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.

An extended basis inexact shift-invert Lanczos for the efficient solution of large-scale generalized eigenproblems

NASA Astrophysics Data System (ADS)

Rewieński, M.; Lamecki, A.; Mrozowski, M.

2013-09-01

This paper proposes a technique, based on the Inexact Shift-Invert Lanczos (ISIL) method with Inexact Jacobi Orthogonal Component Correction (IJOCC) refinement, and a preconditioned conjugate-gradient (PCG) linear solver with multilevel preconditioner, for finding several eigenvalues for generalized symmetric eigenproblems. Several eigenvalues are found by constructing (with the ISIL process) an extended projection basis. Presented results of numerical experiments confirm the technique can be effectively applied to challenging, large-scale problems characterized by very dense spectra, such as resonant cavities with spatial dimensions which are large with respect to wavelengths of the resonating electromagnetic fields. It is also shown that the proposed scheme based on inexact linear solves delivers superior performance, as compared to methods which rely on exact linear solves, indicating tremendous potential of the 'inexact solve' concept. Finally, the scheme which generates an extended projection basis is found to provide a cost-efficient alternative to classical deflation schemes when several eigenvalues are computed.

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.

Incomplete augmented Lagrangian preconditioner for steady incompressible Navier-Stokes equations.

PubMed

Tan, Ning-Bo; Huang, Ting-Zhu; Hu, Ze-Jun

2013-01-01

An incomplete augmented Lagrangian preconditioner, for the steady incompressible Navier-Stokes equations discretized by stable finite elements, is proposed. The eigenvalues of the preconditioned matrix are analyzed. Numerical experiments show that the incomplete augmented Lagrangian-based preconditioner proposed is very robust and performs quite well by the Picard linearization or the Newton linearization over a wide range of values of the viscosity on both uniform and stretched grids.

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.

Incomplete Augmented Lagrangian Preconditioner for Steady Incompressible Navier-Stokes Equations

PubMed Central

Tan, Ning-Bo; Huang, Ting-Zhu; Hu, Ze-Jun

2013-01-01

An incomplete augmented Lagrangian preconditioner, for the steady incompressible Navier-Stokes equations discretized by stable finite elements, is proposed. The eigenvalues of the preconditioned matrix are analyzed. Numerical experiments show that the incomplete augmented Lagrangian-based preconditioner proposed is very robust and performs quite well by the Picard linearization or the Newton linearization over a wide range of values of the viscosity on both uniform and stretched grids. PMID:24235888

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 differentiable reformulation for E-optimal design of experiments in nonlinear dynamic biosystems.

PubMed

Telen, Dries; Van Riet, Nick; Logist, Flip; Van Impe, Jan

2015-06-01

Informative experiments are highly valuable for estimating parameters in nonlinear dynamic bioprocesses. Techniques for optimal experiment design ensure the systematic design of such informative experiments. The E-criterion which can be used as objective function in optimal experiment design requires the maximization of the smallest eigenvalue of the Fisher information matrix. However, one problem with the minimal eigenvalue function is that it can be nondifferentiable. In addition, no closed form expression exists for the computation of eigenvalues of a matrix larger than a 4 by 4 one. As eigenvalues are normally computed with iterative methods, state-of-the-art optimal control solvers are not able to exploit automatic differentiation to compute the derivatives with respect to the decision variables. In the current paper a reformulation strategy from the field of convex optimization is suggested to circumvent these difficulties. This reformulation requires the inclusion of a matrix inequality constraint involving positive semidefiniteness. In this paper, this positive semidefiniteness constraint is imposed via Sylverster's criterion. As a result the maximization of the minimum eigenvalue function can be formulated in standard optimal control solvers through the addition of nonlinear constraints. The presented methodology is successfully illustrated with a case study from the field of predictive microbiology. Copyright © 2015. Published by Elsevier Inc.

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.

An assessment of coupling algorithms for nuclear reactor core physics simulations

DOE PAGES

Hamilton, Steven; Berrill, Mark; Clarno, Kevin; ...

2016-04-01

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven; Berrill, Mark; Clarno, Kevin

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven, E-mail: hamiltonsp@ornl.gov; Berrill, Mark, E-mail: berrillma@ornl.gov; Clarno, Kevin, E-mail: clarnokt@ornl.gov

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNKmore » and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices

NASA Astrophysics Data System (ADS)

Bollhöfer, Matthias; Notay, Yvan

2007-12-01

A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closest to some specified target, which may be in the interior of the spectrum. The underlying algorithm combines the Jacobi-Davidson method with efficient multilevel incomplete LU (ILU) preconditioning. Key features are modest memory requirements and robust convergence to accurate solutions. Parameters needed for incomplete LU preconditioning are automatically computed and may be updated at run time depending on the convergence pattern. The software is easy to use by non-experts and its top level routines are written in FORTRAN 77. Its potentialities are demonstrated on a few applications taken from computational physics. Program summaryProgram title: JADAMILU Catalogue identifier: ADZT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 101 359 No. of bytes in distributed program, including test data, etc.: 7 493 144 Distribution format: tar.gz Programming language: Fortran 77 Computer: Intel or AMD with g77 and pgf; Intel EM64T or Itanium with ifort; AMD Opteron with g77, pgf and ifort; Power (IBM) with xlf90. Operating system: Linux, AIX RAM: problem dependent Word size: real:8; integer: 4 or 8, according to user's choice Classification: 4.8 Nature of problem: Any physical problem requiring the computation of a few eigenvalues of a symmetric matrix. Solution method: Jacobi-Davidson combined with multilevel ILU preconditioning. Additional comments: We supply binaries rather than source code because JADAMILU uses the following external packages: MC64. This software is copyrighted software and not freely available. COPYRIGHT (c) 1999 Council for the Central Laboratory of the Research Councils. AMD. Copyright (c) 2004-2006 by Timothy A. Davis, Patrick R. Amestoy, and Iain S. Duff. Source code is distributed by the authors under the GNU LGPL licence. BLAS. The reference BLAS is a freely-available software package. It is available from netlib via anonymous ftp and the World Wide Web. LAPACK. The complete LAPACK package or individual routines from LAPACK are freely available on netlib and can be obtained via the World Wide Web or anonymous ftp. For maximal benefit to the community, we added the sources we are proprietary of to the tar.gz file submitted for inclusion in the CPC library. However, as explained in the README file, users willing to compile the code instead of using binaries should first obtain the sources for the external packages mentioned above (email and/or web addresses are provided). Running time: Problem dependent; the test examples provided with the code only take a few seconds to run; timing results for large scale problems are given in Section 5.

Approximate analysis for repeated eigenvalue problems with applications to controls-structure integrated design

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Hou, Gene J. W.

1994-01-01

A method for eigenvalue and eigenvector approximate analysis for the case of repeated eigenvalues with distinct first derivatives is presented. The approximate analysis method developed involves a reparameterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations to changes in the eigenvalues and the eigenvectors associated with the repeated eigenvalue problem. This work also presents a numerical technique that facilitates the definition of an eigenvector derivative for the case of repeated eigenvalues with repeated eigenvalue derivatives (of all orders). Examples are given which demonstrate the application of such equations for sensitivity and approximate analysis. Emphasis is placed on the application of sensitivity analysis to large-scale structural and controls-structures optimization problems.

Covariance expressions for eigenvalue and eigenvector problems

NASA Astrophysics Data System (ADS)

Liounis, Andrew J.

There are a number of important scientific and engineering problems whose solutions take the form of an eigenvalue--eigenvector problem. Some notable examples include solutions to linear systems of ordinary differential equations, controllability of linear systems, finite element analysis, chemical kinetics, fitting ellipses to noisy data, and optimal estimation of attitude from unit vectors. In many of these problems, having knowledge of the eigenvalue and eigenvector Jacobians is either necessary or is nearly as important as having the solution itself. For instance, Jacobians are necessary to find the uncertainty in a computed eigenvalue or eigenvector estimate. This uncertainty, which is usually represented as a covariance matrix, has been well studied for problems similar to the eigenvalue and eigenvector problem, such as singular value decomposition. There has been substantially less research on the covariance of an optimal estimate originating from an eigenvalue-eigenvector problem. In this thesis we develop two general expressions for the Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The expressions developed make use of only the parent matrix and the eigenvalue and eigenvector pair under consideration. In addition, they are applicable to any general matrix (including complex valued matrices, eigenvalues, and eigenvectors) as long as the eigenvalues are simple. Alongside this, we develop expressions that determine the uncertainty in a vector estimate obtained from an eigenvalue-eigenvector problem given the uncertainty of the terms of the matrix. The Jacobian expressions developed are numerically validated with forward finite, differencing and the covariance expressions are validated using Monte Carlo analysis. Finally, the results from this work are used to determine covariance expressions for a variety of estimation problem examples and are also applied to the design of a dynamical system.

Construction, classification and parametrization of complex Hadamard matrices

NASA Astrophysics Data System (ADS)

Szöllősi, Ferenc

To improve the design of nuclear systems, high-fidelity neutron fluxes are required. Leadership-class machines provide platforms on which very large problems can be solved. Computing such fluxes efficiently requires numerical methods with good convergence properties and algorithms that can scale to hundreds of thousands of cores. Many 3-D deterministic transport codes are decomposable in space and angle only, limiting them to tens of thousands of cores. Most codes rely on methods such as Gauss Seidel for fixed source problems and power iteration for eigenvalue problems, which can be slow to converge for challenging problems like those with highly scattering materials or high dominance ratios. Three methods have been added to the 3-D SN transport code Denovo that are designed to improve convergence and enable the full use of cutting-edge computers. The first is a multigroup Krylov solver that converges more quickly than Gauss Seidel and parallelizes the code in energy such that Denovo can use hundreds of thousand of cores effectively. The second is Rayleigh quotient iteration (RQI), an old method applied in a new context. This eigenvalue solver finds the dominant eigenvalue in a mathematically optimal way and should converge in fewer iterations than power iteration. RQI creates energy-block-dense equations that the new Krylov solver treats efficiently. However, RQI can have convergence problems because it creates poorly conditioned systems. This can be overcome with preconditioning. The third method is a multigrid-in-energy preconditioner. The preconditioner takes advantage of the new energy decomposition because the grids are in energy rather than space or angle. The preconditioner greatly reduces iteration count for many problem types and scales well in energy. It also allows RQI to be successful for problems it could not solve otherwise. The methods added to Denovo accomplish the goals of this work. They converge in fewer iterations than traditional methods and enable the use of hundreds of thousands of cores. Each method can be used individually, with the multigroup Krylov solver and multigrid-in-energy preconditioner being particularly successful on their own. The largest benefit, though, comes from using these methods in concert.

Efficient iterative method for solving the Dirac-Kohn-Sham density functional theory

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

Lin, Lin; Shao, Sihong; E, Weinan

2012-11-06

We present for the first time an efficient iterative method to directly solve the four-component Dirac-Kohn-Sham (DKS) density functional theory. Due to the existence of the negative energy continuum in the DKS operator, the existing iterative techniques for solving the Kohn-Sham systems cannot be efficiently applied to solve the DKS systems. The key component of our method is a novel filtering step (F) which acts as a preconditioner in the framework of the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The resulting method, dubbed the LOBPCG-F method, is able to compute the desired eigenvalues and eigenvectors in the positive energy band without computing any state in the negative energy band. The LOBPCG-F method introduces mild extra cost compared to the standard LOBPCG method and can be easily implemented. We demonstrate our method in the pseudopotential framework with a planewave basis set which naturally satisfies the kinetic balance prescription. Numerical results for Ptmore » $$_{2}$$, Au$$_{2}$$, TlF, and Bi$$_{2}$$Se$$_{3}$$ indicate that the LOBPCG-F method is a robust and efficient method for investigating the relativistic effect in systems containing heavy elements.« less

Metformin Preconditioning of Human induced Pluripotent Stem Cell-derived Neural Stem Cells Promotes Their Engraftment and Improves Post-Stroke Regeneration and Recovery.

PubMed

Ould-Brahim, Fares; Sarma, Sailendra Nath; Syal, Charvi; Lu, Kevin Jiaqi; Seegobin, Matthew; Carter, Anthony; Jeffers, Matthew S; Doré, Carole; Stanford, William; Corbett, Dale; Wang, Jing

2018-06-12

While transplantation of hiPSC-derived neural stem cells (hiPSC-NSCs) shows therapeutic potential in animal stroke models, major concerns for translating hiPSC therapy to the clinic are efficacy and safety. Therefore, there is a demand to develop an optimal strategy to enhance the engraftment and regenerative capacity of transplanted hiPSC-NSCs in order to produce fully differentiated neural cells to replace lost brain tissues. Metformin, an FDA approved drug, is an optimal neuroregenerative agent that not only promotes NSC proliferation but also drives NSC towards differentiation. In this regard, we hypothesize that preconditioning of hiPSC-NSCs with metformin before transplantation into the stroke-damaged brain will improve engraftment and regenerative capabilities of hiPSC-NSCs, ultimately enhancing functional recovery. Here we show that pretreatment of hiPSC-NSCs with metformin enhances the proliferation and differentiation of hiPSC-NSCs in culture. Furthermore, metformin-preconditioned hiPSC-NSCs show increased engraftment 1-week post-transplant in a rat endothelin-1 focal ischemic stroke model. In addition, metformin preconditioned cell grafts exhibit increased survival compared to naïve cell grafts at 7-week post-transplant. Analysis of the grafts demonstrates that metformin preconditioning enhances the differentiation of hiPSC-NSCs. As an outcome, rats receiving metformin preconditioned cells display accelerated gross motor recovery and reduced infarct volume. These studies represent a vital step forward in the optimization of hiPSC-NSC based transplantation to promote post-stroke recovery.

Principal Eigenvalue Minimization for an Elliptic Problem with Indefinite Weight and Robin Boundary Conditions

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

Hintermueller, M., E-mail: hint@math.hu-berlin.de; Kao, C.-Y., E-mail: Ckao@claremontmckenna.edu; Laurain, A., E-mail: laurain@math.hu-berlin.de

2012-02-15

This paper focuses on the study of a linear eigenvalue problem with indefinite weight and Robin type boundary conditions. We investigate the minimization of the positive principal eigenvalue under the constraint that the absolute value of the weight is bounded and the total weight is a fixed negative constant. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for a species to survive. For rectangular domains with Neumann boundary condition, it is known that there exists a threshold value such that if the total weight is below this thresholdmore » value then the optimal favorable region is like a section of a disk at one of the four corners; otherwise, the optimal favorable region is a strip attached to the shorter side of the rectangle. Here, we investigate the same problem with mixed Robin-Neumann type boundary conditions and study how this boundary condition affects the optimal spatial arrangement.« less

Eigenmode computation of cavities with perturbed geometry using matrix perturbation methods applied on generalized eigenvalue problems

NASA Astrophysics Data System (ADS)

Gorgizadeh, Shahnam; Flisgen, Thomas; van Rienen, Ursula

2018-07-01

Generalized eigenvalue problems are standard problems in computational sciences. They may arise in electromagnetic fields from the discretization of the Helmholtz equation by for example the finite element method (FEM). Geometrical perturbations of the structure under concern lead to a new generalized eigenvalue problems with different system matrices. Geometrical perturbations may arise by manufacturing tolerances, harsh operating conditions or during shape optimization. Directly solving the eigenvalue problem for each perturbation is computationally costly. The perturbed eigenpairs can be approximated using eigenpair derivatives. Two common approaches for the calculation of eigenpair derivatives, namely modal superposition method and direct algebraic methods, are discussed in this paper. Based on the direct algebraic methods an iterative algorithm is developed for efficiently calculating the eigenvalues and eigenvectors of the perturbed geometry from the eigenvalues and eigenvectors of the unperturbed geometry.

Investigation, development and application of optimal output feedback theory. Vol. 4: Measures of eigenvalue/eigenvector sensitivity to system parameters and unmodeled dynamics

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

Some measures of eigenvalue and eigenvector sensitivity applicable to both continuous and discrete linear systems are developed and investigated. An infinite series representation is developed for the eigenvalues and eigenvectors of a system. The coefficients of the series are coupled, but can be obtained recursively using a nonlinear coupled vector difference equation. A new sensitivity measure is developed by considering the effects of unmodeled dynamics. It is shown that the sensitivity is high when any unmodeled eigenvalue is near a modeled eigenvalue. Using a simple example where the sensor dynamics have been neglected, it is shown that high feedback gains produce high eigenvalue/eigenvector sensitivity. The smallest singular value of the return difference is shown not to reflect eigenvalue sensitivity since it increases with the feedback gains. Using an upper bound obtained from the infinite series, a procedure to evaluate whether the sensitivity to parameter variations is within given acceptable bounds is developed and demonstrated by an example.

A method to stabilize linear systems using eigenvalue gradient information

NASA Technical Reports Server (NTRS)

Wieseman, C. D.

1985-01-01

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

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.

Ontario's daily physical activity policy for elementary schools: is everything in place for success?

PubMed

Robertson-Wilson, Jennifer E; Lévesque, Lucie

2009-01-01

The development, implementation, and evaluation of policies may play an important role in promoting health behaviours such as physical activity. The Ontario Ministry of Education (OME) recently mandated Memorandum No. 138 requiring daily physical activity (DPA) for Ontario elementary students in grades one through eight. The purpose of this paper is to examine implementation strategies. Hogwood and Gunn's 10 preconditions for "perfect implementation" are used to examine publicly available Ministry DPA policy documents to assess whether these implementation strategies have been considered in the policy documents. Several preconditions (e.g., allocation of resources, task specification) appear to have been considered, however a number of preconditions (e.g., the sustainability of resources, extent to which the policy is valued, and evaluation plans) thought to be important require additional attention to ensure optimal DPA implementation. Additional reflection upon Hogwood and Gunn's implementation preconditions would, in our opinion, assist in facilitating optimal DPA implementation as per Memorandum No. 138.

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

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach

NASA Astrophysics Data System (ADS)

Tarai, Madhumita; Kumar, Keshav; Divya, O.; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-01

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

Fast optimal wavefront reconstruction for multi-conjugate adaptive optics using the Fourier domain preconditioned conjugate gradient algorithm.

PubMed

Vogel, Curtis R; Yang, Qiang

2006-08-21

We present two different implementations of the Fourier domain preconditioned conjugate gradient algorithm (FD-PCG) to efficiently solve the large structured linear systems that arise in optimal volume turbulence estimation, or tomography, for multi-conjugate adaptive optics (MCAO). We describe how to deal with several critical technical issues, including the cone coordinate transformation problem and sensor subaperture grid spacing. We also extend the FD-PCG approach to handle the deformable mirror fitting problem for MCAO.

Emergent spectral properties of river network topology: an optimal channel network approach.

PubMed

Abed-Elmdoust, Armaghan; Singh, Arvind; Yang, Zong-Liang

2017-09-13

Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues. We show that such spectral features are closely related to the branching topology of the associated river networks. In this regard, we find an empirical relation for the spectral gap and nullity in terms of the energy dissipation exponent of the drainage networks. In addition, the eigenvalue distribution is found to follow a finite-width probability density function with certain skewness which is related to the drainage pattern. Our results are based on optimal channel network simulations and validated through examples obtained from physical experiments on landscape evolution. These results suggest the potential of the spectral graph techniques in characterizing and modeling river networks.

Linear quadratic regulators with eigenvalue placement in a specified region

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Dib, Hani M.; Ganesan, Sekar

1988-01-01

A linear optimal quadratic regulator is developed for optimally placing the closed-loop poles of multivariable continuous-time systems within the common region of an open sector, bounded by lines inclined at + or - pi/2k (k = 2 or 3) from the negative real axis with a sector angle of pi/2 or less, and the left-hand side of a line parallel to the imaginary axis in the complex s-plane. The design method is mainly based on the solution of a linear matrix Liapunov equation, and the resultant closed-loop system with its eigenvalues in the desired region is optimal with respect to a quadratic performance index.

Modeling of frequency-domain scalar wave equation with the average-derivative optimal scheme based on a multigrid-preconditioned iterative solver

NASA Astrophysics Data System (ADS)

Cao, Jian; Chen, Jing-Bo; Dai, Meng-Xue

2018-01-01

An efficient finite-difference frequency-domain modeling of seismic wave propagation relies on the discrete schemes and appropriate solving methods. The average-derivative optimal scheme for the scalar wave modeling is advantageous in terms of the storage saving for the system of linear equations and the flexibility for arbitrary directional sampling intervals. However, using a LU-decomposition-based direct solver to solve its resulting system of linear equations is very costly for both memory and computational requirements. To address this issue, we consider establishing a multigrid-preconditioned BI-CGSTAB iterative solver fit for the average-derivative optimal scheme. The choice of preconditioning matrix and its corresponding multigrid components is made with the help of Fourier spectral analysis and local mode analysis, respectively, which is important for the convergence. Furthermore, we find that for the computation with unequal directional sampling interval, the anisotropic smoothing in the multigrid precondition may affect the convergence rate of this iterative solver. Successful numerical applications of this iterative solver for the homogenous and heterogeneous models in 2D and 3D are presented where the significant reduction of computer memory and the improvement of computational efficiency are demonstrated by comparison with the direct solver. In the numerical experiments, we also show that the unequal directional sampling interval will weaken the advantage of this multigrid-preconditioned iterative solver in the computing speed or, even worse, could reduce its accuracy in some cases, which implies the need for a reasonable control of directional sampling interval in the discretization.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach.

PubMed

Tarai, Madhumita; Kumar, Keshav; Divya, O; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-05

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

A New Coarsening Operator for the Optimal Preconditioning of the Dual and Primal Domain Decomposition Methods: Application to Problems with Severe Coefficient Jumps

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Rixen, Daniel

1996-01-01

We present an optimal preconditioning algorithm that is equally applicable to the dual (FETI) and primal (Balancing) Schur complement domain decomposition methods, and which successfully addresses the problems of subdomain heterogeneities including the effects of large jumps of coefficients. The proposed preconditioner is derived from energy principles and embeds a new coarsening operator that propagates the error globally and accelerates convergence. The resulting iterative solver is illustrated with the solution of highly heterogeneous elasticity problems.

The nonconforming virtual element method for eigenvalue problems

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

Gardini, Francesca; Manzini, Gianmarco; Vacca, Giuseppe

We analyse the nonconforming Virtual Element Method (VEM) for the approximation of elliptic eigenvalue problems. The nonconforming VEM allow to treat in the same formulation the two- and three-dimensional case.We present two possible formulations of the discrete problem, derived respectively by the nonstabilized and stabilized approximation of the L 2-inner product, and we study the convergence properties of the corresponding discrete eigenvalue problems. The proposed schemes provide a correct approximation of the spectrum and we prove optimal-order error estimates for the eigenfunctions and the usual double order of convergence of the eigenvalues. Finally we show a large set of numericalmore » tests supporting the theoretical results, including a comparison with the conforming Virtual Element choice.« less

Aerodynamic shape optimization using preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Burgreen, Greg W.; Baysal, Oktay

1993-01-01

In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.

