhanced chondrogenesis. Whereas hypoxic preconditioning appears to be an excellent way to expand a highly clonogenic progenitor pool, our findings suggest that it may blunt the differentiation potential of MSCs, compromising their utility for regenerative tissue engineering. Exposure to hypoxia during differentiation (post-normoxic expansion), however, appears to result in a greater quantity of functional osteoblasts and chondrocytes and ultimately a larger quantity of high-quality differentiated tissue. PMID:24436440

Inverse transport calculations in optical imaging with subspace optimization algorithms

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

Ding, Tian, E-mail: tding@math.utexas.edu; Ren, Kui, E-mail: ren@math.utexas.edu

2014-09-15

Inverse boundary value problems for the radiative transport equation play an important role in optics-based medical imaging techniques such as diffuse optical tomography (DOT) and fluorescence optical tomography (FOT). Despite the rapid progress in the mathematical theory and numerical computation of these inverse problems in recent years, developing robust and efficient reconstruction algorithms remains a challenging task and an active research topic. We propose here a robust reconstruction method that is based on subspace minimization techniques. The method splits the unknown transport solution (or a functional of it) into low-frequency and high-frequency components, and uses singular value decomposition to analyticallymore » recover part of low-frequency information. Minimization is then applied to recover part of the high-frequency components of the unknowns. We present some numerical simulations with synthetic data to demonstrate the performance of the proposed algorithm.« less

Repeated ischaemic preconditioning: a novel therapeutic intervention and potential underlying mechanisms.

PubMed

Thijssen, Dick H J; Maxwell, Joseph; Green, Daniel J; Cable, N Timothy; Jones, Helen

2016-06-01

What is the topic of this review? This review discusses the effects of repeated exposure of tissue to ischaemic preconditioning on cardiovascular function, the attendant adaptations and their potential clinical relevance. What advances does it highlight? We discuss the effects of episodic exposure to ischaemic preconditioning to prevent and/or attenuate ischaemic injury and summarize evidence pertaining to improvements in cardiovascular function and structure. Discussion is provided regarding the potential mechanisms that contribute to both local and systemic adaptation. Findings suggest that clinical benefits result from both the prevention of ischaemic events and the attenuation of their consequences. Ischaemic preconditioning (IPC) refers to the phenomenon whereby short periods of cyclical tissue ischaemia confer subsequent protection against ischaemia-induced injury. As a consequence, IPC can ameliorate the myocardial damage following infarction and can reduce infarct size. The ability of IPC to confer remote protection makes IPC a potentially feasible cardioprotective strategy. In this review, we discuss the concept that repeated exposure of tissue to IPC may increase the 'dose' of protection and subsequently lead to enhanced protection against ischaemia-induced myocardial injury. This may be relevant for clinical populations, who demonstrate attenuated efficacy of IPC to prevent or attenuate ischaemic injury (and therefore myocardial infarct size). Furthermore, episodic IPC facilitates repeated exposure to local (e.g. shear stress) and systemic stimuli (e.g. hormones, cytokines, blood-borne substances), which may induce improvement in vascular function and health. Such adaptation may contribute to prevention of cardio- and cerebrovascular events. The clinical benefits of repeated IPC may, therefore, result from both the prevention of ischaemic events and the attenuation of their consequences. We provide an overview of the literature pertaining to the impact

Preconditioning of the background error covariance matrix in data assimilation for the Caspian Sea

NASA Astrophysics Data System (ADS)

Arcucci, Rossella; D'Amore, Luisa; Toumi, Ralf

2017-06-01

Data Assimilation (DA) is an uncertainty quantification technique used for improving numerical forecasted results by incorporating observed data into prediction models. As a crucial point into DA models is the ill conditioning of the covariance matrices involved, it is mandatory to introduce, in a DA software, preconditioning methods. Here we present first studies concerning the introduction of two different preconditioning methods in a DA software we are developing (we named S3DVAR) which implements a Scalable Three Dimensional Variational Data Assimilation model for assimilating sea surface temperature (SST) values collected into the Caspian Sea by using the Regional Ocean Modeling System (ROMS) with observations provided by the Group of High resolution sea surface temperature (GHRSST). We also present the algorithmic strategies we employ.