Best dispersal strategies in spatially heterogeneous environments: optimization of the principal eigenvalue for indefinite fractional Neumann problems.

PubMed

Pellacci, Benedetta; Verzini, Gianmaria

2018-05-01

We study the positive principal eigenvalue of a weighted problem associated with the Neumann spectral fractional Laplacian. This analysis is related to the investigation of the survival threshold in population dynamics. Our main result concerns the optimization of such threshold with respect to the fractional order [Formula: see text], the case [Formula: see text] corresponding to the standard Neumann Laplacian: when the habitat is not too fragmented, the principal positive eigenvalue can not have local minima for [Formula: see text]. As a consequence, the best strategy for survival is either following the diffusion with [Formula: see text] (i.e. Brownian diffusion), or with the lowest possible s (i.e. diffusion allowing long jumps), depending on the size of the domain. In addition, we show that analogous results hold for the standard fractional Laplacian in [Formula: see text], in periodic environments.

Two-faced property of a market factor in asset pricing and diversification effect

NASA Astrophysics Data System (ADS)

Eom, Cheoljun

2017-04-01

This study empirically investigates the test hypothesis that a market factor acting as a representative common factor in the pricing models has a negative influence on constructing a well-diversified portfolio from the Markowitz mean-variance optimization function (MVOF). We use the comparative correlation matrix (C-CM) method to control a single eigenvalue among all eigenvalues included in the sample correlation matrix (S-CM), through the random matrix theory (RMT). In particular, this study observes the effect of the largest eigenvalue that has the property of the market factor. According to the results, the largest eigenvalue has the highest explanatory power on the stock return changes. The C-CM without the largest eigenvalue in the S-CM constructs a more diversified portfolio capable of improving the practical applicability of the MVOF. Moreover, the more diversified portfolio constructed from this C-CM has better out-of-sample performance in the future period. These results support the test hypothesis for the two-faced property of the market factor, defined by the largest eigenvalue.

A few shape optimization results for a biharmonic Steklov problem

NASA Astrophysics Data System (ADS)

Buoso, Davide; Provenzano, Luigi

2015-09-01

We derive the equation of a free vibrating thin plate whose mass is concentrated at the boundary, namely a Steklov problem for the biharmonic operator. We provide Hadamard-type formulas for the shape derivatives of the corresponding eigenvalues and prove that balls are critical domains under volume constraint. Finally, we prove an isoperimetric inequality for the first positive eigenvalue.

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

Solving an inverse eigenvalue problem with triple constraints on eigenvalues, singular values, and diagonal elements

NASA Astrophysics Data System (ADS)

Wu, Sheng-Jhih; Chu, Moody T.

2017-08-01

An inverse eigenvalue problem usually entails two constraints, one conditioned upon the spectrum and the other on the structure. This paper investigates the problem where triple constraints of eigenvalues, singular values, and diagonal entries are imposed simultaneously. An approach combining an eclectic mix of skills from differential geometry, optimization theory, and analytic gradient flow is employed to prove the solvability of such a problem. The result generalizes the classical Mirsky, Sing-Thompson, and Weyl-Horn theorems concerning the respective majorization relationships between any two of the arrays of main diagonal entries, eigenvalues, and singular values. The existence theory fills a gap in the classical matrix theory. The problem might find applications in wireless communication and quantum information science. The technique employed can be implemented as a first-step numerical method for constructing the matrix. With slight modification, the approach might be used to explore similar types of inverse problems where the prescribed entries are at general locations.

Structural physical approximation for the realization of the optimal singlet fraction with two measurements

NASA Astrophysics Data System (ADS)

Adhikari, Satyabrata

2018-04-01

Structural physical approximation (SPA) has been exploited to approximate nonphysical operation such as partial transpose. It has already been studied in the context of detection of entanglement and found that if the minimum eigenvalue of SPA to partial transpose is less than 2/9 then the two-qubit state is entangled. We find application of SPA to partial transpose in the estimation of the optimal singlet fraction. We show that the optimal singlet fraction can be expressed in terms of the minimum eigenvalue of SPA to partial transpose. We also show that the optimal singlet fraction can be realized using Hong-Ou-Mandel interferometry with only two detectors. Further we have shown that the generated hybrid entangled state between a qubit and a binary coherent state can be used as a resource state in quantum teleportation.

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.

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. Our results suggest that preconditioning stem cells with the mood stabilizers lithium and VPA before transplantation may serve as an effective strategy for enhancing the therapeutic efficacy of stem cell-based therapies. Copyright © 2016. Published by Elsevier Inc.

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 essential.

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.

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 Projection free method for Generalized Eigenvalue Problem with a nonsmooth Regularizer.

PubMed

Hwang, Seong Jae; Collins, Maxwell D; Ravi, Sathya N; Ithapu, Vamsi K; Adluru, Nagesh; Johnson, Sterling C; Singh, Vikas

2015-12-01

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libraries leverage such tools extensively. However, the ability to call the underlying solver only as a "black box" can often become restrictive. Many 'human in the loop' settings in vision frequently exploit supervision from an expert, to the extent that the user can be considered a subroutine in the overall system. In other cases, there is additional domain knowledge, side or even partial information that one may want to incorporate within the formulation. In general, regularizing a (generalized) eigenvalue problem with such side information remains difficult. Motivated by these needs, this paper presents an optimization scheme to solve generalized eigenvalue problems (GEP) involving a (nonsmooth) regularizer. We start from an alternative formulation of GEP where the feasibility set of the model involves the Stiefel manifold. The core of this paper presents an end to end stochastic optimization scheme for the resultant problem. We show how this general algorithm enables improved statistical analysis of brain imaging data where the regularizer is derived from other 'views' of the disease pathology, involving clinical measurements and other image-derived representations.

Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species.

PubMed

Pocrnic, Ivan; Lourenco, Daniela A L; Masuda, Yutaka; Misztal, Ignacy

2016-10-31

A genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and Young (APY) through recursion on a small number of core animals. The number of core animals is theoretically linked to effective population size (N e ). In a simulation study, the optimal number of core animals was equal to the number of largest eigenvalues of GRM that explained 98% of its variation. The purpose of this study was to find the optimal number of core animals and estimate N e for different species. Datasets included phenotypes, pedigrees, and genotypes for populations of Holstein, Jersey, and Angus cattle, pigs, and broiler chickens. The number of genotyped animals varied from 15,000 for broiler chickens to 77,000 for Holsteins, and the number of single-nucleotide polymorphisms used for genomic prediction varied from 37,000 to 61,000. Eigenvalue decomposition of the GRM for each population determined numbers of largest eigenvalues corresponding to 90, 95, 98, and 99% of variation. The number of eigenvalues corresponding to 90% (98%) of variation was 4527 (14,026) for Holstein, 3325 (11,500) for Jersey, 3654 (10,605) for Angus, 1239 (4103) for pig, and 1655 (4171) for broiler chicken. Each trait in each species was analyzed using the APY inverse of the GRM with randomly selected core animals, and their number was equal to the number of largest eigenvalues. Realized accuracies peaked with the number of core animals corresponding to 98% of variation for Holstein and Jersey and closer to 99% for other breed/species. N e was estimated based on comparisons of eigenvalue decomposition in a simulation study. Assuming a genome length of 30 Morgan, N e was equal to 149 for Holsteins, 101 for Jerseys, 113 for Angus, 32 for pigs, and 44 for broilers. Eigenvalue profiles of GRM for common species are similar to those in simulation studies although they are affected by number of genotyped animals and genotyping quality. For all investigated species, the APY required less than 15,000 core animals. Realized accuracies were equal or greater with the APY inverse than with regular inversion. Eigenvalue analysis of GRM can provide a realistic estimate of N e .

Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

PubMed

Mazandarani, Mehran; Pariz, Naser

2018-05-01

This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Applications of polynomial optimization in financial risk investment

NASA Astrophysics Data System (ADS)

Zeng, Meilan; Fu, Hongwei

2017-09-01

Recently, polynomial optimization has many important applications in optimization, financial economics and eigenvalues of tensor, etc. This paper studies the applications of polynomial optimization in financial risk investment. We consider the standard mean-variance risk measurement model and the mean-variance risk measurement model with transaction costs. We use Lasserre's hierarchy of semidefinite programming (SDP) relaxations to solve the specific cases. The results show that polynomial optimization is effective for some financial optimization problems.

Global Optimality of the Successive Maxbet Algorithm.

ERIC Educational Resources Information Center

Hanafi, Mohamed; ten Berge, Jos M. F.

2003-01-01

It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)

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.

Study of a mixed dispersal population dynamics model

DOE PAGES

Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...

2016-08-27

In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

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.

Linear quadratic regulators with eigenvalue placement in a horizontal strip

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Dib, Hani M.; Ganesan, Sekar

1987-01-01

A method for optimally shifting the imaginary parts of the open-loop poles of a multivariable control system to the desirable closed-loop locations is presented. The optimal solution with respect to a quadratic performance index is obtained by solving a linear matrix Liapunov equation.

nu-TRLan User Guide Version 1.0: A High-Performance Software Package for Large-Scale Harmitian Eigenvalue Problems

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

Yamazaki, Ichitaro; Wu, Kesheng; Simon, Horst

2008-10-27

The original software package TRLan, [TRLan User Guide], page 24, implements the thick restart Lanczos method, [Wu and Simon 2001], page 24, for computing eigenvalues {lambda} and their corresponding eigenvectors v of a symmetric matrix A: Av = {lambda}v. Its effectiveness in computing the exterior eigenvalues of a large matrix has been demonstrated, [LBNL-42982], page 24. However, its performance strongly depends on the user-specified dimension of a projection subspace. If the dimension is too small, TRLan suffers from slow convergence. If it is too large, the computational and memory costs become expensive. Therefore, to balance the solution convergence and costs,more » users must select an appropriate subspace dimension for each eigenvalue problem at hand. To free users from this difficult task, nu-TRLan, [LNBL-1059E], page 23, adjusts the subspace dimension at every restart such that optimal performance in solving the eigenvalue problem is automatically obtained. This document provides a user guide to the nu-TRLan software package. The original TRLan software package was implemented in Fortran 90 to solve symmetric eigenvalue problems using static projection subspace dimensions. nu-TRLan was developed in C and extended to solve Hermitian eigenvalue problems. It can be invoked using either a static or an adaptive subspace dimension. In order to simplify its use for TRLan users, nu-TRLan has interfaces and features similar to those of TRLan: (1) Solver parameters are stored in a single data structure called trl-info, Chapter 4 [trl-info structure], page 7. (2) Most of the numerical computations are performed by BLAS, [BLAS], page 23, and LAPACK, [LAPACK], page 23, subroutines, which allow nu-TRLan to achieve optimized performance across a wide range of platforms. (3) To solve eigenvalue problems on distributed memory systems, the message passing interface (MPI), [MPI forum], page 23, is used. The rest of this document is organized as follows. In Chapter 2 [Installation], page 2, we provide an installation guide of the nu-TRLan software package. In Chapter 3 [Example], page 3, we present a simple nu-TRLan example program. In Chapter 4 [trl-info structure], page 7, and Chapter 5 [trlan subroutine], page 14, we describe the solver parameters and interfaces in detail. In Chapter 6 [Solver parameters], page 21, we discuss the selection of the user-specified parameters. In Chapter 7 [Contact information], page 22, we give the acknowledgements and contact information of the authors. In Chapter 8 [References], page 23, we list reference to related works.« less

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Maximizing algebraic connectivity in interconnected networks.

PubMed

Shakeri, Heman; Albin, Nathan; Darabi Sahneh, Faryad; Poggi-Corradini, Pietro; Scoglio, Caterina

2016-03-01

Algebraic connectivity, the second eigenvalue of the Laplacian matrix, is a measure of node and link connectivity on networks. When studying interconnected networks it is useful to consider a multiplex model, where the component networks operate together with interlayer links among them. In order to have a well-connected multilayer structure, it is necessary to optimally design these interlayer links considering realistic constraints. In this work, we solve the problem of finding an optimal weight distribution for one-to-one interlayer links under budget constraint. We show that for the special multiplex configurations with identical layers, the uniform weight distribution is always optimal. On the other hand, when the two layers are arbitrary, increasing the budget reveals the existence of two different regimes. Up to a certain threshold budget, the second eigenvalue of the supra-Laplacian is simple, the optimal weight distribution is uniform, and the Fiedler vector is constant on each layer. Increasing the budget past the threshold, the optimal weight distribution can be nonuniform. The interesting consequence of this result is that there is no need to solve the optimization problem when the available budget is less than the threshold, which can be easily found analytically.

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.

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

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

A Well-Tempered Hybrid Method for Solving Challenging Time-Dependent Density Functional Theory (TDDFT) Systems.

PubMed

Kasper, Joseph M; Williams-Young, David B; Vecharynski, Eugene; Yang, Chao; Li, Xiaosong

2018-04-10

The time-dependent Hartree-Fock (TDHF) and time-dependent density functional theory (TDDFT) equations allow one to probe electronic resonances of a system quickly and inexpensively. However, the iterative solution of the eigenvalue problem can be challenging or impossible to converge, using standard methods such as the Davidson algorithm for spectrally dense regions in the interior of the spectrum, as are common in X-ray absorption spectroscopy (XAS). More robust solvers, such as the generalized preconditioned locally harmonic residual (GPLHR) method, can alleviate this problem, but at the expense of higher average computational cost. A hybrid method is proposed which adapts to the problem in order to maximize computational performance while providing the superior convergence of GPLHR. In addition, a modification to the GPLHR algorithm is proposed to adaptively choose the shift parameter to enforce a convergence of states above a predefined energy threshold.

Sensitivity analysis and approximation methods for general eigenvalue problems

NASA Technical Reports Server (NTRS)

Murthy, D. V.; Haftka, R. T.

1986-01-01

Optimization of dynamic systems involving complex non-hermitian matrices is often computationally expensive. Major contributors to the computational expense are the sensitivity analysis and reanalysis of a modified design. The present work seeks to alleviate this computational burden by identifying efficient sensitivity analysis and approximate reanalysis methods. For the algebraic eigenvalue problem involving non-hermitian matrices, algorithms for sensitivity analysis and approximate reanalysis are classified, compared and evaluated for efficiency and accuracy. Proper eigenvector normalization is discussed. An improved method for calculating derivatives of eigenvectors is proposed based on a more rational normalization condition and taking advantage of matrix sparsity. Important numerical aspects of this method are also discussed. To alleviate the problem of reanalysis, various approximation methods for eigenvalues are proposed and evaluated. Linear and quadratic approximations are based directly on the Taylor series. Several approximation methods are developed based on the generalized Rayleigh quotient for the eigenvalue problem. Approximation methods based on trace theorem give high accuracy without needing any derivatives. Operation counts for the computation of the approximations are given. General recommendations are made for the selection of appropriate approximation technique as a function of the matrix size, number of design variables, number of eigenvalues of interest and the number of design points at which approximation is sought.

Fourth-order convergence of a compact scheme for the one-dimensional biharmonic equation

NASA Astrophysics Data System (ADS)

Fishelov, D.; Ben-Artzi, M.; Croisille, J.-P.

2012-09-01

The convergence of a fourth-order compact scheme to the one-dimensional biharmonic problem is established in the case of general Dirichlet boundary conditions. The compact scheme invokes value of the unknown function as well as Pade approximations of its first-order derivative. Using the Pade approximation allows us to approximate the first-order derivative within fourth-order accuracy. However, although the truncation error of the discrete biharmonic scheme is of fourth-order at interior point, the truncation error drops to first-order at near-boundary points. Nonetheless, we prove that the scheme retains its fourth-order (optimal) accuracy. This is done by a careful inspection of the matrix elements of the discrete biharmonic operator. A number of numerical examples corroborate this effect. We also present a study of the eigenvalue problem uxxxx = νu. We compute and display the eigenvalues and the eigenfunctions related to the continuous and the discrete problems. By the positivity of the eigenvalues, one can deduce the stability of of the related time-dependent problem ut = -uxxxx. In addition, we study the eigenvalue problem uxxxx = νuxx. This is related to the stability of the linear time-dependent equation uxxt = νuxxxx. Its continuous and discrete eigenvalues and eigenfunction (or eigenvectors) are computed and displayed graphically.

Sparse Covariance Matrix Estimation With Eigenvalue Constraints

PubMed Central

LIU, Han; WANG, Lie; ZHAO, Tuo

2014-01-01

We propose a new approach for estimating high-dimensional, positive-definite covariance matrices. Our method extends the generalized thresholding operator by adding an explicit eigenvalue constraint. The estimated covariance matrix simultaneously achieves sparsity and positive definiteness. The estimator is rate optimal in the minimax sense and we develop an efficient iterative soft-thresholding and projection algorithm based on the alternating direction method of multipliers. Empirically, we conduct thorough numerical experiments on simulated datasets as well as real data examples to illustrate the usefulness of our method. Supplementary materials for the article are available online. PMID:25620866

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

A finite difference Davidson procedure to sidestep full ab initio hessian calculation: Application to characterization of stationary points and transition state searches

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

Sharada, Shaama Mallikarjun; Bell, Alexis T., E-mail: mhg@bastille.cchem.berkeley.edu, E-mail: bell@cchem.berkeley.edu; Head-Gordon, Martin, E-mail: mhg@bastille.cchem.berkeley.edu, E-mail: bell@cchem.berkeley.edu

2014-04-28

The cost of calculating nuclear hessians, either analytically or by finite difference methods, during the course of quantum chemical analyses can be prohibitive for systems containing hundreds of atoms. In many applications, though, only a few eigenvalues and eigenvectors, and not the full hessian, are required. For instance, the lowest one or two eigenvalues of the full hessian are sufficient to characterize a stationary point as a minimum or a transition state (TS), respectively. We describe here a method that can eliminate the need for hessian calculations for both the characterization of stationary points as well as searches for saddlemore » points. A finite differences implementation of the Davidson method that uses only first derivatives of the energy to calculate the lowest eigenvalues and eigenvectors of the hessian is discussed. This method can be implemented in conjunction with geometry optimization methods such as partitioned-rational function optimization (P-RFO) to characterize stationary points on the potential energy surface. With equal ease, it can be combined with interpolation methods that determine TS guess structures, such as the freezing string method, to generate approximate hessian matrices in lieu of full hessians as input to P-RFO for TS optimization. This approach is shown to achieve significant cost savings relative to exact hessian calculation when applied to both stationary point characterization as well as TS optimization. The basic reason is that the present approach scales one power of system size lower since the rate of convergence is approximately independent of the size of the system. Therefore, the finite-difference Davidson method is a viable alternative to full hessian calculation for stationary point characterization and TS search particularly when analytical hessians are not available or require substantial computational effort.« less

A variational eigenvalue solver on a photonic quantum processor

PubMed Central

Peruzzo, Alberto; McClean, Jarrod; Shadbolt, Peter; Yung, Man-Hong; Zhou, Xiao-Qi; Love, Peter J.; Aspuru-Guzik, Alán; O’Brien, Jeremy L.

2014-01-01

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the physical dimension grows exponentially, finding the eigenvalues of certain operators is one such intractable problem and remains a fundamental challenge. The quantum phase estimation algorithm efficiently finds the eigenvalue of a given eigenvector but requires fully coherent evolution. Here we present an alternative approach that greatly reduces the requirements for coherent evolution and combine this method with a new approach to state preparation based on ansätze and classical optimization. We implement the algorithm by combining a highly reconfigurable photonic quantum processor with a conventional computer. We experimentally demonstrate the feasibility of this approach with an example from quantum chemistry—calculating the ground-state molecular energy for He–H+. The proposed approach drastically reduces the coherence time requirements, enhancing the potential of quantum resources available today and in the near future. PMID:25055053

COSAL: A black-box compressible stability analysis code for transition prediction in three-dimensional boundary layers

NASA Technical Reports Server (NTRS)

Malik, M. R.

1982-01-01

A fast computer code COSAL for transition prediction in three dimensional boundary layers using compressible stability analysis is described. The compressible stability eigenvalue problem is solved using a finite difference method, and the code is a black box in the sense that no guess of the eigenvalue is required from the user. Several optimization procedures were incorporated into COSAL to calculate integrated growth rates (N factor) for transition correlation for swept and tapered laminar flow control wings using the well known e to the Nth power method. A user's guide to the program is provided.

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).

Simultaneous optical flow and source estimation: Space–time discretization and preconditioning

PubMed Central

Andreev, R.; Scherzer, O.; Zulehner, W.

2015-01-01

We consider the simultaneous estimation of an optical flow field and an illumination source term in a movie sequence. The particular optical flow equation is obtained by assuming that the image intensity is a conserved quantity up to possible sources and sinks which represent varying illumination. We formulate this problem as an energy minimization problem and propose a space–time simultaneous discretization for the optimality system in saddle-point form. We investigate a preconditioning strategy that renders the discrete system well-conditioned uniformly in the discretization resolution. Numerical experiments complement the theory. PMID:26435561

A Polynomial-Based Nonlinear Least Squares Optimized Preconditioner for Continuous and Discontinuous Element-Based Discretizations of the Euler Equations

DTIC Science & Technology

2014-01-01

system (here using left- preconditioning ) (KÃ)x = Kb̃, (3.1) where K is a low-order polynomial in à given by K = s(Ã) = m∑ i=0 kià i, (3.2) and has a... system with a complex spectrum, region E in the complex plane must be some convex form (e.g., an ellipse or polygon) that approximately encloses the...preconditioners with p = 2 and p = 20 on the spectrum of the preconditioned system matrices Kà and KH̃ for both CG Schur-complement form and DG form cases

Eigenvectors of optimal color spectra.

PubMed

Flinkman, Mika; Laamanen, Hannu; Tuomela, Jukka; Vahimaa, Pasi; Hauta-Kasari, Markku

2013-09-01

Principal component analysis (PCA) and weighted PCA were applied to spectra of optimal colors belonging to the outer surface of the object-color solid or to so-called MacAdam limits. The correlation matrix formed from this data is a circulant matrix whose biggest eigenvalue is simple and the corresponding eigenvector is constant. All other eigenvalues are double, and the eigenvectors can be expressed with trigonometric functions. Found trigonometric functions can be used as a general basis to reconstruct all possible smooth reflectance spectra. When the spectral data are weighted with an appropriate weight function, the essential part of the color information is compressed to the first three components and the shapes of the first three eigenvectors correspond to one achromatic response function and to two chromatic response functions, the latter corresponding approximately to Munsell opponent-hue directions 9YR-9B and 2BG-2R.

3-D phononic crystals with ultra-wide band gaps

PubMed Central

Lu, Yan; Yang, Yang; Guest, James K.; Srivastava, Ankit

2017-01-01

In this paper gradient based topology optimization (TO) is used to discover 3-D phononic structures that exhibit ultra-wide normalized all-angle all-mode band gaps. The challenging computational task of repeated 3-D phononic band-structure evaluations is accomplished by a combination of a fast mixed variational eigenvalue solver and distributed Graphic Processing Unit (GPU) parallel computations. The TO algorithm utilizes the material distribution-based approach and a gradient-based optimizer. The design sensitivity for the mixed variational eigenvalue problem is derived using the adjoint method and is implemented through highly efficient vectorization techniques. We present optimized results for two-material simple cubic (SC), body centered cubic (BCC), and face centered cubic (FCC) crystal structures and show that in each of these cases different initial designs converge to single inclusion network topologies within their corresponding primitive cells. The optimized results show that large phononic stop bands for bulk wave propagation can be achieved at lower than close packed spherical configurations leading to lighter unit cells. For tungsten carbide - epoxy crystals we identify all angle all mode normalized stop bands exceeding 100%, which is larger than what is possible with only spherical inclusions. PMID:28233812

3-D phononic crystals with ultra-wide band gaps.

PubMed

Lu, Yan; Yang, Yang; Guest, James K; Srivastava, Ankit

2017-02-24

In this paper gradient based topology optimization (TO) is used to discover 3-D phononic structures that exhibit ultra-wide normalized all-angle all-mode band gaps. The challenging computational task of repeated 3-D phononic band-structure evaluations is accomplished by a combination of a fast mixed variational eigenvalue solver and distributed Graphic Processing Unit (GPU) parallel computations. The TO algorithm utilizes the material distribution-based approach and a gradient-based optimizer. The design sensitivity for the mixed variational eigenvalue problem is derived using the adjoint method and is implemented through highly efficient vectorization techniques. We present optimized results for two-material simple cubic (SC), body centered cubic (BCC), and face centered cubic (FCC) crystal structures and show that in each of these cases different initial designs converge to single inclusion network topologies within their corresponding primitive cells. The optimized results show that large phononic stop bands for bulk wave propagation can be achieved at lower than close packed spherical configurations leading to lighter unit cells. For tungsten carbide - epoxy crystals we identify all angle all mode normalized stop bands exceeding 100%, which is larger than what is possible with only spherical inclusions.

Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1980-01-01

Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalue and the directional derivatives of closed loop eigenvectors. An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties. An algorithm is presented that can be used to select a feedback gain matrix for the linear state feedback problem which produces a specified asymptotic eigenstructure. Another algorithm is given to compute the asymptotic eigenstructure properties inherent in a given set of quadratic weights. Finally, it is shown that optimal root loci for nongeneric problems can be approximated by generic ones in the nonasymptotic region.

Application of preconditioned alternating direction method of multipliers in depth from focal stack

NASA Astrophysics Data System (ADS)

Javidnia, Hossein; Corcoran, Peter

2018-03-01

Postcapture refocusing effect in smartphone cameras is achievable using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the extended depth of field effect in this application can be improved significantly by computing an accurate depth map, which has been an open issue for decades. To tackle this issue, a framework is proposed based on a preconditioned alternating direction method of multipliers for depth from the focal stack and synthetic defocus application. In addition to its ability to provide high structural accuracy, the optimization function of the proposed framework can, in fact, converge faster and better than state-of-the-art methods. The qualitative evaluation has been done on 21 sets of focal stacks and the optimization function has been compared against five other methods. Later, 10 light field image sets have been transformed into focal stacks for quantitative evaluation purposes. Preliminary results indicate that the proposed framework has a better performance in terms of structural accuracy and optimization in comparison to the current state-of-the-art methods.

Acceleration of high resolution temperature based optimization for hyperthermia treatment planning using element grouping.

PubMed

Kok, H P; de Greef, M; Bel, A; Crezee, J

2009-08-01

In regional hyperthermia, optimization is useful to obtain adequate applicator settings. A speed-up of the previously published method for high resolution temperature based optimization is proposed. Element grouping as described in literature uses selected voxel sets instead of single voxels to reduce computation time. Elements which achieve their maximum heating potential for approximately the same phase/amplitude setting are grouped. To form groups, eigenvalues and eigenvectors of precomputed temperature matrices are used. At high resolution temperature matrices are unknown and temperatures are estimated using low resolution (1 cm) computations and the high resolution (2 mm) temperature distribution computed for low resolution optimized settings using zooming. This technique can be applied to estimate an upper bound for high resolution eigenvalues. The heating potential of elements was estimated using these upper bounds. Correlations between elements were estimated with low resolution eigenvalues and eigenvectors, since high resolution eigenvectors remain unknown. Four different grouping criteria were applied. Constraints were set to the average group temperatures. Element grouping was applied for five patients and optimal settings for the AMC-8 system were determined. Without element grouping the average computation times for five and ten runs were 7.1 and 14.4 h, respectively. Strict grouping criteria were necessary to prevent an unacceptable exceeding of the normal tissue constraints (up to approximately 2 degrees C), caused by constraining average instead of maximum temperatures. When strict criteria were applied, speed-up factors of 1.8-2.1 and 2.6-3.5 were achieved for five and ten runs, respectively, depending on the grouping criteria. When many runs are performed, the speed-up factor will converge to 4.3-8.5, which is the average reduction factor of the constraints and depends on the grouping criteria. Tumor temperatures were comparable. Maximum exceeding of the constraint in a hot spot was 0.24-0.34 degree C; average maximum exceeding over all five patients was 0.09-0.21 degree C, which is acceptable. High resolution temperature based optimization using element grouping can achieve a speed-up factor of 4-8, without large deviations from the conventional method.

Remote preconditioning and major clinical complications following adult cardiovascular surgery: systematic review and meta-analysis.

PubMed

Healy, D A; Khan, W A; Wong, C S; Moloney, M Clarke; Grace, P A; Coffey, J C; Dunne, C; Walsh, S R; Sadat, U; Gaunt, M E; Chen, S; Tehrani, S; Hausenloy, D J; Yellon, D M; Kramer, R S; Zimmerman, R F; Lomivorotov, V V; Shmyrev, V A; Ponomarev, D N; Rahman, I A; Mascaro, J G; Bonser, R S; Jeon, Y; Hong, D M; Wagner, R; Thielmann, M; Heusch, G; Zacharowski, K; Meybohm, P; Bein, B; Tang, T Y

2014-09-01

A number of 'proof-of-concept' trials suggest that remote ischaemic preconditioning (RIPC) reduces surrogate markers of end-organ injury in patients undergoing major cardiovascular surgery. To date, few studies have involved hard clinical outcomes as primary end-points. Randomised clinical trials of RIPC in major adult cardiovascular surgery were identified by a systematic review of electronic abstract databases, conference proceedings and article reference lists. Clinical end-points were extracted from trial reports. In addition, trial principal investigators provided unpublished clinical outcome data. In total, 23 trials of RIPC in 2200 patients undergoing major adult cardiovascular surgery were identified. RIPC did not have a significant effect on clinical end-points (death, peri-operative myocardial infarction (MI), renal failure, stroke, mesenteric ischaemia, hospital or critical care length of stay). Pooled data from pilot trials cannot confirm that RIPC has any significant effect on clinically relevant end-points. Heterogeneity in study inclusion and exclusion criteria and in the type of preconditioning stimulus limits the potential for extrapolation at present. An effort must be made to clarify the optimal preconditioning stimulus. Following this, large-scale trials in a range of patient populations are required to ascertain the role of this simple, cost-effective intervention in routine practice. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

LONG-TERM PRECONDITIONING OF PLANTLETS: A PRACTICAL METHOD FOR ENHANCING SURVIVAL OF PINEAPPLE (Ananas comosus Merr.) SHOOT TIPS CRYOPRESERVED USING VITRIFICATION.

PubMed

Hu, W H; Liu, S F; Liaw, S I

2015-01-01

The purpose of this study was to develop an efficient cryopreservation protocol for pineapple (Ananas comosus Merr.) shoot tips. The optimal state of pineapple plantlets was investigated by using sucrose preconditioning to enhance survival after cryostorage. To achieve a suitable state of plantlets before cryopreservation, 0.2 M to 0.4 M sucrose concentrations combined with short- (0-7 days), medium- (15-30 days), and long-term (75-150 days) preconditioning periods were compared. The highest survival (100 %) was achieved using the following procedure: intact plantlets underwent long-term preconditioning with 0.2 M sucrose for 135 days, dissected shoot tips were treated with a loading solution containing 2.0 M glycerol + 0.4 M sucrose for 60 min at 25 degree and the shoot tips were dehydrated in PVS2 for 2h at 0 degree C before being plunged in liquid nitrogen. Rewarming was conducted in a water-bath for 30 s at 40 degree C and PVS2 was replaced with a 1.2 M sucrose solution for 30 min at 25 degree C. The shoot tips were transferred on semisolid medium and left in the dark for 1 week, then in dim light for 3 weeks.

Key elements of optimal treatment decision-making for surgeons and older patients with colorectal or pancreatic cancer: A qualitative study.

PubMed

Geessink, Noralie H; Schoon, Yvonne; van Herk, Hanneke C P; van Goor, Harry; Olde Rikkert, Marcel G M

2017-03-01

To identify key elements of optimal treatment decision-making for surgeons and older patients with colorectal (CRC) or pancreatic cancer (PC). Six focus groups with different participants were performed: three with older CRC/PC patients and relatives, and three with physicians. Supplementary in-depth interviews were conducted in another seven patients. Framework analysis was used to identify key elements in decision-making. 23 physicians, 22 patients and 14 relatives participated. Three interacting components were revealed: preconditions, content and facilitators of decision-making. To provide optimal information about treatments' impact on an older patient's daily life, physicians should obtain an overall picture and take into account patients' frailty. Depending on patients' preferences and capacities, dividing decision-making into more sessions will be helpful and simultaneously emphasize patients' own responsibility. GPs may have a valuable contribution because of their background knowledge and supportive role. Stakeholders identified several crucial elements in the complex surgical decision-making of older CRC/PC patients. Structured qualitative research may also be of great help in optimizing other treatment directed decision-making processes. Surgeons should be trained in examining preconditions and useful facilitators in decision-making in older CRC/PC patients to optimize its content and to improve the quality of shared care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Waste to Energy Potential - A High Concentration Anaerobic Bioreactor

DTIC Science & Technology

2012-05-23

process • bacteria consume approximately 50-70% of the solids placed in the bioreactor and, generate a biogas • What do you get? • Biogas that can be...Symposium & Exhibition Objectives of the Demo • Establish the inoculation/startup procedures • Optimize presorting requirements • Evaluate biogas ...quality • Establish biogas pre-conditioning requirements • Understand the cause of upset conditions • Determine – optimal mixture of feedstock

A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems

NASA Astrophysics Data System (ADS)

Babaee, Hessam; Choi, Minseok; Sapsis, Themistoklis P.; Karniadakis, George Em

2017-09-01

We develop a new robust methodology for the stochastic Navier-Stokes equations based on the dynamically-orthogonal (DO) and bi-orthogonal (BO) methods [1-3]. Both approaches are variants of a generalized Karhunen-Loève (KL) expansion in which both the stochastic coefficients and the spatial basis evolve according to system dynamics, hence, capturing the low-dimensional structure of the solution. The DO and BO formulations are mathematically equivalent [3], but they exhibit computationally complimentary properties. Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues. To this end, we combine the two methods into a robust hybrid framework and in addition we employ a pseudo-inverse technique to invert the covariance matrix. The robustness of the proposed method stems from addressing the following issues in the DO/BO formulation: (i) eigenvalue crossing: we resolve the issue of eigenvalue crossing in the BO formulation by switching to the DO near eigenvalue crossing using the equivalence theorem and switching back to BO when the distance between eigenvalues is larger than a threshold value; (ii) ill-conditioned covariance matrix: we utilize a pseudo-inverse strategy to invert the covariance matrix; (iii) adaptivity: we utilize an adaptive strategy to add/remove modes to resolve the covariance matrix up to a threshold value. In particular, we introduce a soft-threshold criterion to allow the system to adapt to the newly added/removed mode and therefore avoid repetitive and unnecessary mode addition/removal. When the total variance approaches zero, we show that the DO/BO formulation becomes equivalent to the evolution equation of the Optimally Time-Dependent modes [4]. We demonstrate the capability of the proposed methodology with several numerical examples, namely (i) stochastic Burgers equation: we analyze the performance of the method in the presence of eigenvalue crossing and zero eigenvalues; (ii) stochastic Kovasznay flow: we examine the method in the presence of a singular covariance matrix; and (iii) we examine the adaptivity of the method for an incompressible flow over a cylinder where for large stochastic forcing thirteen DO/BO modes are active.

Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1979-01-01

Results are given on the relationships between closed loop eigenstructures, state feedback gain matrices of the linear state feedback problem, and quadratic weights of the linear quadratic regulator. Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used for the first time to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalues and the directional derivatives of closed loop eigenvectors (with respect to a scalar multiplying the feedback gain matrix or the quadratic control weight). An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, sufficient conditions to be in it are given, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties.

Increased Agrobacterium-mediated transformation and rooting efficiencies in canola (Brassica napus L.) from hypocotyl segment explants

NASA Technical Reports Server (NTRS)

Cardoza, V.; Stewart, C. N.

2003-01-01

An efficient protocol for the production of transgenic Brassica napus cv. Westar plants was developed by optimizing two important parameters: preconditioning time and co-cultivation time. Agrobacterium tumefaciens-mediated transformation was performed using hypocotyls as explant tissue. Two variants of a green fluorescent protein (GFP)-encoding gene--mGFP5-ER and eGFP--both under the constitutive expression of the cauliflower mosaic virus 35S promoter, were used for the experiments. Optimizing the preconditioning time to 72 h and co-cultivation time with Agrobacterium to 48 h provided the increase in the transformation efficiency from a baseline of 4% to 25%. With mGFP5-ER, the transformation rate was 17% and with eGFP it was 25%. Transgenic shoots were selected on 200 mg/l kanamycin. Rooting efficiency was 100% on half-strength Murashige and Skoog medium with 10 g/l sucrose and 0.5 mg/l indole butyric acid in the presence of kanamycin.

Thermodynamic characterization of synchronization-optimized oscillator networks

NASA Astrophysics Data System (ADS)

Yanagita, Tatsuo; Ichinomiya, Takashi

2014-12-01

We consider a canonical ensemble of synchronization-optimized networks of identical oscillators under external noise. By performing a Markov chain Monte Carlo simulation using the Kirchhoff index, i.e., the sum of the inverse eigenvalues of the Laplacian matrix (as a graph Hamiltonian of the network), we construct more than 1 000 different synchronization-optimized networks. We then show that the transition from star to core-periphery structure depends on the connectivity of the network, and is characterized by the node degree variance of the synchronization-optimized ensemble. We find that thermodynamic properties such as heat capacity show anomalies for sparse networks.

Seismic waveform inversion best practices: regional, global and exploration test cases

NASA Astrophysics Data System (ADS)

Modrak, Ryan; Tromp, Jeroen

2016-09-01

Reaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence associated with strong nonlinearity, one or two test cases are not enough to reliably inform such decisions. We identify best practices, instead, using four seismic near-surface problems, one regional problem and two global problems. To make meaningful quantitative comparisons between methods, we carry out hundreds of inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that limited-memory BFGS provides computational savings over nonlinear conjugate gradient methods in a wide range of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization and total variation regularization are effective in different contexts. Besides questions of one strategy or another, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details involving the line search and restart conditions have a strong effect on computational cost, regardless of the chosen nonlinear optimization algorithm.

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.

Computers and the Thought-Producing Self of the Young Child.

ERIC Educational Resources Information Center

Fomichova, Olga; Fomichov, Vladimir

2000-01-01

Discusses a new, informational-based cybernetic conception of the early development of child consciousness. Suggests a solution to the fundamental problem of formulating and creating the optimal cognitive preconditions of successful child-computer interaction, and analyzes some negative aspects of using intelligent computer and communications…

Linear-scaling time-dependent density-functional theory beyond the Tamm-Dancoff approximation: Obtaining efficiency and accuracy with in situ optimised local orbitals.

PubMed

Zuehlsdorff, T J; Hine, N D M; Payne, M C; Haynes, P D

2015-11-28

We present a solution of the full time-dependent density-functional theory (TDDFT) eigenvalue equation in the linear response formalism exhibiting a linear-scaling computational complexity with system size, without relying on the simplifying Tamm-Dancoff approximation (TDA). The implementation relies on representing the occupied and unoccupied subspaces with two different sets of in situ optimised localised functions, yielding a very compact and efficient representation of the transition density matrix of the excitation with the accuracy associated with a systematic basis set. The TDDFT eigenvalue equation is solved using a preconditioned conjugate gradient algorithm that is very memory-efficient. The algorithm is validated on a small test molecule and a good agreement with results obtained from standard quantum chemistry packages is found, with the preconditioner yielding a significant improvement in convergence rates. The method developed in this work is then used to reproduce experimental results of the absorption spectrum of bacteriochlorophyll in an organic solvent, where it is demonstrated that the TDA fails to reproduce the main features of the low energy spectrum, while the full TDDFT equation yields results in good qualitative agreement with experimental data. Furthermore, the need for explicitly including parts of the solvent into the TDDFT calculations is highlighted, making the treatment of large system sizes necessary that are well within reach of the capabilities of the algorithm introduced here. Finally, the linear-scaling properties of the algorithm are demonstrated by computing the lowest excitation energy of bacteriochlorophyll in solution. The largest systems considered in this work are of the same order of magnitude as a variety of widely studied pigment-protein complexes, opening up the possibility of studying their properties without having to resort to any semiclassical approximations to parts of the protein environment.

Parallel-vector computation for structural analysis and nonlinear unconstrained optimization problems

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.

1990-01-01

Practical engineering application can often be formulated in the form of a constrained optimization problem. There are several solution algorithms for solving a constrained optimization problem. One approach is to convert a constrained problem into a series of unconstrained problems. Furthermore, unconstrained solution algorithms can be used as part of the constrained solution algorithms. Structural optimization is an iterative process where one starts with an initial design, a finite element structure analysis is then performed to calculate the response of the system (such as displacements, stresses, eigenvalues, etc.). Based upon the sensitivity information on the objective and constraint functions, an optimizer such as ADS or IDESIGN, can be used to find the new, improved design. For the structural analysis phase, the equation solver for the system of simultaneous, linear equations plays a key role since it is needed for either static, or eigenvalue, or dynamic analysis. For practical, large-scale structural analysis-synthesis applications, computational time can be excessively large. Thus, it is necessary to have a new structural analysis-synthesis code which employs new solution algorithms to exploit both parallel and vector capabilities offered by modern, high performance computers such as the Convex, Cray-2 and Cray-YMP computers. The objective of this research project is, therefore, to incorporate the latest development in the parallel-vector equation solver, PVSOLVE into the widely popular finite-element production code, such as the SAP-4. Furthermore, several nonlinear unconstrained optimization subroutines have also been developed and tested under a parallel computer environment. The unconstrained optimization subroutines are not only useful in their own right, but they can also be incorporated into a more popular constrained optimization code, such as ADS.

Some Results on Proper Eigenvalues and Eigenvectors with Applications to Scaling.

ERIC Educational Resources Information Center

McDonald, Roderick P.; And Others

1979-01-01

Problems in avoiding the singularity problem in analyzing matrices for optimal scaling are addressed. Conditions are given under which the stationary points and values of a ratio of quadratic forms in two singular matrices can be obtained by a series of simple matrix operations. (Author/JKS)

Legendre-tau approximation for functional differential equations. Part 2: The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, K.; Teglas, R.

1984-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

Legendre-tau approximation for functional differential equations. II - The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, Kazufumi; Teglas, Russell

1987-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

Optimal Periodic Control Theory.

DTIC Science & Technology

1980-08-01

single pair of complex eigenvalues are restricted to the unit circle in the complex plane . This is shown by first applying the reciprocity property to a...figure 6.2a and for H in figure 6.2b. Traversing the right half plot of figure 6.1a in a counter-clockwise direction, beginning at the origin...respectively. Only the lower half of the plots are shown because this region provides the solutions of most interest to the optimal periodic control problem

Remote ischemic preconditioning with a specialized protocol activates the non-neuronal cardiac cholinergic system and increases ATP content in the heart.

PubMed

Oikawa, Shino; Mano, Asuka; Takahashi, Rina; Kakinuma, Yoshihiko

2015-11-01

Ischemic preconditioning (IPC) renders the targeted organ resistant to prolonged ischemic insults, leading to organoprotection. Among several means to achieve IPC, we reported that remote ischemic preconditioning (RIPC) activates the non-neuronal cardiac cholinergic system (NNCCS) to accelerate de novo ACh synthesis in cardiomyocytes. In the current study, we aimed to optimize a specific protocol to most efficiently activate NNCCS using RIPC. In this study, we elucidated that the protocol with 3 min of ischemia repeated three times increased cardiac ChAT expression (139.2 ± 0.4%; P < 0.05) as well as ACh (14.2 ± 2.0× 10(-8) M; P< 0.05) and ATP content (2.13 ± 0.19 μmol/g tissue; P < 0.05) in the heart. Moreover, in the specific protocol, several characteristic responses against energy starvation and for obtaining adequate energy were observed; therefore, it is suggested that RIPC evokes a robust response by the heart to activate NNCCS through the modification of energy metabolism. Copyright © 2015 Elsevier B.V. All rights reserved.

Platelet rich plasma clot releasate preconditioning induced PI3K/AKT/NFκB signaling enhances survival and regenerative function of rat bone marrow mesenchymal stem cells in hostile microenvironments.