Combinatorial therapy of exercise-preconditioning and nanocurcumin formulation supplementation improves cardiac adaptation under hypobaric hypoxia.

PubMed

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

Surface pre-conditioning with bioactive glass air-abrasion can enhance enamel white spot lesion remineralization.

PubMed

Milly, Hussam; Festy, Frederic; Andiappan, Manoharan; Watson, Timothy F; Thompson, Ian; Banerjee, Avijit

2015-05-01

To evaluate the effect of pre-conditioning enamel white spot lesion (WSL) surfaces using bioactive glass (BAG) air-abrasion prior to remineralization therapy. Ninety human enamel samples with artificial WSLs were assigned to three WSL surface pre-conditioning groups (n=30): (a) air-abrasion with BAG-polyacrylic acid (PAA-BAG) powder, (b) acid-etching using 37% phosphoric acid gel (positive control) and (c) unconditioned (negative control). Each group was further divided into three subgroups according to the following remineralization therapy (n=10): (I) BAG paste (36 wt.% BAG), (II) BAG slurry (100 wt.% BAG) and (III) de-ionized water (negative control). The average surface roughness and the lesion step height compared to intra-specimen sound enamel reference points were analyzed using non-contact profilometry. Optical changes within the lesion subsurface compared to baseline scans were assessed using optical coherence tomography (OCT). Knoop microhardness evaluated the WSLs' mechanical properties. Raman micro-spectroscopy measured the v-(CO3)(2-)/v1-(PO4)(3-) ratio. Structural changes in the lesion were observed using confocal laser scanning microscopy (CLSM) and scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX). All comparisons were considered statistically significant if p<0.05. PAA-BAG air-abrasion removed 5.1 ± 0.6 μm from the lesion surface, increasing the WSL surface roughness. Pre-conditioning WSL surfaces with PAA-BAG air-abrasion reduced subsurface light scattering, increased the Knoop microhardness and the mineral content of the remineralized lesions (p<0.05). SEM-EDX revealed mineral depositions covering the lesion surface. BAG slurry resulted in a superior remineralization outcome, when compared to BAG paste. Pre-conditioning WSL surfaces with PAA-BAG air-abrasion modified the lesion surface physically and enhanced remineralization using BAG 45S5 therapy. Copyright © 2015 Academy of Dental Materials. Published by Elsevier

Amelioration of rCBF and PbtO2 following TBI at high altitude by hyperbaric oxygen pre-conditioning.

PubMed

Hu, Shengli; Li, Fei; Luo, Haishui; Xia, Yongzhi; Zhang, Jiuquan; Hu, Rong; Cui, Gaoyu; Meng, Hui; Feng, Hua

2010-03-01

Hypobaric hypoxia at high altitude can lead to brain damage and pre-conditioning with hyperbaric oxygen (HBO) can reduce ischemic/hypoxic brain injury. This study investigates the effects of high altitude on traumatic brain injury (TBI) and examines the neuroprotection provided by HBO preconditioning against TBI. Rats were randomly divided into four groups: HBO pre-conditioning group (HBOP, n=10), high altitude group (HA, n=10), plain control group (PC, n=10) and plain sham operation group (sham, n=10). All groups were subjected to head trauma by weight drop device except for the sham group. Rats from each group were examined for neurological function, regional cerebral blood flow (rCBF) and brain tissue oxygen pressure (PbtO(2)) and were killed for analysis by transmission electron microscope. The score of neurological deficits in the HA group was highest, followed by the HBOP group and the PC group, respectively. Both rCBF and PbtO(2) were the lowest in the HA group. Brain morphology and structure seen via the transmission electron microscope was diminished in the HA group, while fewer pathological injuries occurred in the HBOP and PC groups. High altitude aggravates TBI significantly and HBO pre-conditioning can attenuate TBI in rats at high altitude by improvement of rCBF and PbtO(2). Pre-treatment with HBO might be beneficial for people traveling to high altitude locations.

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.