PubMed

Peng, Yan; Huang, Sha; Wu, Yan; Cheng, Biao; Nie, Xiaohu; Liu, Hongwei; Ma, Kui; Zhou, Jiping; Gao, Dongyun; Feng, Changjiang; Yang, Siming; Fu, Xiaobing

2013-12-15

Mesenchymal stem cells (MSCs) have been optimal targets in the development of cell based therapies, but their limited availability and high death rate after transplantation remains a concern in clinical applications. This study describes novel effects of platelet rich clot releasate (PRCR) on rat bone marrow-derived MSCs (BM-MSCs), with the former driving a gene program, which can reduce apoptosis and promote the regenerative function of the latter in hostile microenvironments through enhancement of paracrine/autocrine factors. By using reverse transcription-polymerase chain reaction, immunofluorescence and western blot analyses, we showed that PRCR preconditioning could alleviate the apoptosis of BM-MSCs under stress conditions induced by hydrogen peroxide (H2O2) and serum deprivation by enhancing expression of vascular endothelial growth factor and platelet-derived growth factor (PDGF) via stimulation of the platelet-derived growth factor receptor (PDGFR)/PI3K/AKT/NF-κB signaling pathways. Furthermore, the effects of PRCR preconditioned GFP-BM-MSCs subcutaneously transplanted into rats 6 h after wound surgery were examined by histological and other tests from days 0-22 after transplantation. Engraftment of the PRCR preconditioned BM-MSCs not only significantly attenuated apoptosis and wound size but also improved epithelization and blood vessel regeneration of skin via regulation of the wound microenvironment. Thus, preconditioning with PRCR, which reprograms BM-MSCs to tolerate hostile microenvironments and enhance regenerative function by increasing levels of paracrine factors through PDGFR-α/PI3K/AKT/NF-κB signaling pathways would be a safe method for boosting the effectiveness of transplantation therapy in the clinic.

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 promise. In addition, we will also highlight the role of gene reprogramming and mitochondrial biogenesis in the preconditioning-mediated neuroprotective events.

Vulnerable Atherosclerotic Plaque Elasticity Reconstruction Based on a Segmentation-Driven Optimization Procedure Using Strain Measurements: Theoretical Framework

PubMed Central

Le Floc’h, Simon; Tracqui, Philippe; Finet, Gérard; Gharib, Ahmed M.; Maurice, Roch L.; Cloutier, Guy; Pettigrew, Roderic I.

2016-01-01

It is now recognized that prediction of the vulnerable coronary plaque rupture requires not only an accurate quantification of fibrous cap thickness and necrotic core morphology but also a precise knowledge of the mechanical properties of plaque components. Indeed, such knowledge would allow a precise evaluation of the peak cap-stress amplitude, which is known to be a good biomechanical predictor of plaque rupture. Several studies have been performed to reconstruct a Young’s modulus map from strain elastograms. It seems that the main issue for improving such methods does not rely on the optimization algorithm itself, but rather on preconditioning requiring the best estimation of the plaque components’ contours. The present theoretical study was therefore designed to develop: 1) a preconditioning model to extract the plaque morphology in order to initiate the optimization process, and 2) an approach combining a dynamic segmentation method with an optimization procedure to highlight the modulogram of the atherosclerotic plaque. This methodology, based on the continuum mechanics theory prescribing the strain field, was successfully applied to seven intravascular ultrasound coronary lesion morphologies. The reconstructed cap thickness, necrotic core area, calcium area, and the Young’s moduli of the calcium, necrotic core, and fibrosis were obtained with mean relative errors of 12%, 4% and 1%, 43%, 32%, and 2%, respectively. PMID:19164080

Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states

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

McClean, Jarrod R.; Kimchi-Schwartz, Mollie E.; Carter, Jonathan

Using quantum devices supported by classical computational resources is a promising approach to quantum-enabled computation. One powerful example of such a hybrid quantum-classical approach optimized for classically intractable eigenvalue problems is the variational quantum eigensolver, built to utilize quantum resources for the solution of eigenvalue problems and optimizations with minimal coherence time requirements by leveraging classical computational resources. These algorithms have been placed as leaders among the candidates for the first to achieve supremacy over classical computation. Here, we provide evidence for the conjecture that variational approaches can automatically suppress even nonsystematic decoherence errors by introducing an exactly solvable channelmore » model of variational state preparation. Moreover, we develop a more general hierarchy of measurement and classical computation that allows one to obtain increasingly accurate solutions by leveraging additional measurements and classical resources. In conclusion, we demonstrate numerically on a sample electronic system that this method both allows for the accurate determination of excited electronic states as well as reduces the impact of decoherence, without using any additional quantum coherence time or formal error-correction codes.« less

Material identification based on electrostatic sensing technology

NASA Astrophysics Data System (ADS)

Liu, Kai; Chen, Xi; Li, Jingnan

2018-04-01

When the robot travels on the surface of different media, the uncertainty of the medium will seriously affect the autonomous action of the robot. In this paper, the distribution characteristics of multiple electrostatic charges on the surface of materials are detected, so as to improve the accuracy of the existing electrostatic signal material identification methods, which is of great significance to help the robot optimize the control algorithm. In this paper, based on the electrostatic signal material identification method proposed by predecessors, the multi-channel detection circuit is used to obtain the electrostatic charge distribution at different positions of the material surface, the weights are introduced into the eigenvalue matrix, and the weight distribution is optimized by the evolutionary algorithm, which makes the eigenvalue matrix more accurately reflect the surface charge distribution characteristics of the material. The matrix is used as the input of the k-Nearest Neighbor (kNN)classification algorithm to classify the dielectric materials. The experimental results show that the proposed method can significantly improve the recognition rate of the existing electrostatic signal material recognition methods.

Communication Skills Training Increases Self-Efficacy of Health Care Professionals

ERIC Educational Resources Information Center

Norgaard, Birgitte; Ammentorp, Jette; Kyvik, Kirsten Ohm; Kofoed, Poul-Erik

2012-01-01

Introduction: Despite the knowledge of good communication as a precondition for optimal care and treatment in health care, serious communication problems are still experienced by patients as well as by health care professionals. An orthopedic surgery department initiated a 3-day communication skills training course for all staff members expecting…

An Extension of the Krieger-Li-Iafrate Approximation to the Optimized-Effective-Potential Method

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

Wilson, B.G.

1999-11-11

The Krieger-Li-Iafrate approximation can be expressed as the zeroth order result of an unstable iterative method for solving the integral equation form of the optimized-effective-potential method. By pre-conditioning the iterate a first order correction can be obtained which recovers the bulk of quantal oscillations missing in the zeroth order approximation. A comparison of calculated total energies are given with Krieger-Li-Iafrate, Local Density Functional, and Hyper-Hartree-Fock results for non-relativistic atoms and ions.

Giving rheumatology patients online home access to their electronic medical record (EMR): advantages, drawbacks and preconditions according to care providers.

PubMed

van der Vaart, Rosalie; Drossaert, Constance H C; Taal, Erik; van de Laar, Mart A F J

2013-09-01

Technology enables patients home access to their electronic medical record (EMR), via a patient portal. This study aims to analyse (dis)advantages, preconditions and suitable content for this service, according to rheumatology health professionals. A two-phase policy Delphi study was conducted. First, interviews were performed with nurses/nurse practitioners (n = 9) and rheumatologists (n = 13). Subsequently, collected responses were quantified, using a questionnaire among the interviewees. The following advantages of patient home access to the EMR were reported: (1) enhancement of patient participation in treatment, (2) increased knowledge and self-management, (3) improved patient-provider interaction, (4) increased patient safety, and (5) better communication with others. Foreseen disadvantages of the service included: (1) problems with interpretation of data, (2) extra workload, (3) a change in consultation content, and (4) disturbing the patient-provider interaction. Also, the following preconditions emerged from the data: (1) optimal security, (2) no extra record, but a patient-accessible section, (3) no access to clinical notes, and (4) a lag time on the release of lab data. Most respondents reported that data on diagnosis, medication, treatment plan and consultations could be released to patients. On releasing more complex data, such as bodily examinations, lab results and radiological images the opinions differed considerably. Providing patients home access to their medical record might be a valuable next step into patient empowerment and in service towards the patient, provided that security is optimal and content and presentation of data are carefully considered.

Local CC2 response method based on the Laplace transform: analytic energy gradients for ground and excited states.

PubMed

Ledermüller, Katrin; Schütz, Martin

2014-04-28

A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.

Eigenvalue and eigenvector sensitivity and approximate analysis for repeated eigenvalue problems

NASA Technical Reports Server (NTRS)

Hou, Gene J. W.; Kenny, Sean P.

1991-01-01

A set of computationally efficient equations for eigenvalue and eigenvector sensitivity analysis are derived, and a method for eigenvalue and eigenvector approximate analysis in the presence of repeated eigenvalues is presented. The method developed for approximate analysis involves a reparamaterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations of changes in both the eigenvalues and eigenvectors associated with the repeated eigenvalue problem. Examples are given to demonstrate the application of such equations for sensitivity and approximate analysis.

Optimal scheduling of micro grids based on single objective programming

NASA Astrophysics Data System (ADS)

Chen, Yue

2018-04-01

Faced with the growing demand for electricity and the shortage of fossil fuels, how to optimally optimize the micro-grid has become an important research topic to maximize the economic, technological and environmental benefits of the micro-grid. This paper considers the role of the battery and the micro-grid and power grid to allow the exchange of power not exceeding 150kW preconditions, the main study of the economy to load for the goal is to minimize the electricity cost (abandonment of wind), to establish an optimization model, and to solve the problem by genetic algorithm. The optimal scheduling scheme is obtained and the utilization of renewable energy and the impact of the battery involved in regulation are analyzed.

NASTRAN maintenance and enhancement experiences

NASA Technical Reports Server (NTRS)

Schmitz, R. P.

1975-01-01

The current capability is described which includes isoparametric elements, optimization of grid point sequencing, and eigenvalue routine. Overlay and coding errors were corrected for cyclic symmetry, transient response, and differential stiffness rigid formats. Error corrections and program enhancements are discussed along with developments scheduled for the current year and a brief description of analyses being performed using the program.

Moving force identification based on modified preconditioned conjugate gradient method

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy

2018-06-01

This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

A sequential linear optimization approach for controller design

NASA Technical Reports Server (NTRS)

Horta, L. G.; Juang, J.-N.; Junkins, J. L.

1985-01-01

A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.

Simultaneous structural and control optimization via linear quadratic regulator eigenstructure assignment

NASA Technical Reports Server (NTRS)

Becus, G. A.; Lui, C. Y.; Venkayya, V. B.; Tischler, V. A.

1987-01-01

A method for simultaneous structural and control design of large flexible space structures (LFSS) to reduce vibration generated by disturbances is presented. Desired natural frequencies and damping ratios for the closed loop system are achieved by using a combination of linear quadratic regulator (LQR) synthesis and numerical optimization techniques. The state and control weighing matrices (Q and R) are expressed in terms of structural parameters such as mass and stiffness. The design parameters are selected by numerical optimization so as to minimize the weight of the structure and to achieve the desired closed-loop eigenvalues. An illustrative example of the design of a two bar truss is presented.

On the solution of two-point linear differential eigenvalue problems. [numerical technique with application to Orr-Sommerfeld equation

NASA Technical Reports Server (NTRS)

Antar, B. N.

1976-01-01

A numerical technique is presented for locating the eigenvalues of two point linear differential eigenvalue problems. The technique is designed to search for complex eigenvalues belonging to complex operators. With this method, any domain of the complex eigenvalue plane could be scanned and the eigenvalues within it, if any, located. For an application of the method, the eigenvalues of the Orr-Sommerfeld equation of the plane Poiseuille flow are determined within a specified portion of the c-plane. The eigenvalues for alpha = 1 and R = 10,000 are tabulated and compared for accuracy with existing solutions.

True logarithmic amplification of frequency clock in SS-OCT for calibration

PubMed Central

Liu, Bin; Azimi, Ehsan; Brezinski, Mark E.

2011-01-01

With swept source optical coherence tomography (SS-OCT), imprecise signal calibration prevents optimal imaging of biological tissues such as coronary artery. This work demonstrates an approach using a true logarithmic amplifier to precondition the clock signal, with the effort to minimize the noises and phase errors for optimal calibration. This method was validated and tested with a high-speed SS-OCT. The experimental results manifest its superior ability on optimization of the calibration and improvement of the imaging performance. Particularly, this hardware-based approach is suitable for real-time calibration in a high-speed system where computation time is constrained. PMID:21698036

Optimal port-based teleportation

NASA Astrophysics Data System (ADS)

Mozrzymas, Marek; Studziński, Michał; Strelchuk, Sergii; Horodecki, Michał

2018-05-01

Deterministic port-based teleportation (dPBT) protocol is a scheme where a quantum state is guaranteed to be transferred to another system without unitary correction. We characterise the best achievable performance of the dPBT when both the resource state and the measurement is optimised. Surprisingly, the best possible fidelity for an arbitrary number of ports and dimension of the teleported state is given by the largest eigenvalue of a particular matrix—Teleportation Matrix. It encodes the relationship between a certain set of Young diagrams and emerges as the optimal solution to the relevant semidefinite programme.

Quadratic partial eigenvalue assignment in large-scale stochastic dynamic systems for resilient and economic design

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

Das, Sonjoy; Goswami, Kundan; Datta, Biswa N.

2014-12-10

Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this workmore » for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.« less

Observer-Pattern Modeling and Slow-Scale Bifurcation Analysis of Two-Stage Boost Inverters

NASA Astrophysics Data System (ADS)

Zhang, Hao; Wan, Xiaojin; Li, Weijie; Ding, Honghui; Yi, Chuanzhi

2017-06-01

This paper deals with modeling and bifurcation analysis of two-stage Boost inverters. Since the effect of the nonlinear interactions between source-stage converter and load-stage inverter causes the “hidden” second-harmonic current at the input of the downstream H-bridge inverter, an observer-pattern modeling method is proposed by removing time variance originating from both fundamental frequency and hidden second harmonics in the derived averaged equations. Based on the proposed observer-pattern model, the underlying mechanism of slow-scale instability behavior is uncovered with the help of eigenvalue analysis method. Then eigenvalue sensitivity analysis is used to select some key system parameters of two-stage Boost inverter, and some behavior boundaries are given to provide some design-oriented information for optimizing the circuit. Finally, these theoretical results are verified by numerical simulations and circuit experiment.

Krein signature for instability of PT-symmetric states

NASA Astrophysics Data System (ADS)

Chernyavsky, Alexander; Pelinovsky, Dmitry E.

2018-05-01

Krein quantity is introduced for isolated neutrally stable eigenvalues associated with the stationary states in the PT-symmetric nonlinear Schrödinger equation. Krein quantity is real and nonzero for simple eigenvalues but it vanishes if two simple eigenvalues coalesce into a defective eigenvalue. A necessary condition for bifurcation of unstable eigenvalues from the defective eigenvalue is proved. This condition requires the two simple eigenvalues before the coalescence point to have opposite Krein signatures. The theory is illustrated with several numerical examples motivated by recent publications in physics literature.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

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...

Extensions to PIFCGT: Multirate output feedback and optimal disturbance suppression

NASA Technical Reports Server (NTRS)

Broussard, J. R.

1986-01-01

New control synthesis procedures for digital flight control systems were developed. The theoretical developments are the solution to the problem of optimal disturbance suppression in the presence of windshear. Control synthesis is accomplished using a linear quadratic cost function, the command generator tracker for trajectory following and the proportional-integral-filter control structure for practical implementation. Extensions are made to the optimal output feedback algorithm for computing feedback gains so that the multirate and optimal disturbance control designs are computed and compared for the advanced transport operating system (ATOPS). The performance of the designs is demonstrated by closed-loop poles, frequency domain multiinput sigma and eigenvalue plots and detailed nonlinear 6-DOF aircraft simulations in the terminal area in the presence of windshear.

Simultaneous analysis and design

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1984-01-01

Optimization techniques are increasingly being used for performing nonlinear structural analysis. The development of element by element (EBE) preconditioned conjugate gradient (CG) techniques is expected to extend this trend to linear analysis. Under these circumstances the structural design problem can be viewed as a nested optimization problem. There are computational benefits to treating this nested problem as a large single optimization problem. The response variables (such as displacements) and the structural parameters are all treated as design variables in a unified formulation which performs simultaneously the design and analysis. Two examples are used for demonstration. A seventy-two bar truss is optimized subject to linear stress constraints and a wing box structure is optimized subject to nonlinear collapse constraints. Both examples show substantial computational savings with the unified approach as compared to the traditional nested approach.

Optimization of Sensing and Feedback Control for Vibration/Flutter of Rotating Disk by PZT Actuators via Air Coupled Pressure

PubMed Central

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin’s discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations. PMID:22163788

Optimization of sensing and feedback control for vibration/flutter of rotating disk by PZT actuators via air coupled pressure.

PubMed

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin's discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations.

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 and matrix-vector product evaluation, as well as block preconditioning techniques that preserve the modularity between subproblems. The monolithic solution method is applied to problems with varying degrees of fluid-structural coupling, as well as a wing span optimization study. The monolithic solution algorithm typically requires 20%-70% less computing time than its partitioned counterpart. This advantage increases with increasing wing flexibility. The performance of the monolithic solution method is also much less sensitive to the choice of the solution parameter.

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

Linear-scaling time-dependent density-functional theory beyond the Tamm-Dancoff approximation: Obtaining efficiency and accuracy with in situ optimised local orbitals

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

Zuehlsdorff, T. J., E-mail: tjz21@cam.ac.uk; Payne, M. C.; Hine, N. D. M.

2015-11-28

We present a solution of the full time-dependent density-functional theory (TDDFT) eigenvalue equation in the linear response formalism exhibiting a linear-scaling computational complexity with system size, without relying on the simplifying Tamm-Dancoff approximation (TDA). The implementation relies on representing the occupied and unoccupied subspaces with two different sets of in situ optimised localised functions, yielding a very compact and efficient representation of the transition density matrix of the excitation with the accuracy associated with a systematic basis set. The TDDFT eigenvalue equation is solved using a preconditioned conjugate gradient algorithm that is very memory-efficient. The algorithm is validated on amore » small test molecule and a good agreement with results obtained from standard quantum chemistry packages is found, with the preconditioner yielding a significant improvement in convergence rates. The method developed in this work is then used to reproduce experimental results of the absorption spectrum of bacteriochlorophyll in an organic solvent, where it is demonstrated that the TDA fails to reproduce the main features of the low energy spectrum, while the full TDDFT equation yields results in good qualitative agreement with experimental data. Furthermore, the need for explicitly including parts of the solvent into the TDDFT calculations is highlighted, making the treatment of large system sizes necessary that are well within reach of the capabilities of the algorithm introduced here. Finally, the linear-scaling properties of the algorithm are demonstrated by computing the lowest excitation energy of bacteriochlorophyll in solution. The largest systems considered in this work are of the same order of magnitude as a variety of widely studied pigment-protein complexes, opening up the possibility of studying their properties without having to resort to any semiclassical approximations to parts of the protein environment.« less

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

NASA Astrophysics Data System (ADS)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.

Structure preserving parallel algorithms for solving the Bethe–Salpeter eigenvalue problem

DOE PAGES

Shao, Meiyue; da Jornada, Felipe H.; Yang, Chao; ...

2015-10-02

The Bethe–Salpeter eigenvalue problem is a dense structured eigenvalue problem arising from discretized Bethe–Salpeter equation in the context of computing exciton energies and states. A computational challenge is that at least half of the eigenvalues and the associated eigenvectors are desired in practice. In this paper, we establish the equivalence between Bethe–Salpeter eigenvalue problems and real Hamiltonian eigenvalue problems. Based on theoretical analysis, structure preserving algorithms for a class of Bethe–Salpeter eigenvalue problems are proposed. We also show that for this class of problems all eigenvalues obtained from the Tamm–Dancoff approximation are overestimated. In order to solve large scale problemsmore » of practical interest, we discuss parallel implementations of our algorithms targeting distributed memory systems. Finally, several numerical examples are presented to demonstrate the efficiency and accuracy of our algorithms.« 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.

Goal-based h-adaptivity of the 1-D diamond difference discrete ordinate method

NASA Astrophysics Data System (ADS)

Jeffers, R. S.; Kópházi, J.; Eaton, M. D.; Févotte, F.; Hülsemann, F.; Ragusa, J.

2017-04-01

The quantity of interest (QoI) associated with a solution of a partial differential equation (PDE) is not, in general, the solution itself, but a functional of the solution. Dual weighted residual (DWR) error estimators are one way of providing an estimate of the error in the QoI resulting from the discretisation of the PDE. This paper aims to provide an estimate of the error in the QoI due to the spatial discretisation, where the discretisation scheme being used is the diamond difference (DD) method in space and discrete ordinate (SN) method in angle. The QoI are reaction rates in detectors and the value of the eigenvalue (Keff) for 1-D fixed source and eigenvalue (Keff criticality) neutron transport problems respectively. Local values of the DWR over individual cells are used as error indicators for goal-based mesh refinement, which aims to give an optimal mesh for a given QoI.

Approximate equiangular tight frames for compressed sensing and CDMA applications

NASA Astrophysics Data System (ADS)

Tsiligianni, Evaggelia; Kondi, Lisimachos P.; Katsaggelos, Aggelos K.

2017-12-01

Performance guarantees for recovery algorithms employed in sparse representations, and compressed sensing highlights the importance of incoherence. Optimal bounds of incoherence are attained by equiangular unit norm tight frames (ETFs). Although ETFs are important in many applications, they do not exist for all dimensions, while their construction has been proven extremely difficult. In this paper, we construct frames that are close to ETFs. According to results from frame and graph theory, the existence of an ETF depends on the existence of its signature matrix, that is, a symmetric matrix with certain structure and spectrum consisting of two distinct eigenvalues. We view the construction of a signature matrix as an inverse eigenvalue problem and propose a method that produces frames of any dimensions that are close to ETFs. Due to the achieved equiangularity property, the so obtained frames can be employed as spreading sequences in synchronous code-division multiple access (s-CDMA) systems, besides compressed sensing.

Minimizing the stochasticity of halos in large-scale structure surveys

NASA Astrophysics Data System (ADS)

Hamaus, Nico; Seljak, Uroš; Desjacques, Vincent; Smith, Robert E.; Baldauf, Tobias

2010-08-01

In recent work (Seljak, Hamaus, and Desjacques 2009) it was found that weighting central halo galaxies by halo mass can significantly suppress their stochasticity relative to the dark matter, well below the Poisson model expectation. This is useful for constraining relations between galaxies and the dark matter, such as the galaxy bias, especially in situations where sampling variance errors can be eliminated. In this paper we extend this study with the goal of finding the optimal mass-dependent halo weighting. We use N-body simulations to perform a general analysis of halo stochasticity and its dependence on halo mass. We investigate the stochasticity matrix, defined as Cij≡⟨(δi-biδm)(δj-bjδm)⟩, where δm is the dark matter overdensity in Fourier space, δi the halo overdensity of the i-th halo mass bin, and bi the corresponding halo bias. In contrast to the Poisson model predictions we detect nonvanishing correlations between different mass bins. We also find the diagonal terms to be sub-Poissonian for the highest-mass halos. The diagonalization of this matrix results in one large and one low eigenvalue, with the remaining eigenvalues close to the Poisson prediction 1/n¯, where n¯ is the mean halo number density. The eigenmode with the lowest eigenvalue contains most of the information and the corresponding eigenvector provides an optimal weighting function to minimize the stochasticity between halos and dark matter. We find this optimal weighting function to match linear mass weighting at high masses, while at the low-mass end the weights approach a constant whose value depends on the low-mass cut in the halo mass function. This weighting further suppresses the stochasticity as compared to the previously explored mass weighting. Finally, we employ the halo model to derive the stochasticity matrix and the scale-dependent bias from an analytical perspective. It is remarkably successful in reproducing our numerical results and predicts that the stochasticity between halos and the dark matter can be reduced further when going to halo masses lower than we can resolve in current simulations.

Local fisheries management at the Swedish coast: biological and social preconditions.

PubMed

Bruckmeier, Karl; Neuman, Erik

2005-03-01

Most of the Swedish coastal fisheries are not sustainable from either a social, economic or ecological point of view. We propose the introduction of local fisheries management (LFM) as a tool for restructuring the present large-scale management system in order to achieve sustainability. To implement LFM two questions need to be answered: How to distribute the resource fish among different resource user groups? How to restructure present fisheries management to meet the criteria of sustainability? Starting from these questions we describe possible forms of LFM for Swedish coastal fishery supported by recent research. The biological and social preconditions for restructuring fisheries management are derived from an analysis of the ecological and managerial situation in Swedish fishery. Three types of LFM--owner based, user based, and community based management--are analyzed with regard to the tasks to be carried outin LFM, the roles of management groups, and the definition and optimal size of management areas.

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.

Integrated Sensing Processor, Phase 2

DTIC Science & Technology

2005-12-01

performance analysis for several baseline classifiers including neural nets, linear classifiers, and kNN classifiers. Use of CCDR as a preprocessing step...below the level of the benchmark non-linear classifier for this problem ( kNN ). Furthermore, the CCDR preconditioned kNN achieved a 10% improvement over...the benchmark kNN without CCDR. Finally, we found an important connection between intrinsic dimension estimation via entropic graphs and the optimal

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

Comparison of scalar measures used in magnetic resonance diffusion tensor imaging.

PubMed

Bahn, M M

1999-07-01

The tensors derived from diffusion tensor imaging describe complex diffusion in tissues. However, it is difficult to compare tensors directly or to produce images that contain all of the information of the tensor. Therefore, it is convenient to produce scalar measures that extract desired aspects of the tensor. These measures map the three-dimensional eigenvalues of the diffusion tensor into scalar values. The measures impose an order on eigenvalue space. Many invariant scalar measures have been introduced in the literature. In the present manuscript, a general approach for producing invariant scalar measures is introduced. Because it is often difficult to determine in clinical practice which of the many measures is best to apply to a given situation, two formalisms are introduced for the presentation, definition, and comparison of measures applied to eigenvalues: (1) normalized eigenvalue space, and (2) parametric eigenvalue transformation plots. All of the anisotropy information contained in the three eigenvalues can be retained and displayed in a two-dimensional plot, the normalized eigenvalue plot. An example is given of how to determine the best measure to use for a given situation by superimposing isometric contour lines from various anisotropy measures on plots of actual measured eigenvalue data points. Parametric eigenvalue transformation plots allow comparison of how different measures impose order on normalized eigenvalue space to determine whether the measures are equivalent and how the measures differ. These formalisms facilitate the comparison of scalar invariant measures for diffusion tensor imaging. Normalized eigenvalue space allows presentation of eigenvalue anisotropy information. Copyright 1999 Academic Press.

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 glycogen per se does not cause the protection of preconditioning.

Laparoscopic ischemic conditioning of the stomach increases neovascularization of the gastric conduit in patients undergoing esophagectomy for cancer.

PubMed

Pham, Thai H; Melton, Shelby D; McLaren, Patrick J; Mokdad, Ali A; Huerta, Sergio; Wang, David H; Perry, Kyle A; Hardaker, Hope L; Dolan, James P

2017-09-01

Gastric ischemic preconditioning has been proposed to improve blood flow and reduce the incidence of anastomotic complications following esophagectomy with gastric pull-up. This study aimed to evaluate the effect of prolonged ischemic preconditioning on the degree of neovascularization in the distal gastric conduit at the time of esophagectomy. A retrospective review of a prospectively maintained database identified 30 patients who underwent esophagectomy. The patients were divided into three groups: control (no preconditioning, n = 9), partial (short gastric vessel ligation only, n = 8), and complete ischemic preconditioning (left and short gastric vessel ligation, n = 13). Microvessel counts were assessed, using immunohistologic analysis to determine the degree of neovascularization at the distal gastric margin. The groups did not differ in age, gender, BMI, pathologic stage, or cancer subtype. Ischemic preconditioning durations were 163 ± 156 days for partial ischemic preconditioning, compared to 95 ± 50 days for complete ischemic preconditioning (P = 0.2). Immunohistologic analysis demonstrated an increase in microvessel counts of 29% following partial ischemic preconditioning (P = 0.3) and 67% after complete ischemic preconditioning (P < 0.0001), compared to controls. Our study indicates that prolonged ischemic preconditioning is safe and does not interfere with subsequent esophagectomy. Complete ischemic preconditioning increased neovascularization in the distal gastric conduit. © 2017 Wiley Periodicals, Inc.

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 impact on anesthetic preconditioning and subsequent ischemic outcomes in the brain. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

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.

Large computer simulations on elastic networks: Small eigenvalues and eigenvalue spectra of the Kirchhoff matrix

NASA Astrophysics Data System (ADS)

Shy, L. Y.; Eichinger, B. E.

1989-05-01

Computer simulations of the formation of trifunctional and tetrafunctional polydimethyl-siloxane networks that are crosslinked by condensation of telechelic chains with multifunctional crosslinking agents have been carried out on systems containing up to 1.05×106 chains. Eigenvalue spectra of Kirchhoff matrices for these networks have been evaluated at two levels of approximation: (1) inclusion of all midchain modes, and (2) suppression of midchain modes. By use of the recursion method of Haydock and Nex, we have been able to effectively diagonalize matrices with 730 498 rows and columns without actually constructing matrices of this size. The small eigenvalues have been computed by use of the Lanczos algorithm. We demonstrate the following results: (1) The smallest eigenvalues (with chain modes suppressed) vary as μ-2/3 for sufficiently large μ, where μ is the number of junctions in the network; (2) the eigenvalue spectra of the Kirchhoff matrices are well described by McKay's theory for random regular graphs in the range of the larger eigenvalues, but there are significant departures in the region of small eigenvalues where computed spectra have many more small eigenvalues than random regular graphs; (3) the smallest eigenvalues vary as n-1.78 where n is the number of Rouse beads in the chains that comprise the network. Computations are done for both monodisperse and polydisperse chain length distributions. Large eigenvalues associated with localized motion of the junctions are found as predicted by theory. The relationship between the small eigenvalues and the equilibrium modulus of elasticity is discussed, as is the relationship between viscoelasticity and the band edge of the spectrum.

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.

Optimization of Closed Loop Eigenvalues: Maneuvering, Vibration Control, and Structure/Control Design Iteration for Flexible Spacecraft.

DTIC Science & Technology

1986-05-31

Nonlinear Feedback Control 8-16 for Spacecraft Attitude Maneuvers" 2. " Spacecraft Attitude Control Using 17-35... nonlinear state feedback control laws are developed for space- craft attitude control using the Euler parameters and conjugate angular momenta. Time... Nonlinear Feedback Control for Spacecraft Attitude Maneuvers," to appear in AIAA J. of Guidance, Control, and Dynamics, (AIAA Paper No. 83-2230-CP,

Column Subset Selection, Matrix Factorization, and Eigenvalue Optimization

DTIC Science & Technology

2008-07-01

Pietsch and Grothendieck, which are regarded as basic instruments in modern functional analysis [Pis86]. • The methods for computing these... Pietsch factorization and the maxcut semi- definite program [GW95]. 1.2. Overview. We focus on the algorithmic version of the Kashin–Tzafriri theorem...will see that the desired subset is exposed by factoring the random submatrix. This factorization, which was invented by Pietsch , is regarded as a basic

Sequential design of discrete linear quadratic regulators via optimal root-locus techniques

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Yates, Robert E.; Ganesan, Sekar

1989-01-01

A sequential method employing classical root-locus techniques has been developed in order to determine the quadratic weighting matrices and discrete linear quadratic regulators of multivariable control systems. At each recursive step, an intermediate unity rank state-weighting matrix that contains some invariant eigenvectors of that open-loop matrix is assigned, and an intermediate characteristic equation of the closed-loop system containing the invariant eigenvalues is created.

A proposed method for enhanced eigen-pair extraction using finite element methods: Theory and application

NASA Technical Reports Server (NTRS)

Jara-Almonte, J.; Mitchell, L. D.

1988-01-01

The paper covers two distinct parts: theory and application. The goal of this work was the reduction of model size with an increase in eigenvalue/vector accuracy. This method is ideal for the condensation of large truss- or beam-type structures. The theoretical approach involves the conversion of a continuum transfer matrix beam element into an 'Exact' dynamic stiffness element. This formulation is implemented in a finite element environment. This results in the need to solve a transcendental eigenvalue problem. Once the eigenvalue is determined the eigenvectors can be reconstructed with any desired spatial precision. No discretization limitations are imposed on the reconstruction. The results of such a combined finite element and transfer matrix formulation is a much smaller FEM eigenvalue problem. This formulation has the ability to extract higher eigenvalues as easily and as accurately as lower eigenvalues. Moreover, one can extract many more eigenvalues/vectors from the model than the number of degrees of freedom in the FEM formulation. Typically, the number of eigenvalues accurately extractable via the 'Exact' element method are at least 8 times the number of degrees of freedom. In contrast, the FEM usually extracts one accurate (within 5 percent) eigenvalue for each 3-4 degrees of freedom. The 'Exact' element results in a 20-30 improvement in the number of accurately extractable eigenvalues and eigenvectors.

Efficient dense blur map estimation for automatic 2D-to-3D conversion

NASA Astrophysics Data System (ADS)

Vosters, L. P. J.; de Haan, G.

2012-03-01

Focus is an important depth cue for 2D-to-3D conversion of low depth-of-field images and video. However, focus can be only reliably estimated on edges. Therefore, Bea et al. [1] first proposed an optimization based approach to propagate focus to non-edge image portions, for single image focus editing. While their approach produces accurate dense blur maps, the computational complexity and memory requirements for solving the resulting sparse linear system with standard multigrid or (multilevel) preconditioning techniques, are infeasible within the stringent requirements of the consumer electronics and broadcast industry. In this paper we propose fast, efficient, low latency, line scanning based focus propagation, which mitigates the need for complex multigrid or (multilevel) preconditioning techniques. In addition we propose facial blur compensation to compensate for false shading edges that cause incorrect blur estimates in people's faces. In general shading leads to incorrect focus estimates, which may lead to unnatural 3D and visual discomfort. Since visual attention mostly tends to faces, our solution solves the most distracting errors. A subjective assessment by paired comparison on a set of challenging low-depth-of-field images shows that the proposed approach achieves equal 3D image quality as optimization based approaches, and that facial blur compensation results in a significant improvement.

Modal interaction in linear dynamic systems near degenerate modes

NASA Technical Reports Server (NTRS)

Afolabi, D.

1991-01-01

In various problems in structural dynamics, the eigenvalues of a linear system depend on a characteristic parameter of the system. Under certain conditions, two eigenvalues of the system approach each other as the characteristic parameter is varied, leading to modal interaction. In a system with conservative coupling, the two eigenvalues eventually repel each other, leading to the curve veering effect. In a system with nonconservative coupling, the eigenvalues continue to attract each other, eventually colliding, leading to eigenvalue degeneracy. Modal interaction is studied in linear systems with conservative and nonconservative coupling using singularity theory, sometimes known as catastrophe theory. The main result is this: eigenvalue degeneracy is a cause of instability; in systems with conservative coupling, it induces only geometric instability, whereas in systems with nonconservative coupling, eigenvalue degeneracy induces both geometric and elastic instability. Illustrative examples of mechanical systems are given.

[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.

Transmission eigenvalues

NASA Astrophysics Data System (ADS)

Cakoni, Fioralba; Haddar, Houssem

2013-10-01

In inverse scattering theory, transmission eigenvalues can be seen as the extension of the notion of resonant frequencies for impenetrable objects to the case of penetrable dielectrics. The transmission eigenvalue problem is a relatively late arrival to the spectral theory of partial differential equations. Its first appearance was in 1986 in a paper by Kirsch who was investigating the denseness of far-field patterns for scattering solutions of the Helmholtz equation or, in more modern terminology, the injectivity of the far-field operator [1]. The paper of Kirsch was soon followed by a more systematic study by Colton and Monk in the context of developing the dual space method for solving the inverse scattering problem for acoustic waves in an inhomogeneous medium [2]. In this paper they showed that for a spherically stratified media transmission eigenvalues existed and formed a discrete set. Numerical examples were also given showing that in principle transmission eigenvalues could be determined from the far-field data. This first period of interest in transmission eigenvalues was concluded with papers by Colton et al in 1989 [3] and Rynne and Sleeman in 1991 [4] showing that for an inhomogeneous medium (not necessarily spherically stratified) transmission eigenvalues, if they existed, formed a discrete set. For the next seventeen years transmission eigenvalues were ignored. This was mainly due to the fact that, with the introduction of various sampling methods to determine the shape of an inhomogeneous medium from far-field data, transmission eigenvalues were something to be avoided and hence the fact that transmission eigenvalues formed at most a discrete set was deemed to be sufficient. In addition, questions related to the existence of transmission eigenvalues or the structure of associated eigenvectors were recognized as being particularly difficult due to the nonlinearity of the eigenvalue problem and the special structure of the associated transmission eigenvalue problem. The need to answer these questions became important after a series of papers by Cakoni et al [5], and Cakoni et al [6] suggesting that these transmission eigenvalues could be used to obtain qualitative information about the material properties of the scattering object from far-field data. The first answer to the existence of transmission eigenvalues in the general case was given in 2008 when Päivärinta and Sylvester showed the existence of transmission eigenvalues for the index of refraction sufficiently large [7] followed in 2010 by the paper of Cakoni et al who removed the size restriction on the index of refraction [8]. More importantly, in the latter it was shown that transmission eigenvalues yielded qualitative information on the material properties of the scattering object and Cakoni et al established in [9] that transmission eigenvalues could be determined from the Tikhonov regularized solution of the far-field equation. Since the appearance of these papers there has been an explosion of interest in the transmission eigenvalue problem (we refer the reader to our recent survey paper [10] for a detailed account of the developments in this field up to 2012) and the papers in this special issue are representative of the myriad directions that this research has taken. Indeed, we are happy to see that many open theoretical and numerical questions raised in [10] have been answered (totally or partially) in the contributions of this special issue: the existence of transmission eigenvalues with minimal assumptions on the contrast, the numerical evaluation of transmission eigenvalues, the inverse spectral problem, applications to non-destructive testing, etc. In addition to these topics, many other new investigations and research directions have been proposed as we shall see in the brief content summary below. A number of papers in this special issue are concerned with the question of existence of transmission eigenvalues and the structure of the associated transmission eigenfunctions. The three papers by respectively Robbiano [11], Blasten and Päivärinta [12], and Lakshtanov and Vainberg [13] provide new complementary results on the existence of transmission eigenvalues for the scalar problem under weak assumptions on the (possibly complex valued) refractive index that mainly stipulates that the contrast does not change sign on the boundary. It is interesting here to see three different new methods to obtain these results. On the other hand, the paper by Bonnet-Ben Dhia and Chesnel [14] addresses the Fredholm properties of the interior transmission problem when the contrast changes sign on the boundary, exhibiting cases where this property fails. Using more standard approaches, the existence and structure of transmission eigenvalues are analyzed in the paper by Delbary [15] for the case of frequency dependent materials in the context of Maxwell's equations, whereas the paper by Vesalainen [16] initiates the study of the transmission eigenvalue problem in unbounded domains by considering the transmission eigenvalues for Schrödinger equation with non-compactly supported potential. The paper by Monk and Selgas [17] addresses the case where the dielectric is mounted on a perfect conductor and provides some numerical examples of the localization of associated eigenvalues using the linear sampling method. A series of papers then addresses the question of localization of transmission eigenvalues and the associated inverse spectral problem for spherically stratified media. More specifically, the paper by Colton and Leung [18] provides new results on complex transmission eigenvalues and a new proof for uniqueness of a solution to the inverse spectral problem, whereas the paper by Sylvester [19] provides sharp results on how to locate all the transmission eigenvalues associated with angular independent eigenfunctions when the index of refraction is constant. The paper by Gintides and Pallikarakis [20] investigates an iterative least square method to identify the spherically stratified index of refraction from transmission eigenvalues. On the characterization of transmission eigenvalues in terms of far-field measurements, a promising new result is obtained by Kirsch and Lechleiter [21] showing how one can identify the transmission eigenvalues using the eigenvalues of the scattering operator which are available in terms of measured scattering data. In the paper by Kleefeld [22], an accurate method for computing transmission eigenvalues based on a surface integral formulation of the interior transmission problem and numerical methods for nonlinear eigenvalue problems is proposed and numerically validated for the scalar problem in three dimensions. On the other hand, the paper by Sun and Xu [23] investigates the computation of transmission eigenvalues for Maxwell's equations using a standard iterative method associated with a variational formulation of the interior transmission problem with an emphasis on the effect of anisotropy on transmission eigenvalues. From the perspective of using transmission eigenvalues in non-destructive testing, the paper by Cakoni and Moskow [24] investigates the asymptotic behavior of transmission eigenvalues with respect to small inhomogeneities. The paper by Nakamura and Wang [25] investigates the linear sampling method for the time dependent heat equation and analyses the interior transmission problem associated with this equation. Finally, in the paper by Finch and Hickmann [26], the spectrum of the interior transmission problem is related to the unique determination of the acoustic properties of a body in thermoacoustic imaging. We hope that this collection of papers will stimulate further research in the rapidly growing area of transmission eigenvalues and inverse scattering theory.

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

Optimal linear-quadratic control of coupled parabolic-hyperbolic PDEs

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2017-10-01

This paper focuses on the optimal control design for a system of coupled parabolic-hypebolic partial differential equations by using the infinite-dimensional state-space description and the corresponding operator Riccati equation. Some dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the linear-quadratic (LQ)-optimal control problem. A state LQ-feedback operator is computed by solving the operator Riccati equation, which is converted into a set of algebraic and differential Riccati equations, thanks to the eigenvalues and the eigenvectors of the parabolic operator. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ-optimal controller designed in the early portion of the paper is implemented for the original nonlinear model. Numerical simulations are performed to show the controller performances.

New sets of eigenvalues in inverse scattering for inhomogeneous media and their determination from scattering data

NASA Astrophysics Data System (ADS)

Audibert, Lorenzo; Cakoni, Fioralba; Haddar, Houssem

2017-12-01

In this paper we develop a general mathematical framework to determine interior eigenvalues from a knowledge of the modified far field operator associated with an unknown (anisotropic) inhomogeneity. The modified far field operator is obtained by subtracting from the measured far field operator the computed far field operator corresponding to a well-posed scattering problem depending on one (possibly complex) parameter. Injectivity of this modified far field operator is related to an appropriate eigenvalue problem whose eigenvalues can be determined from the scattering data, and thus can be used to obtain information about material properties of the unknown inhomogeneity. We discuss here two examples of such modification leading to a Steklov eigenvalue problem, and a new type of the transmission eigenvalue problem. We present some numerical examples demonstrating the viability of our method for determining the interior eigenvalues form far field data.

Use of SCALE Continuous-Energy Monte Carlo Tools for Eigenvalue Sensitivity Coefficient Calculations

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

Perfetti, Christopher M; Rearden, Bradley T

2013-01-01

The TSUNAMI code within the SCALE code system makes use of eigenvalue sensitivity coefficients for an extensive number of criticality safety applications, such as quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating sensitivity coefficients in continuous-energy (CE) Monte Carlo applications. The CLUTCH and Iterated Fission Probability (IFP) eigenvalue sensitivity methods were recently implemented in themore » CE KENO framework to generate the capability for TSUNAMI-3D to perform eigenvalue sensitivity calculations in continuous-energy applications. This work explores the improvements in accuracy that can be gained in eigenvalue and eigenvalue sensitivity calculations through the use of the SCALE CE KENO and CE TSUNAMI continuous-energy Monte Carlo tools as compared to multigroup tools. The CE KENO and CE TSUNAMI tools were used to analyze two difficult models of critical benchmarks, and produced eigenvalue and eigenvalue sensitivity coefficient results that showed a marked improvement in accuracy. The CLUTCH sensitivity method in particular excelled in terms of efficiency and computational memory requirements.« less

Redundant interferometric calibration as a complex optimization problem

NASA Astrophysics Data System (ADS)

Grobler, T. L.; Bernardi, G.; Kenyon, J. S.; Parsons, A. R.; Smirnov, O. M.

2018-05-01

Observations of the redshifted 21 cm line from the epoch of reionization have recently motivated the construction of low-frequency radio arrays with highly redundant configurations. These configurations provide an alternative calibration strategy - `redundant calibration' - and boost sensitivity on specific spatial scales. In this paper, we formulate calibration of redundant interferometric arrays as a complex optimization problem. We solve this optimization problem via the Levenberg-Marquardt algorithm. This calibration approach is more robust to initial conditions than current algorithms and, by leveraging an approximate matrix inversion, allows for further optimization and an efficient implementation (`redundant STEFCAL'). We also investigated using the preconditioned conjugate gradient method as an alternative to the approximate matrix inverse, but found that its computational performance is not competitive with respect to `redundant STEFCAL'. The efficient implementation of this new algorithm is made publicly available.

Weak value amplification considered harmful

NASA Astrophysics Data System (ADS)

Ferrie, Christopher; Combes, Joshua

2014-03-01

We show using statistically rigorous arguments that the technique of weak value amplification does not perform better than standard statistical techniques for the tasks of parameter estimation and signal detection. We show that using all data and considering the joint distribution of all measurement outcomes yields the optimal estimator. Moreover, we show estimation using the maximum likelihood technique with weak values as small as possible produces better performance for quantum metrology. In doing so, we identify the optimal experimental arrangement to be the one which reveals the maximal eigenvalue of the square of system observables. We also show these conclusions do not change in the presence of technical noise.

Gain selection method and model for coupled propulsion and airframe systems

NASA Technical Reports Server (NTRS)

Murphy, P. C.

1982-01-01

A longitudinal model is formulated for an advanced fighter from three subsystem models: the inlet, the engine, and the airframe. Notable interaction is found in the coupled system. A procedure, based on eigenvalue sensitivities, is presented which indicates the importance of the feedback gains to the optimal solution. This allows ineffectual gains to be eliminated; thus, hardware and expense may be saved in the realization of the physical controller.

The Shock and Vibration Digest, Volume 18, Number 3

DTIC Science & Technology

1986-03-01

Linear Distributed Parameter Des., Proc. Intl. Symp., 11th ONR Naval Struc. Systems by Shifted Legendre Polynomial Func- Mech. Symp., Tucson, AZ, pp...University, Atlanta, Georgia nonlinear problems with elementary algebra . It J. Sound Vib., 102 (2), pp 247-257 (Sept 22, uses i = -1, the Pascal’s...eigenvalues specified. The optimal avoid failure due to resonance under the action control problem of a linear distributed parameter 0School of Mechanical

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.

Eigenvalues of the Wentzell-Laplace operator and of the fourth order Steklov problems

NASA Astrophysics Data System (ADS)

Xia, Changyu; Wang, Qiaoling

2018-05-01

We prove a sharp upper bound and a lower bound for the first nonzero eigenvalue of the Wentzell-Laplace operator on compact manifolds with boundary and an isoperimetric inequality for the same eigenvalue in the case where the manifold is a bounded domain in a Euclidean space. We study some fourth order Steklov problems and obtain isoperimetric upper bound for the first eigenvalue of them. We also find all the eigenvalues and eigenfunctions for two kind of fourth order Steklov problems on a Euclidean ball.

Finite-difference solution of the compressible stability eigenvalue problem

NASA Technical Reports Server (NTRS)

Malik, M. R.

1982-01-01

A compressible stability analysis computer code is developed. The code uses a matrix finite difference method for local eigenvalue solution when a good guess for the eigenvalue is available and is significantly more computationally efficient than the commonly used initial value approach. The local eigenvalue search procedure also results in eigenfunctions and, at little extra work, group velocities. A globally convergent eigenvalue procedure is also developed which may be used when no guess for the eigenvalue is available. The global problem is formulated in such a way that no unstable spurious modes appear so that the method is suitable for use in a black box stability code. Sample stability calculations are presented for the boundary layer profiles of a Laminar Flow Control (LFC) swept wing.

Coral thermal tolerance: tuning gene expression to resist thermal stress.

PubMed

Bellantuono, Anthony J; Granados-Cifuentes, Camila; Miller, David J; Hoegh-Guldberg, Ove; Rodriguez-Lanetty, Mauricio

2012-01-01

The acclimatization capacity of corals is a critical consideration in the persistence of coral reefs under stresses imposed by global climate change. The stress history of corals plays a role in subsequent response to heat stress, but the transcriptomic changes associated with these plastic changes have not been previously explored. In order to identify host transcriptomic changes associated with acquired thermal tolerance in the scleractinian coral Acropora millepora, corals preconditioned to a sub-lethal temperature of 3°C below bleaching threshold temperature were compared to both non-preconditioned corals and untreated controls using a cDNA microarray platform. After eight days of hyperthermal challenge, conditions under which non-preconditioned corals bleached and preconditioned corals (thermal-tolerant) maintained Symbiodinium density, a clear differentiation in the transcriptional profiles was revealed among the condition examined. Among these changes, nine differentially expressed genes separated preconditioned corals from non-preconditioned corals, with 42 genes differentially expressed between control and preconditioned treatments, and 70 genes between non-preconditioned corals and controls. Differentially expressed genes included components of an apoptotic signaling cascade, which suggest the inhibition of apoptosis in preconditioned corals. Additionally, lectins and genes involved in response to oxidative stress were also detected. One dominant pattern was the apparent tuning of gene expression observed between preconditioned and non-preconditioned treatments; that is, differences in expression magnitude were more apparent than differences in the identity of genes differentially expressed. Our work revealed a transcriptomic signature underlying the tolerance associated with coral thermal history, and suggests that understanding the molecular mechanisms behind physiological acclimatization would be critical for the modeling of reefs in impending climate change scenarios.

Coral Thermal Tolerance: Tuning Gene Expression to Resist Thermal Stress

PubMed Central

Bellantuono, Anthony J.; Granados-Cifuentes, Camila; Miller, David J.; Hoegh-Guldberg, Ove; Rodriguez-Lanetty, Mauricio

2012-01-01

The acclimatization capacity of corals is a critical consideration in the persistence of coral reefs under stresses imposed by global climate change. The stress history of corals plays a role in subsequent response to heat stress, but the transcriptomic changes associated with these plastic changes have not been previously explored. In order to identify host transcriptomic changes associated with acquired thermal tolerance in the scleractinian coral Acropora millepora, corals preconditioned to a sub-lethal temperature of 3°C below bleaching threshold temperature were compared to both non-preconditioned corals and untreated controls using a cDNA microarray platform. After eight days of hyperthermal challenge, conditions under which non-preconditioned corals bleached and preconditioned corals (thermal-tolerant) maintained Symbiodinium density, a clear differentiation in the transcriptional profiles was revealed among the condition examined. Among these changes, nine differentially expressed genes separated preconditioned corals from non-preconditioned corals, with 42 genes differentially expressed between control and preconditioned treatments, and 70 genes between non-preconditioned corals and controls. Differentially expressed genes included components of an apoptotic signaling cascade, which suggest the inhibition of apoptosis in preconditioned corals. Additionally, lectins and genes involved in response to oxidative stress were also detected. One dominant pattern was the apparent tuning of gene expression observed between preconditioned and non-preconditioned treatments; that is, differences in expression magnitude were more apparent than differences in the identity of genes differentially expressed. Our work revealed a transcriptomic signature underlying the tolerance associated with coral thermal history, and suggests that understanding the molecular mechanisms behind physiological acclimatization would be critical for the modeling of reefs in impending climate change scenarios. PMID:23226355

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 against MPTP/MPP{sup +}.« less

Determination of spatial scale of response unit for WASSI-C eco–hydrological model—a case study on the upper Zagunao River watershed of China

Treesearch

Ning Liu; Peng-Sen Sun; Shi-Rong Liu; Ge Sun

2013-01-01

Main publication is written in Chinese.Aims: Optimal spatial scale of hydrological response unit (HRU) is a precondition for eco-hydrological modeling as it is essential to improve accuracy. Our objective was to evaluate the spatial scale of HRU for application of the WASSSI-C model.Methods: We determined the best HRU scale for the eco-...

Efficient parallel resolution of the simplified transport equations in mixed-dual formulation

NASA Astrophysics Data System (ADS)

Barrault, M.; Lathuilière, B.; Ramet, P.; Roman, J.

2011-03-01

A reactivity computation consists of computing the highest eigenvalue of a generalized eigenvalue problem, for which an inverse power algorithm is commonly used. Very fine modelizations are difficult to treat for our sequential solver, based on the simplified transport equations, in terms of memory consumption and computational time. A first implementation of a Lagrangian based domain decomposition method brings to a poor parallel efficiency because of an increase in the power iterations [1]. In order to obtain a high parallel efficiency, we improve the parallelization scheme by changing the location of the loop over the subdomains in the overall algorithm and by benefiting from the characteristics of the Raviart-Thomas finite element. The new parallel algorithm still allows us to locally adapt the numerical scheme (mesh, finite element order). However, it can be significantly optimized for the matching grid case. The good behavior of the new parallelization scheme is demonstrated for the matching grid case on several hundreds of nodes for computations based on a pin-by-pin discretization.

Experimental Validation of Model Updating and Damage Detection via Eigenvalue Sensitivity Methods with Artificial Boundary Conditions

DTIC Science & Technology

2017-09-01

VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY CONDITIONS by Matthew D. Bouwense...VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY CONDITIONS 5. FUNDING NUMBERS 6. AUTHOR...unlimited. EXPERIMENTAL VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY

Type I and Type II Error Rates and Overall Accuracy of the Revised Parallel Analysis Method for Determining the Number of Factors

ERIC Educational Resources Information Center

Green, Samuel B.; Thompson, Marilyn S.; Levy, Roy; Lo, Wen-Juo

2015-01-01

Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the "k"th eigenvalue for sample data to the "k"th eigenvalue for generated data sets, conditioned on"k"-…

EvArnoldi: A New Algorithm for Large-Scale Eigenvalue Problems.

PubMed

Tal-Ezer, Hillel

2016-05-19

Eigenvalues and eigenvectors are an essential theme in numerical linear algebra. Their study is mainly motivated by their high importance in a wide range of applications. Knowledge of eigenvalues is essential in quantum molecular science. Solutions of the Schrödinger equation for the electrons composing the molecule are the basis of electronic structure theory. Electronic eigenvalues compose the potential energy surfaces for nuclear motion. The eigenvectors allow calculation of diople transition matrix elements, the core of spectroscopy. The vibrational dynamics molecule also requires knowledge of the eigenvalues of the vibrational Hamiltonian. Typically in these problems, the dimension of Hilbert space is huge. Practically, only a small subset of eigenvalues is required. In this paper, we present a highly efficient algorithm, named EvArnoldi, for solving the large-scale eigenvalues problem. The algorithm, in its basic formulation, is mathematically equivalent to ARPACK ( Sorensen , D. C. Implicitly Restarted Arnoldi/Lanczos Methods for Large Scale Eigenvalue Calculations ; Springer , 1997 ; Lehoucq , R. B. ; Sorensen , D. C. SIAM Journal on Matrix Analysis and Applications 1996 , 17 , 789 ; Calvetti , D. ; Reichel , L. ; Sorensen , D. C. Electronic Transactions on Numerical Analysis 1994 , 2 , 21 ) (or Eigs of Matlab) but significantly simpler.

Eigenvalue density of cross-correlations in Sri Lankan financial market

NASA Astrophysics Data System (ADS)

Nilantha, K. G. D. R.; Ranasinghe; Malmini, P. K. C.

2007-05-01

We apply the universal properties with Gaussian orthogonal ensemble (GOE) of random matrices namely spectral properties, distribution of eigenvalues, eigenvalue spacing predicted by random matrix theory (RMT) to compare cross-correlation matrix estimators from emerging market data. The daily stock prices of the Sri Lankan All share price index and Milanka price index from August 2004 to March 2005 were analyzed. Most eigenvalues in the spectrum of the cross-correlation matrix of stock price changes agree with the universal predictions of RMT. We find that the cross-correlation matrix satisfies the universal properties of the GOE of real symmetric random matrices. The eigen distribution follows the RMT predictions in the bulk but there are some deviations at the large eigenvalues. The nearest-neighbor spacing and the next nearest-neighbor spacing of the eigenvalues were examined and found that they follow the universality of GOE. RMT with deterministic correlations found that each eigenvalue from deterministic correlations is observed at values, which are repelled from the bulk distribution.

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

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.

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

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.

Calculation of transmission probability by solving an eigenvalue problem

NASA Astrophysics Data System (ADS)

Bubin, Sergiy; Varga, Kálmán

2010-11-01

The electron transmission probability in nanodevices is calculated by solving an eigenvalue problem. The eigenvalues are the transmission probabilities and the number of nonzero eigenvalues is equal to the number of open quantum transmission eigenchannels. The number of open eigenchannels is typically a few dozen at most, thus the computational cost amounts to the calculation of a few outer eigenvalues of a complex Hermitian matrix (the transmission matrix). The method is implemented on a real space grid basis providing an alternative to localized atomic orbital based quantum transport calculations. Numerical examples are presented to illustrate the efficiency of the method.

Analysis of the Hessian for Aerodynamic Optimization: Inviscid Flow

NASA Technical Reports Server (NTRS)

Arian, Eyal; Ta'asan, Shlomo

1996-01-01

In this paper we analyze inviscid aerodynamic shape optimization problems governed by the full potential and the Euler equations in two and three dimensions. The analysis indicates that minimization of pressure dependent cost functions results in Hessians whose eigenvalue distributions are identical for the full potential and the Euler equations. However the optimization problems in two and three dimensions are inherently different. While the two dimensional optimization problems are well-posed the three dimensional ones are ill-posed. Oscillations in the shape up to the smallest scale allowed by the design space can develop in the direction perpendicular to the flow, implying that a regularization is required. A natural choice of such a regularization is derived. The analysis also gives an estimate of the Hessian's condition number which implies that the problems at hand are ill-conditioned. Infinite dimensional approximations for the Hessians are constructed and preconditioners for gradient based methods are derived from these approximate Hessians.

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.

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.

Weighted SGD for ℓ p Regression with Randomized Preconditioning.

PubMed

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W

2016-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems-e.g., ℓ 2 and ℓ 1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓ p regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓ p solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ 1 regression with size n by d , pwSGD returns an approximate solution with ε relative error in the objective value in (log n ·nnz( A )+poly( d )/ ε 2 ) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ 2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in (log n ·nnz( A )+poly( d ) log(1/ ε )/ ε ) time. We show that for unconstrained ℓ 2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε , high dimension n and low dimension d satisfy d ≥ 1/ ε and n ≥ d 2 / ε . We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10 -3 , more quickly.

Weighted SGD for ℓp Regression with Randomized Preconditioning*

PubMed Central

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W.

2018-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems—e.g., ℓ2 and ℓ1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓp regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓp solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ1 regression with size n by d, pwSGD returns an approximate solution with ε relative error in the objective value in 𝒪(log n·nnz(A)+poly(d)/ε2) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in 𝒪(log n·nnz(A)+poly(d) log(1/ε)/ε) time. We show that for unconstrained ℓ2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε, high dimension n and low dimension d satisfy d ≥ 1/ε and n ≥ d2/ε. We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10−3, more quickly. PMID:29782626

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

PubMed

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.

A numerical projection technique for large-scale eigenvalue problems

NASA Astrophysics Data System (ADS)

Gamillscheg, Ralf; Haase, Gundolf; von der Linden, Wolfgang

2011-10-01

We present a new numerical technique to solve large-scale eigenvalue problems. It is based on the projection technique, used in strongly correlated quantum many-body systems, where first an effective approximate model of smaller complexity is constructed by projecting out high energy degrees of freedom and in turn solving the resulting model by some standard eigenvalue solver. Here we introduce a generalization of this idea, where both steps are performed numerically and which in contrast to the standard projection technique converges in principle to the exact eigenvalues. This approach is not just applicable to eigenvalue problems encountered in many-body systems but also in other areas of research that result in large-scale eigenvalue problems for matrices which have, roughly speaking, mostly a pronounced dominant diagonal part. We will present detailed studies of the approach guided by two many-body models.

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 against a behavioral and cellular manifestation of neural damage.

Development of a generalized perturbation theory method for sensitivity analysis using continuous-energy Monte Carlo methods

DOE PAGES

Perfetti, Christopher M.; Rearden, Bradley T.

2016-03-01

The sensitivity and uncertainty analysis tools of the ORNL SCALE nuclear modeling and simulation code system that have been developed over the last decade have proven indispensable for numerous application and design studies for nuclear criticality safety and reactor physics. SCALE contains tools for analyzing the uncertainty in the eigenvalue of critical systems, but cannot quantify uncertainty in important neutronic parameters such as multigroup cross sections, fuel fission rates, activation rates, and neutron fluence rates with realistic three-dimensional Monte Carlo simulations. A more complete understanding of the sources of uncertainty in these design-limiting parameters could lead to improvements in processmore » optimization, reactor safety, and help inform regulators when setting operational safety margins. A novel approach for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was recently explored as academic research and has been found to accurately and rapidly calculate sensitivity coefficients in criticality safety applications. The work presented here describes a new method, known as the GEAR-MC method, which extends the CLUTCH theory for calculating eigenvalue sensitivity coefficients to enable sensitivity coefficient calculations and uncertainty analysis for a generalized set of neutronic responses using high-fidelity continuous-energy Monte Carlo calculations. Here, several criticality safety systems were examined to demonstrate proof of principle for the GEAR-MC method, and GEAR-MC was seen to produce response sensitivity coefficients that agreed well with reference direct perturbation sensitivity coefficients.« less

Eigenvalues of normalized Laplacian matrices of fractal trees and dendrimers: Analytical results and applications

NASA Astrophysics Data System (ADS)

Julaiti, Alafate; Wu, Bin; Zhang, Zhongzhi

2013-05-01

The eigenvalues of the normalized Laplacian matrix of a network play an important role in its structural and dynamical aspects associated with the network. In this paper, we study the spectra and their applications of normalized Laplacian matrices of a family of fractal trees and dendrimers modeled by Cayley trees, both of which are built in an iterative way. For the fractal trees, we apply the spectral decimation approach to determine analytically all the eigenvalues and their corresponding multiplicities, with the eigenvalues provided by a recursive relation governing the eigenvalues of networks at two successive generations. For Cayley trees, we show that all their eigenvalues can be obtained by computing the roots of several small-degree polynomials defined recursively. By using the relation between normalized Laplacian spectra and eigentime identity, we derive the explicit solution to the eigentime identity for random walks on the two treelike networks, the leading scalings of which follow quite different behaviors. In addition, we corroborate the obtained eigenvalues and their degeneracies through the link between them and the number of spanning trees.

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.

Approximation of the Newton Step by a Defect Correction Process

NASA Technical Reports Server (NTRS)

Arian, E.; Batterman, A.; Sachs, E. W.

1999-01-01

In this paper, an optimal control problem governed by a partial differential equation is considered. The Newton step for this system can be computed by solving a coupled system of equations. To do this efficiently with an iterative defect correction process, a modifying operator is introduced into the system. This operator is motivated by local mode analysis. The operator can be used also for preconditioning in Generalized Minimum Residual (GMRES). We give a detailed convergence analysis for the defect correction process and show the derivation of the modifying operator. Numerical tests are done on the small disturbance shape optimization problem in two dimensions for the defect correction process and for GMRES.

Toward Optimal Transport Networks

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Optimal exponential synchronization of general chaotic delayed neural networks: an LMI approach.

PubMed

Liu, Meiqin

2009-09-01

This paper investigates the optimal exponential synchronization problem of general chaotic neural networks with or without time delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. This general model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs) with or without delays. Using the drive-response concept, time-delay feedback controllers are designed to synchronize two identical chaotic neural networks as quickly as possible. The control design equations are shown to be a generalized eigenvalue problem (GEVP) which can be easily solved by various convex optimization algorithms to determine the optimal control law and the optimal exponential synchronization rate. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Multicomponent diffusion in basaltic melts at 1350 °C

NASA Astrophysics Data System (ADS)

Guo, Chenghuan; Zhang, Youxue

2018-05-01

Nine successful diffusion couple experiments were conducted in an 8-component SiO2-TiO2-Al2O3-FeO-MgO-CaO-Na2O-K2O system at ∼1350 °C and at 1 GPa, to study multicomponent diffusion in basaltic melts. At least 3 traverses were measured to obtain diffusion profiles for each experiment. Multicomponent diffusion matrix at 1350 °C was obtained by simultaneously fitting diffusion profiles of diffusion couple experiments. Furthermore, in order to better constrain the diffusion matrix and reconcile mineral dissolution data, mineral dissolution experiments in the literature and diffusion couple experiments from this study, were fit together. All features of diffusion profiles in both diffusion couple and mineral dissolution experiments were well reproduced by the diffusion matrix. Diffusion mechanism is inferred from eigenvectors of the diffusion matrix, and it shows that the diffusive exchange between network-formers SiO2 and Al2O3 is the slowest, the exchange of SiO2 with other oxide components is the second slowest with an eigenvalue that is only ∼10% larger, then the exchange between divalent oxide components and all the other oxide components is the third slowest with an eigenvalue that is twice the smallest eigenvalue, then the exchange of FeO + K2O with all the other oxide components is the fourth slowest with an eigenvalue that is 5 times the smallest eigenvalue, then the exchange of MgO with FeO + CaO is the third fastest with an eigenvalue that is 6.3 times the smallest eigenvalue, then the exchange of CaO + K2O with all the other oxide components is the second fastest with an eigenvalue that is 7.5 times the smallest eigenvalue, and the exchange of Na2O with all other oxide components is the fastest with an eigenvalue that is 31 times the smallest eigenvalue. The slowest and fastest eigenvectors are consistent with those for simpler systems in most literature. The obtained diffusion matrix was successfully applied to predict diffusion profiles during mineral dissolution in basaltic melts.

The Shock and Vibration Bulletin. Part 2. Vibration Analysis.

DTIC Science & Technology

1977-09-01

Spring, MD and J.C.S. Yang, University of Maryland, College Park, MD APPLICATION O LIGHT-INITIATED EXPLOSIVE FOR SIMULATING X -RAY BLOWOFF IMPULSE...0.785t to the free end. effectiveness being produced from the For a spring located at the free end poorest ( X /1=1) to the optimal location ( X /L=1...the eigenvalue coefficient ( X /L=0.785). Although accurate support varies from 1.875 for a null spring placement is imperative, the second mode rate to

Introduction to Numerical Methods

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

Schoonover, Joseph A.

2016-06-14

These are slides for a lecture for the Parallel Computing Summer Research Internship at the National Security Education Center. This gives an introduction to numerical methods. Repetitive algorithms are used to obtain approximate solutions to mathematical problems, using sorting, searching, root finding, optimization, interpolation, extrapolation, least squares regresion, Eigenvalue problems, ordinary differential equations, and partial differential equations. Many equations are shown. Discretizations allow us to approximate solutions to mathematical models of physical systems using a repetitive algorithm and introduce errors that can lead to numerical instabilities if we are not careful.

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 conclusions are drawn from the analysis of the structure of the non-GI errors and the associated corrections, with particular emphasis on their dependence on the preconditioning parameter. The GI preconditioned central-moment LB method is validated for a number of complex flow benchmark problems and its effectiveness to achieve convergence acceleration and improvement in accuracy is demonstrated.

Matrix-Free Polynomial-Based Nonlinear Least Squares Optimized Preconditioning and its Application to Discontinuous Galerkin Discretizations of the Euler Equations

DTIC Science & Technology

2015-06-01

cient parallel code for applying the operator. Our method constructs a polynomial preconditioner using a nonlinear least squares (NLLS) algorithm. We show...apply the underlying operator. Such a preconditioner can be very attractive in scenarios where one has a highly efficient parallel code for applying...repeatedly solve a large system of linear equations where one has an extremely fast parallel code for applying an underlying fixed linear operator

S4 solution of the transport equation for eigenvalues using Legendre polynomials

NASA Astrophysics Data System (ADS)

Öztürk, Hakan; Bülbül, Ahmet

2017-09-01

Numerical solution of the transport equation for monoenergetic neutrons scattered isotropically through the medium of a finite homogeneous slab is studied for the determination of the eigenvalues. After obtaining the discrete ordinates form of the transport equation, separated homogeneous and particular solutions are formed and then the eigenvalues are calculated using the Gauss-Legendre quadrature set. Then, the calculated eigenvalues for various values of the c0, the mean number of secondary neutrons per collision, are given in the tables.

Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1

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

SHAO, MEIYEU; YANG, CHAO

2017-04-25

The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.

Sturm-Liouville eigenproblems with an interior pole

NASA Technical Reports Server (NTRS)

Boyd, J. P.

1981-01-01

The eigenvalues and eigenfunctions of self-adjoint Sturm-Liouville problems with a simple pole on the interior of an interval are investigated. Three general theorems are proved, and it is shown that as n approaches infinity, the eigenfunctions more and more closely resemble those of an ordinary Sturm-Liouville problem. The low-order modes differ significantly from those of a nonsingular eigenproblem in that both eigenvalues and eigenfunctions are complex, and the eigenvalues for all small n may cluster about a common value in contrast to the widely separated eigenvalues of the corresponding nonsingular problem. In addition, the WKB is shown to be accurate for all n, and all eigenvalues of a normal one-dimensional Sturm-Liouville equation with nonperiodic boundary conditions are well separated.

Evaluation of the eigenvalue method in the solution of transient heat conduction problems

NASA Astrophysics Data System (ADS)

Landry, D. W.

1985-01-01

The eigenvalue method is evaluated to determine the advantages and disadvantages of the method as compared to fully explicit, fully implicit, and Crank-Nicolson methods. Time comparisons and accuracy comparisons are made in an effort to rank the eigenvalue method in relation to the comparison schemes. The eigenvalue method is used to solve the parabolic heat equation in multidimensions with transient temperatures. Extensions into three dimensions are made to determine the method's feasibility in handling large geometry problems requiring great numbers of internal mesh points. The eigenvalue method proves to be slightly better in accuracy than the comparison routines because of an exact treatment, as opposed to a numerical approximation, of the time derivative in the heat equation. It has the potential of being a very powerful routine in solving long transient type problems. The method is not well suited to finely meshed grid arrays or large regions because of the time and memory requirements necessary for calculating large sets of eigenvalues and eigenvectors.

Statistical properties of cross-correlation in the Korean stock market

NASA Astrophysics Data System (ADS)

Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

2011-01-01

We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

A comparison of matrix methods for calculating eigenvalues in acoustically lined ducts

NASA Technical Reports Server (NTRS)

Watson, W.; Lansing, D. L.

1976-01-01

Three approximate methods - finite differences, weighted residuals, and finite elements - were used to solve the eigenvalue problem which arises in finding the acoustic modes and propagation constants in an absorptively lined two-dimensional duct without airflow. The matrix equations derived for each of these methods were solved for the eigenvalues corresponding to various values of wall impedance. Two matrix orders, 20 x 20 and 40 x 40, were used. The cases considered included values of wall admittance for which exact eigenvalues were known and for which several nearly equal roots were present. Ten of the lower order eigenvalues obtained from the three approximate methods were compared with solutions calculated from the exact characteristic equation in order to make an assessment of the relative accuracy and reliability of the three methods. The best results were given by the finite element method using a cubic polynomial. Excellent accuracy was consistently obtained, even for nearly equal eigenvalues, by using a 20 x 20 order matrix.

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.

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.

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 Elsevier B.V. All rights reserved.

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.

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...

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

A new method of passive modifications for partial frequency assignment of general structures

NASA Astrophysics Data System (ADS)

Belotti, Roberto; Ouyang, Huajiang; Richiedei, Dario

2018-01-01

The assignment of a subset of natural frequencies to vibrating systems can be conveniently achieved by means of suitable structural modifications. It has been observed that such an approach usually leads to the undesired change of the unassigned natural frequencies, which is a phenomenon known as frequency spill-over. Such an issue has been dealt with in the literature only in simple specific cases. In this paper, a new and general method is proposed that aims to assign a subset of natural frequencies with low spill-over. The optimal structural modifications are determined through a three-step procedure that considers both the prescribed eigenvalues and the feasibility constraints, assuring that the obtained solution is physically realizable. The proposed method is therefore applicable to very general vibrating systems, such as those obtained through the finite element method. The numerical difficulties that may occur as a result of employing the method are also carefully addressed. Finally, the capabilities of the method are validated in three test-cases in which both lumped and distributed parameters are modified to obtain the desired eigenvalues.

Diagonally Implicit Runge-Kutta Methods for Ordinary Differential Equations. A Review

NASA Technical Reports Server (NTRS)

Kennedy, Christopher A.; Carpenter, Mark H.

2016-01-01

A review of diagonally implicit Runge-Kutta (DIRK) methods applied to rst-order ordinary di erential equations (ODEs) is undertaken. The goal of this review is to summarize the characteristics, assess the potential, and then design several nearly optimal, general purpose, DIRK-type methods. Over 20 important aspects of DIRKtype methods are reviewed. A design study is then conducted on DIRK-type methods having from two to seven implicit stages. From this, 15 schemes are selected for general purpose application. Testing of the 15 chosen methods is done on three singular perturbation problems. Based on the review of method characteristics, these methods focus on having a stage order of two, sti accuracy, L-stability, high quality embedded and dense-output methods, small magnitudes of the algebraic stability matrix eigenvalues, small values of aii, and small or vanishing values of the internal stability function for large eigenvalues of the Jacobian. Among the 15 new methods, ESDIRK4(3)6L[2]SA is recommended as a good default method for solving sti problems at moderate error tolerances.

Increasing the applicability of density functional theory. IV. Consequences of ionization-potential improved exchange-correlation potentials.

PubMed

Verma, Prakash; Bartlett, Rodney J

2014-05-14

This paper's objective is to create a "consistent" mean-field based Kohn-Sham (KS) density functional theory (DFT) meaning the functional should not only provide good total energy properties, but also the corresponding KS eigenvalues should be accurate approximations to the vertical ionization potentials (VIPs) of the molecule, as the latter condition attests to the viability of the exchange-correlation potential (VXC). None of the prominently used DFT approaches show these properties: the optimized effective potential VXC based ab initio dft does. A local, range-separated hybrid potential cam-QTP-00 is introduced as the basis for a "consistent" KS DFT approach. The computed VIPs as the negative of KS eigenvalue have a mean absolute error of 0.8 eV for an extensive set of molecule's electron ionizations, including the core. Barrier heights, equilibrium geometries, and magnetic properties obtained from the potential are in good agreement with experiment. A similar accuracy with less computational efforts can be achieved by using a non-variational global hybrid variant of the QTP-00 approach.

A low dimensional dynamical system for the wall layer

NASA Technical Reports Server (NTRS)

Aubry, N.; Keefe, L. R.

1987-01-01

Low dimensional dynamical systems which model a fully developed turbulent wall layer were derived.The model is based on the optimally fast convergent proper orthogonal decomposition, or Karhunen-Loeve expansion. This decomposition provides a set of eigenfunctions which are derived from the autocorrelation tensor at zero time lag. Via Galerkin projection, low dimensional sets of ordinary differential equations in time, for the coefficients of the expansion, were derived from the Navier-Stokes equations. The energy loss to the unresolved modes was modeled by an eddy viscosity representation, analogous to Heisenberg's spectral model. A set of eigenfunctions and eigenvalues were obtained from direct numerical simulation of a plane channel at a Reynolds number of 6600, based on the mean centerline velocity and the channel width flow and compared with previous work done by Herzog. Using the new eigenvalues and eigenfunctions, a new ten dimensional set of ordinary differential equations were derived using five non-zero cross-stream Fourier modes with a periodic length of 377 wall units. The dynamical system was integrated for a range of the eddy viscosity prameter alpha. This work is encouraging.

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.

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 the number of eigenvalues of the discrete one-dimensional Dirac operator with a complex potential

NASA Astrophysics Data System (ADS)

Hulko, Artem

2018-03-01

In this paper we define a one-dimensional discrete Dirac operator on Z . We study the eigenvalues of the Dirac operator with a complex potential. We obtain bounds on the total number of eigenvalues in the case where V decays exponentially at infinity. We also estimate the number of eigenvalues for the discrete Schrödinger operator with complex potential on Z . That is we extend the result obtained by Hulko (Bull Math Sci, to appear) to the whole Z.

An Eigenvalue Analysis of finite-difference approximations for hyperbolic IBVPs

NASA Technical Reports Server (NTRS)

Warming, Robert F.; Beam, Richard M.

1989-01-01

The eigenvalue spectrum associated with a linear finite-difference approximation plays a crucial role in the stability analysis and in the actual computational performance of the discrete approximation. The eigenvalue spectrum associated with the Lax-Wendroff scheme applied to a model hyperbolic equation was investigated. For an initial-boundary-value problem (IBVP) on a finite domain, the eigenvalue or normal mode analysis is analytically intractable. A study of auxiliary problems (Dirichlet and quarter-plane) leads to asymptotic estimates of the eigenvalue spectrum and to an identification of individual modes as either benign or unstable. The asymptotic analysis establishes an intuitive as well as quantitative connection between the algebraic tests in the theory of Gustafsson, Kreiss, and Sundstrom and Lax-Richtmyer L(sub 2) stability on a finite domain.

An eigenvalue localization set for tensors and its applications.

PubMed

Zhao, Jianxing; Sang, Caili

2017-01-01

A new eigenvalue localization set for tensors is given and proved to be tighter than those presented by Li et al . (Linear Algebra Appl. 481:36-53, 2015) and Huang et al . (J. Inequal. Appl. 2016:254, 2016). As an application of this set, new bounds for the minimum eigenvalue of [Formula: see text]-tensors are established and proved to be sharper than some known results. Compared with the results obtained by Huang et al ., the advantage of our results is that, without considering the selection of nonempty proper subsets S of [Formula: see text], we can obtain a tighter eigenvalue localization set for tensors and sharper bounds for the minimum eigenvalue of [Formula: see text]-tensors. Finally, numerical examples are given to verify the theoretical results.

SCALE Continuous-Energy Eigenvalue Sensitivity Coefficient Calculations

DOE PAGES

Perfetti, Christopher M.; Rearden, Bradley T.; Martin, William R.

2016-02-25

Sensitivity coefficients describe the fractional change in a system response that is induced by changes to system parameters and nuclear data. The Tools for Sensitivity and UNcertainty Analysis Methodology Implementation (TSUNAMI) code within the SCALE code system makes use of eigenvalue sensitivity coefficients for an extensive number of criticality safety applications, including quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the developmentmore » of a methodology for calculating sensitivity coefficients in continuous-energy (CE) Monte Carlo applications. The Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) and Iterated Fission Probability (IFP) eigenvalue sensitivity methods were recently implemented in the CE-KENO framework of the SCALE code system to enable TSUNAMI-3D to perform eigenvalue sensitivity calculations using continuous-energy Monte Carlo methods. This work provides a detailed description of the theory behind the CLUTCH method and describes in detail its implementation. This work explores the improvements in eigenvalue sensitivity coefficient accuracy that can be gained through the use of continuous-energy sensitivity methods and also compares several sensitivity methods in terms of computational efficiency and memory requirements.« less

Design of a New Concentration Series for the Orthogonal Sample Design Approach and Estimation of the Number of Reactions in Chemical Systems.

PubMed

Shi, Jiajia; Liu, Yuhai; Guo, Ran; Li, Xiaopei; He, Anqi; Gao, Yunlong; Wei, Yongju; Liu, Cuige; Zhao, Ying; Xu, Yizhuang; Noda, Isao; Wu, Jinguang

2015-11-01

A new concentration series is proposed for the construction of a two-dimensional (2D) synchronous spectrum for orthogonal sample design analysis to probe intermolecular interaction between solutes dissolved in the same solutions. The obtained 2D synchronous spectrum possesses the following two properties: (1) cross peaks in the 2D synchronous spectra can be used to reflect intermolecular interaction reliably, since interference portions that have nothing to do with intermolecular interaction are completely removed, and (2) the two-dimensional synchronous spectrum produced can effectively avoid accidental collinearity. Hence, the correct number of nonzero eigenvalues can be obtained so that the number of chemical reactions can be estimated. In a real chemical system, noise present in one-dimensional spectra may also produce nonzero eigenvalues. To get the correct number of chemical reactions, we classified nonzero eigenvalues into significant nonzero eigenvalues and insignificant nonzero eigenvalues. Significant nonzero eigenvalues can be identified by inspecting the pattern of the corresponding eigenvector with help of the Durbin-Watson statistic. As a result, the correct number of chemical reactions can be obtained from significant nonzero eigenvalues. This approach provides a solid basis to obtain insight into subtle spectral variations caused by intermolecular interaction.

Predictability of a Coupled Model of ENSO Using Singular Vector Analysis: Optimal Growth and Forecast Skill.

NASA Astrophysics Data System (ADS)

Xue, Yan

The optimal growth and its relationship with the forecast skill of the Zebiak and Cane model are studied using a simple statistical model best fit to the original nonlinear model and local linear tangent models about idealized climatic states (the mean background and ENSO cycles in a long model run), and the actual forecast states, including two sets of runs using two different initialization procedures. The seasonally varying Markov model best fit to a suite of 3-year forecasts in a reduced EOF space (18 EOFs) fits the original nonlinear model reasonably well and has comparable or better forecast skill. The initial error growth in a linear evolution operator A is governed by the eigenvalues of A^{T}A, and the square roots of eigenvalues and eigenvectors of A^{T}A are named singular values and singular vectors. One dominant growing singular vector is found, and the optimal 6 month growth rate is largest for a (boreal) spring start and smallest for a fall start. Most of the variation in the optimal growth rate of the two forecasts is seasonal, attributable to the seasonal variations in the mean background, except that in the cold events it is substantially suppressed. It is found that the mean background (zero anomaly) is the most unstable state, and the "forecast IC states" are more unstable than the "coupled model states". One dominant growing singular vector is found, characterized by north-south and east -west dipoles, convergent winds on the equator in the eastern Pacific and a deepened thermocline in the whole equatorial belt. This singular vector is insensitive to initial time and optimization time, but its final pattern is a strong function of initial states. The ENSO system is inherently unpredictable for the dominant singular vector can amplify 5-fold to 24-fold in 6 months and evolve into the large scales characteristic of ENSO. However, the inherent ENSO predictability is only a secondary factor, while the mismatches between the model and data is a primary factor controlling the current forecast skill.

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...

Corruption of coronary collateral growth in metabolic syndrome: Role of oxidative stress

PubMed Central

Pung, Yuh Fen; Chilian, William M

2010-01-01

The myocardium adapts to ischemic insults in a variety of ways. One adaptation is the phenomenon of acute preconditioning, which can greatly ameliorate ischemic damage. However, this effect wanes within a few hours and does not confer chronic protection. A more chronic adaptation is the so-called second window of preconditioning, which enables protection for a few days. The most potent adaptation invoked by the myocardium to minimize the effects of ischemia is the growth of blood vessels in the heart, angiogenesis and arteriogenesis (collateral growth), which prevent the development of ischemia by enabling flow to a jeopardized region of the heart. This brief review examines the mechanisms underlying angiogenesis and arteriogenesis in the heart. The concept of a redox window, which is an optimal redox state for vascular growth, is discussed along with signaling mechanisms invoked by reactive oxygen species that are stimulated during ischemia-reperfusion. Finally, the review discusses of some of the pathologies, especially the metabolic syndrome, that negatively affect collateral growth through the corruption of redox signaling processes. PMID:21191543

Fast algorithms for chiral fermions in 2 dimensions

NASA Astrophysics Data System (ADS)

Hyka (Xhako), Dafina; Osmanaj (Zeqirllari), Rudina

2018-03-01

In lattice QCD simulations the formulation of the theory in lattice should be chiral in order that symmetry breaking happens dynamically from interactions. In order to guarantee this symmetry on the lattice one uses overlap and domain wall fermions. On the other hand high computational cost of lattice QCD simulations with overlap or domain wall fermions remains a major obstacle of research in the field of elementary particles. We have developed the preconditioned GMRESR algorithm as fast inverting algorithm for chiral fermions in U(1) lattice gauge theory. In this algorithm we used the geometric multigrid idea along the extra dimension.The main result of this work is that the preconditioned GMRESR is capable to accelerate the convergence 2 to 12 times faster than the other optimal algorithms (SHUMR) for different coupling constant and lattice 32x32. Also, in this paper we tested it for larger lattice size 64x64. From the results of simulations we can see that our algorithm is faster than SHUMR. This is a very promising result that this algorithm can be adapted also in 4 dimension.

Modern control techniques in active flutter suppression using a control moment gyro

NASA Technical Reports Server (NTRS)

Buchek, P. M.

1974-01-01

Development of organized synthesis techniques, using concepts of modern control theory was studied for the design of active flutter suppression systems for two and three-dimensional lifting surfaces, utilizing a control moment gyro (CMG) to generate the required control torques. Incompressible flow theory is assumed, with the unsteady aerodynamic forces and moments for arbitrary airfoil motion obtained by using the convolution integral based on Wagner's indicial lift function. Linear optimal control theory is applied to find particular optimal sets of gain values which minimize a quadratic performance function. The closed loop system's response to impulsive gust disturbances and the resulting control power requirements are investigated, and the system eigenvalues necessary to minimize the maximum value of control power are determined.

Noisy covariance matrices and portfolio optimization

NASA Astrophysics Data System (ADS)

Pafka, S.; Kondor, I.

2002-05-01

According to recent findings [#!bouchaud!#,#!stanley!#], empirical covariance matrices deduced from financial return series contain such a high amount of noise that, apart from a few large eigenvalues and the corresponding eigenvectors, their structure can essentially be regarded as random. In [#!bouchaud!#], e.g., it is reported that about 94% of the spectrum of these matrices can be fitted by that of a random matrix drawn from an appropriately chosen ensemble. In view of the fundamental role of covariance matrices in the theory of portfolio optimization as well as in industry-wide risk management practices, we analyze the possible implications of this effect. Simulation experiments with matrices having a structure such as described in [#!bouchaud!#,#!stanley!#] lead us to the conclusion that in the context of the classical portfolio problem (minimizing the portfolio variance under linear constraints) noise has relatively little effect. To leading order the solutions are determined by the stable, large eigenvalues, and the displacement of the solution (measured in variance) due to noise is rather small: depending on the size of the portfolio and on the length of the time series, it is of the order of 5 to 15%. The picture is completely different, however, if we attempt to minimize the variance under non-linear constraints, like those that arise e.g. in the problem of margin accounts or in international capital adequacy regulation. In these problems the presence of noise leads to a serious instability and a high degree of degeneracy of the solutions.

An Extremal Eigenvalue Problem for a Two-Phase Conductor in a Ball

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

Conca, Carlos; Mahadevan, Rajesh; Sanz, Leon

2009-10-15

The pioneering works of Murat and Tartar (Topics in the mathematical modeling of composite materials. PNLDE 31. Birkhaeuser, Basel, 1997) go a long way in showing, in general, that problems of optimal design may not admit solutions if microstructural designs are excluded from consideration. Therefore, assuming, tactilely, that the problem of minimizing the first eigenvalue of a two-phase conducting material with the conducting phases to be distributed in a fixed proportion in a given domain has no true solution in general domains, Cox and Lipton only study conditions for an optimal microstructural design (Cox and Lipton in Arch. Ration. Mech.more » Anal. 136:101-117, 1996). Although, the problem in one dimension has a solution (cf. Krein in AMS Transl. Ser. 2(1):163-187, 1955) and, in higher dimensions, the problem set in a ball can be deduced to have a radially symmetric solution (cf. Alvino et al. in Nonlinear Anal. TMA 13(2):185-220, 1989), these existence results have been regarded so far as being exceptional owing to complete symmetry. It is still not clear why the same problem in domains with partial symmetry should fail to have a solution which does not develop microstructure and respecting the symmetry of the domain. We hope to revive interest in this question by giving a new proof of the result in a ball using a simpler symmetrization result from Alvino and Trombetti (J. Math. Anal. Appl. 94:328-337, 1983)« less

Body measurements and the variability of sitting postures at preschool age as preconditions for an optimal adjustment of chairs and tables.

PubMed

Voigt, Andrea; Greil, Holle

2009-03-01

Preschool age is a biological stage of intensive longitudinal growth with high plasticity of the growing body and of body postures. It is the period where children learn to persist in a sitting posture for a longer time and to use furniture like chairs or other body supporting systems. The growing body shows a special sensitivity for the manifestation of inappropriate postures. In this study the development of body measurements and sitting behaviour of preschool age children is investigated as a precondition for an optimal adjustment of seats and desks to the growing body. Accordingly to the instructions of Knussmann (1988) and Jiirgens (1988) 6 body measurements were taken from 122 German children aged 3 to 7 years from Potsdam, Province Brandenburg. Additionally, every child was videotaped for 10 minutes while crayoning in a sitting position of its own choice using a chair and a desk. To analyse the tapes, the software Noldus Observer was used and examined, picture by picture, to define the different types of sitting postures as well as the duration of persistence in a posture and the number of changes of postures. The used chairs and desks were also measured. Furthermore, the data of the furniture guideline DIN ISO 5970 (DIN, 1981), which regulates the dimensions of furniture for sitting in educational institutions, were compared with the results of the body measurements and with the dimensions of the furniture used by the children.

Towards quality indicators for assertive outreach programmes for severely impaired substance abusers: concept mapping with Dutch experts.

PubMed

Roeg, Diana; van de Goor, Ien; Garretsen, Henk

2005-06-01

We investigated the concept of 'quality of assertive outreach programmes for severely impaired substance abusers' with the aim of developing a conceptual framework as the basis for an assessment instrument. We held a concept-mapping session with 13 experts in 2003. Fifty measurable elements of quality were mentioned and rated in terms of relative importance on a Likert-type response scale. Subsequently, the experts grouped the statements that were similar in content. The resulting concept map and additional interpretation made up the final quality framework. SETTING/STUDY PARTICIPANTS: Theoretical sampling was used to select Dutch managers, team leaders, and service providers from different assertive outreach delivery systems for substance abusers. Variation in both perspective and region was reflected in the sample. Nine aspects of quality were formulated: preconditions for care, preconditions for service providers' work, relationship to regular care, service providers' activities and goals, service providers' skills, the role of repression, optimal care for the client, goals of assertive outreach, and nuisance reduction to society. Each aspect was presented using a selection of measurable elements. According to the experts, optimal assertive outreach depends on a broad range of aspects that were later classified in three regions: structure, process, and outcomes. Saturation of the elements has not been proved so far. Nevertheless, it is promising that the framework's regions are supported by theory and that it is largely in accordance with clients' perspectives on assertive community treatment.

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...

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...

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...

Pseudo-compressibility methods for the incompressible flow equations

NASA Technical Reports Server (NTRS)

Turkel, Eli; Arnone, A.

1993-01-01

Preconditioning methods to accelerate convergence to a steady state for the incompressible fluid dynamics equations are considered. The analysis relies on the inviscid equations. The preconditioning consists of a matrix multiplying the time derivatives. Thus the steady state of the preconditioned system is the same as the steady state of the original system. The method is compared to other types of pseudo-compressibility. For finite difference methods preconditioning can change and improve the steady state solutions. An application to viscous flow around a cascade with a non-periodic mesh is presented.

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

Accurate Valence Ionization Energies from Kohn-Sham Eigenvalues with the Help of Potential Adjustors.

PubMed

Thierbach, Adrian; Neiss, Christian; Gallandi, Lukas; Marom, Noa; Körzdörfer, Thomas; Görling, Andreas

2017-10-10

An accurate yet computationally very efficient and formally well justified approach to calculate molecular ionization potentials is presented and tested. The first as well as higher ionization potentials are obtained as the negatives of the Kohn-Sham eigenvalues of the neutral molecule after adjusting the eigenvalues by a recently [ Görling Phys. Rev. B 2015 , 91 , 245120 ] introduced potential adjustor for exchange-correlation potentials. Technically the method is very simple. Besides a Kohn-Sham calculation of the neutral molecule, only a second Kohn-Sham calculation of the cation is required. The eigenvalue spectrum of the neutral molecule is shifted such that the negative of the eigenvalue of the highest occupied molecular orbital equals the energy difference of the total electronic energies of the cation minus the neutral molecule. For the first ionization potential this simply amounts to a ΔSCF calculation. Then, the higher ionization potentials are obtained as the negatives of the correspondingly shifted Kohn-Sham eigenvalues. Importantly, this shift of the Kohn-Sham eigenvalue spectrum is not just ad hoc. In fact, it is formally necessary for the physically correct energetic adjustment of the eigenvalue spectrum as it results from ensemble density-functional theory. An analogous approach for electron affinities is equally well obtained and justified. To illustrate the practical benefits of the approach, we calculate the valence ionization energies of test sets of small- and medium-sized molecules and photoelectron spectra of medium-sized electron acceptor molecules using a typical semilocal (PBE) and two typical global hybrid functionals (B3LYP and PBE0). The potential adjusted B3LYP and PBE0 eigenvalues yield valence ionization potentials that are in very good agreement with experimental values, reaching an accuracy that is as good as the best G 0 W 0 methods, however, at much lower computational costs. The potential adjusted PBE eigenvalues result in somewhat less accurate ionization energies, which, however, are almost as accurate as those obtained from the most commonly used G 0 W 0 variants.

Cucheb: A GPU implementation of the filtered Lanczos procedure

NASA Astrophysics Data System (ADS)

Aurentz, Jared L.; Kalantzis, Vassilis; Saad, Yousef

2017-11-01

This paper describes the software package Cucheb, a GPU implementation of the filtered Lanczos procedure for the solution of large sparse symmetric eigenvalue problems. The filtered Lanczos procedure uses a carefully chosen polynomial spectral transformation to accelerate convergence of the Lanczos method when computing eigenvalues within a desired interval. This method has proven particularly effective for eigenvalue problems that arise in electronic structure calculations and density functional theory. We compare our implementation against an equivalent CPU implementation and show that using the GPU can reduce the computation time by more than a factor of 10. Program Summary Program title: Cucheb Program Files doi:http://dx.doi.org/10.17632/rjr9tzchmh.1 Licensing provisions: MIT Programming language: CUDA C/C++ Nature of problem: Electronic structure calculations require the computation of all eigenvalue-eigenvector pairs of a symmetric matrix that lie inside a user-defined real interval. Solution method: To compute all the eigenvalues within a given interval a polynomial spectral transformation is constructed that maps the desired eigenvalues of the original matrix to the exterior of the spectrum of the transformed matrix. The Lanczos method is then used to compute the desired eigenvectors of the transformed matrix, which are then used to recover the desired eigenvalues of the original matrix. The bulk of the operations are executed in parallel using a graphics processing unit (GPU). Runtime: Variable, depending on the number of eigenvalues sought and the size and sparsity of the matrix. Additional comments: Cucheb is compatible with CUDA Toolkit v7.0 or greater.

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

Bai, Zhaojun; Yang, Chao

What is common among electronic structure calculation, design of MEMS devices, vibrational analysis of high speed railways, and simulation of the electromagnetic field of a particle accelerator? The answer: they all require solving large scale nonlinear eigenvalue problems. In fact, these are just a handful of examples in which solving nonlinear eigenvalue problems accurately and efficiently is becoming increasingly important. Recognizing the importance of this class of problems, an invited minisymposium dedicated to nonlinear eigenvalue problems was held at the 2005 SIAM Annual Meeting. The purpose of the minisymposium was to bring together numerical analysts and application scientists to showcasemore » some of the cutting edge results from both communities and to discuss the challenges they are still facing. The minisymposium consisted of eight talks divided into two sessions. The first three talks focused on a type of nonlinear eigenvalue problem arising from electronic structure calculations. In this type of problem, the matrix Hamiltonian H depends, in a non-trivial way, on the set of eigenvectors X to be computed. The invariant subspace spanned by these eigenvectors also minimizes a total energy function that is highly nonlinear with respect to X on a manifold defined by a set of orthonormality constraints. In other applications, the nonlinearity of the matrix eigenvalue problem is restricted to the dependency of the matrix on the eigenvalues to be computed. These problems are often called polynomial or rational eigenvalue problems In the second session, Christian Mehl from Technical University of Berlin described numerical techniques for solving a special type of polynomial eigenvalue problem arising from vibration analysis of rail tracks excited by high-speed trains.« less

Semi-analytical Karhunen-Loeve representation of irregular waves based on the prolate spheroidal wave functions

NASA Astrophysics Data System (ADS)

Lee, Gibbeum; Cho, Yeunwoo

2018-01-01

A new semi-analytical approach is presented to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of direct numerical approach to this matrix eigenvalue problem, which may suffer from the computational inaccuracy for big data, a pair of integral and differential equations are considered, which are related to the so-called prolate spheroidal wave functions (PSWF). First, the PSWF is expressed as a summation of a small number of the analytical Legendre functions. After substituting them into the PSWF differential equation, a much smaller size matrix eigenvalue problem is obtained than the direct numerical K-L matrix eigenvalue problem. By solving this with a minimal numerical effort, the PSWF and the associated eigenvalue of the PSWF differential equation are obtained. Then, the eigenvalue of the PSWF integral equation is analytically expressed by the functional values of the PSWF and the eigenvalues obtained in the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data such as ordinary irregular waves. It is found that, with the same accuracy, the required memory size of the present method is smaller than that of the direct numerical K-L representation and the computation time of the present method is shorter than that of the semi-analytical method based on the sinusoidal functions.

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics

PubMed Central

Zou, Weiyao; Burns, Stephen A.

2012-01-01

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. PMID:22441462

LQR-Based Optimal Distributed Cooperative Design for Linear Discrete-Time Multiagent Systems.

PubMed

Zhang, Huaguang; Feng, Tao; Liang, Hongjing; Luo, Yanhong

2017-03-01

In this paper, a novel linear quadratic regulator (LQR)-based optimal distributed cooperative design method is developed for synchronization control of general linear discrete-time multiagent systems on a fixed, directed graph. Sufficient conditions are derived for synchronization, which restrict the graph eigenvalues into a bounded circular region in the complex plane. The synchronizing speed issue is also considered, and it turns out that the synchronizing region reduces as the synchronizing speed becomes faster. To obtain more desirable synchronizing capacity, the weighting matrices are selected by sufficiently utilizing the guaranteed gain margin of the optimal regulators. Based on the developed LQR-based cooperative design framework, an approximate dynamic programming technique is successfully introduced to overcome the (partially or completely) model-free cooperative design for linear multiagent systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design methods.

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics.

PubMed

Zou, Weiyao; Burns, Stephen A

2012-03-20

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. © 2012 Optical Society of America

On the placement of active members in adaptive truss structures for vibration control

NASA Technical Reports Server (NTRS)

Lu, L.-Y.; Utku, S.; Wada, B. K.

1992-01-01

The problem of optimal placement of active members which are used for vibration control in adaptive truss structures is investigated. The control scheme is based on the method of eigenvalue assignment as a means of shaping the transient response of the controlled adaptive structures, and the minimization of required control action is considered as the optimization criterion. To this end, a performance index which measures the control strokes of active members is formulated in an efficient way. In order to reduce the computation burden, particularly for the case where the locations of active members have to be selected from a large set of available sites, several heuristic searching schemes are proposed for obtaining the near-optimal locations. The proposed schemes significantly reduce the computational complexity of placing multiple active members to the order of that when a single active member is placed.

Contributions on Optimizing Approximations in the Study of Melting and Solidification Processes That Occur in Processing by Electro-Erosion

NASA Astrophysics Data System (ADS)

Potra, F. L.; Potra, T.; Soporan, V. F.

We propose two optimization methods of the processes which appear in EDM (Electrical Discharge Machining). First refers to the introduction of a new function approximating the thermal flux energy in EDM machine. Classical researches approximate this energy with the Gauss' function. In the case of unconventional technology the Gauss' bell became null only for r → +∞, where r is the radius of crater produced by EDM. We introduce a cubic spline regression which descends to zero at the crater's boundary. In the second optimization we propose modifications in technologies' work regarding the displacement of the tool electrode to the piece electrode such that the material melting to be realized in optimal time and the feeding speed with dielectric liquid regarding the solidification of the expulsed material. This we realize using the FAHP algorithm based on the theory of eigenvalues and eigenvectors, which lead to mean values of best approximation. [6

Optimal Frequency-Domain System Realization with Weighting

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Maghami, Peiman G.

1999-01-01

Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation uses a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. Three different approaches are introduced to fine-tune the model using nonlinear programming methods to minimize the desired cost function. The first method uses an eigenvalue assignment technique to reassign a subset of system poles to improve the identified model. The second method deals with the model in the real Schur or modal form, reassigns a subset of system poles, and adjusts the columns (rows) of the input (output) influence matrix using a nonlinear optimizer. The third method also optimizes a subset of poles, but the input and output influence matrices are refined at every optimization step through least-squares procedures.

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

Determining Optimal Location and Numbers of Sample Transects for Characterization of UXO Sites

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

BILISOLY, ROGER L.; MCKENNA, SEAN A.

2003-01-01

Previous work on sample design has been focused on constructing designs for samples taken at point locations. Significantly less work has been done on sample design for data collected along transects. A review of approaches to point and transect sampling design shows that transects can be considered as a sequential set of point samples. Any two sampling designs can be compared through using each one to predict the value of the quantity being measured on a fixed reference grid. The quality of a design is quantified in two ways: computing either the sum or the product of the eigenvalues ofmore » the variance matrix of the prediction error. An important aspect of this analysis is that the reduction of the mean prediction error variance (MPEV) can be calculated for any proposed sample design, including one with straight and/or meandering transects, prior to taking those samples. This reduction in variance can be used as a ''stopping rule'' to determine when enough transect sampling has been completed on the site. Two approaches for the optimization of the transect locations are presented. The first minimizes the sum of the eigenvalues of the predictive error, and the second minimizes the product of these eigenvalues. Simulated annealing is used to identify transect locations that meet either of these objectives. This algorithm is applied to a hypothetical site to determine the optimal locations of two iterations of meandering transects given a previously existing straight transect. The MPEV calculation is also used on both a hypothetical site and on data collected at the Isleta Pueblo to evaluate its potential as a stopping rule. Results show that three or four rounds of systematic sampling with straight parallel transects covering 30 percent or less of the site, can reduce the initial MPEV by as much as 90 percent. The amount of reduction in MPEV can be used as a stopping rule, but the relationship between MPEV and the results of excavation versus no-further-action decisions is site specific and cannot be calculated prior to the sampling. It may be advantageous to use the reduction in MPEV as a stopping rule for systematic sampling across the site that can then be followed by focused sampling in areas identified has having UXO during the systematic sampling. The techniques presented here provide answers to the questions of ''Where to sample?'' and ''When to stop?'' and are capable of running in near real time to support iterative site characterization campaigns.« less

Hessian eigenvalue distribution in a random Gaussian landscape

NASA Astrophysics Data System (ADS)

Yamada, Masaki; Vilenkin, Alexander

2018-03-01

The energy landscape of multiverse cosmology is often modeled by a multi-dimensional random Gaussian potential. The physical predictions of such models crucially depend on the eigenvalue distribution of the Hessian matrix at potential minima. In particular, the stability of vacua and the dynamics of slow-roll inflation are sensitive to the magnitude of the smallest eigenvalues. The Hessian eigenvalue distribution has been studied earlier, using the saddle point approximation, in the leading order of 1/ N expansion, where N is the dimensionality of the landscape. This approximation, however, is insufficient for the small eigenvalue end of the spectrum, where sub-leading terms play a significant role. We extend the saddle point method to account for the sub-leading contributions. We also develop a new approach, where the eigenvalue distribution is found as an equilibrium distribution at the endpoint of a stochastic process (Dyson Brownian motion). The results of the two approaches are consistent in cases where both methods are applicable. We discuss the implications of our results for vacuum stability and slow-roll inflation in the landscape.

PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction.

PubMed

Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou

2018-02-08

The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.

Multigrid one shot methods for optimal control problems: Infinite dimensional control

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.

Computation of Reacting Flows in Combustion Processes

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.; Chen, Kuo-Huey

1997-01-01

The main objective of this research was to develop an efficient three-dimensional computer code for chemically reacting flows. The main computer code developed is ALLSPD-3D. The ALLSPD-3D computer program is developed for the calculation of three-dimensional, chemically reacting flows with sprays. The ALL-SPD code employs a coupled, strongly implicit solution procedure for turbulent spray combustion flows. A stochastic droplet model and an efficient method for treatment of the spray source terms in the gas-phase equations are used to calculate the evaporating liquid sprays. The chemistry treatment in the code is general enough that an arbitrary number of reaction and species can be defined by the users. Also, it is written in generalized curvilinear coordinates with both multi-block and flexible internal blockage capabilities to handle complex geometries. In addition, for general industrial combustion applications, the code provides both dilution and transpiration cooling capabilities. The ALLSPD algorithm, which employs the preconditioning and eigenvalue rescaling techniques, is capable of providing efficient solution for flows with a wide range of Mach numbers. Although written for three-dimensional flows in general, the code can be used for two-dimensional and axisymmetric flow computations as well. The code is written in such a way that it can be run in various computer platforms (supercomputers, workstations and parallel processors) and the GUI (Graphical User Interface) should provide a user-friendly tool in setting up and running the code.

The Cr dependence problem of eigenvalues of the Laplace operator on domains in the plane

NASA Astrophysics Data System (ADS)

Haddad, Julian; Montenegro, Marcos

2018-03-01

The Cr dependence problem of multiple Dirichlet eigenvalues on domains is discussed for elliptic operators by regarding C r + 1-smooth one-parameter families of C1 perturbations of domains in Rn. As applications of our main theorem (Theorem 1), we provide a fairly complete description for all eigenvalues of the Laplace operator on disks and squares in R2 and also for its second eigenvalue on balls in Rn for any n ≥ 3. The central tool used in our proof is a degenerate implicit function theorem on Banach spaces (Theorem 2) of independent interest.

Computing interior eigenvalues of nonsymmetric matrices: application to three-dimensional metamaterial composites.

PubMed

Terao, Takamichi

2010-08-01

We propose a numerical method to calculate interior eigenvalues and corresponding eigenvectors for nonsymmetric matrices. Based on the subspace projection technique onto expanded Ritz subspace, it becomes possible to obtain eigenvalues and eigenvectors with sufficiently high precision. This method overcomes the difficulties of the traditional nonsymmetric Lanczos algorithm, and improves the accuracy of the obtained interior eigenvalues and eigenvectors. Using this algorithm, we investigate three-dimensional metamaterial composites consisting of positive and negative refractive index materials, and it is demonstrated that the finite-difference frequency-domain algorithm is applicable to analyze these metamaterial composites.

The first eigenvalue of the p-Laplacian on quantum graphs

NASA Astrophysics Data System (ADS)

Del Pezzo, Leandro M.; Rossi, Julio D.

2016-12-01

We study the first eigenvalue of the p-Laplacian (with 1

Proper Orthogonal Decomposition in Optimal Control of Fluids

NASA Technical Reports Server (NTRS)

Ravindran, S. S.

1999-01-01

In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

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...

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

A new approach to the method of source-sink potentials for molecular conduction

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

Pickup, Barry T., E-mail: B.T.Pickup@sheffield.ac.uk, E-mail: P.W.Fowler@sheffield.ac.uk; Fowler, Patrick W., E-mail: B.T.Pickup@sheffield.ac.uk, E-mail: P.W.Fowler@sheffield.ac.uk; Borg, Martha

2015-11-21

We re-derive the tight-binding source-sink potential (SSP) equations for ballistic conduction through conjugated molecular structures in a form that avoids singularities. This enables derivation of new results for families of molecular devices in terms of eigenvectors and eigenvalues of the adjacency matrix of the molecular graph. In particular, we define the transmission of electrons through individual molecular orbitals (MO) and through MO shells. We make explicit the behaviour of the total current and individual MO and shell currents at molecular eigenvalues. A rich variety of behaviour is found. A SSP device has specific insulation or conduction at an eigenvalue ofmore » the molecular graph (a root of the characteristic polynomial) according to the multiplicities of that value in the spectra of four defined device polynomials. Conduction near eigenvalues is dominated by the transmission curves of nearby shells. A shell may be inert or active. An inert shell does not conduct at any energy, not even at its own eigenvalue. Conduction may occur at the eigenvalue of an inert shell, but is then carried entirely by other shells. If a shell is active, it carries all conduction at its own eigenvalue. For bipartite molecular graphs (alternant molecules), orbital conduction properties are governed by a pairing theorem. Inertness of shells for families such as chains and rings is predicted by selection rules based on node counting and degeneracy.« less

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

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 reserved.

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.

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; they were worse on preconditioned quantitative susceptibility mapping. Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury. © 2018 by American Journal of Neuroradiology.

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.

Resolvent analysis of shear flows using One-Way Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Rigas, Georgios; Schmidt, Oliver; Towne, Aaron; Colonius, Tim

2017-11-01

For three-dimensional flows, questions of stability, receptivity, secondary flows, and coherent structures require the solution of large partial-derivative eigenvalue problems. Reduced-order approximations are thus required for engineering prediction since these problems are often computationally intractable or prohibitively expensive. For spatially slowly evolving flows, such as jets and boundary layers, the One-Way Navier-Stokes (OWNS) equations permit a fast spatial marching procedure that results in a huge reduction in computational cost. Here, an adjoint-based optimization framework is proposed and demonstrated for calculating optimal boundary conditions and optimal volumetric forcing. The corresponding optimal response modes are validated against modes obtained in terms of global resolvent analysis. For laminar base flows, the optimal modes reveal modal and non-modal transition mechanisms. For turbulent base flows, they predict the evolution of coherent structures in a statistical sense. Results from the application of the method to three-dimensional laminar wall-bounded flows and turbulent jets will be presented. This research was supported by the Office of Naval Research (N00014-16-1-2445) and Boeing Company (CT-BA-GTA-1).

The Use of Sphere Indentation Experiments to Characterize Ceramic Damage Models

DTIC Science & Technology

2011-09-01

state having two equal eigenvalues. For TXC, the axial stress (single eigenvalue) is more compressive than the lateral stresses (dual eigenvalues). For...parameters. These dynamic experiments supplement traditional characterization experiments such as tension, triaxial compression , Brazilian, and...These dynamic experiments supplement traditional characterization experiments such as tension, triaxial compression , Brazilian, and plate impact, which

Localization of the eigenvalues of linear integral equations with applications to linear ordinary differential equations.

NASA Technical Reports Server (NTRS)

Sloss, J. M.; Kranzler, S. K.

1972-01-01

The equivalence of a considered integral equation form with an infinite system of linear equations is proved, and the localization of the eigenvalues of the infinite system is expressed. Error estimates are derived, and the problems of finding upper bounds and lower bounds for the eigenvalues are solved simultaneously.

Conjugate gradient heat bath for ill-conditioned actions.

PubMed

Ceriotti, Michele; Bussi, Giovanni; Parrinello, Michele

2007-08-01

We present a method for performing sampling from a Boltzmann distribution of an ill-conditioned quadratic action. This method is based on heat-bath thermalization along a set of conjugate directions, generated via a conjugate-gradient procedure. The resulting scheme outperforms local updates for matrices with very high condition number, since it avoids the slowing down of modes with lower eigenvalue, and has some advantages over the global heat-bath approach, compared to which it is more stable and allows for more freedom in devising case-specific optimizations.

Automated Pole Placement Algorithm for Multivariable Optimal Control Synthesis.

DTIC Science & Technology

1985-09-01

set of Q and F The effective Qe and F, after n reassignments are given by .Q, Q Q. .. (eqn 4.11) and Fe =F, + Fa+... Fn (eqn 4.12) The above pole...Inverse transformation and determination of Q, and Fe are identical to the distinct eigenvalue case with M in equation 4.9 replaced by T. 3. System...and F and the augmented plant matrix become, Q -2.998 -149. 0.9994 -49.978 -149.9 7499 -0.00841 0.4211 The effective Q. and Fe required to move both

Vibration control of large linear quadratic symmetric systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Jeon, G. J.

1983-01-01

Some unique properties on a class of the second order lambda matrices were found and applied to determine a damping matrix of the decoupled subsystem in such a way that the damped system would have preassigned eigenvalues without disturbing the stiffness matrix. The resulting system was realized as a time invariant velocity only feedback control system with desired poles. Another approach using optimal control theory was also applied to the decoupled system in such a way that the mode spillover problem could be eliminated. The procedures were tested successfully by numerical examples.

Cardioprotective Effects of Transfusion of Late-Phase Preconditioned Plasma May Be Induced by Activating the Reperfusion Injury Salvage Kinase Pathway but Not the Survivor Activating Factor Enhancement Pathway in Rats.

PubMed

Zhao, Yang; Zheng, Zhi-Nan; Pi, Yan-Na; Liang, Xue; Jin, San-Qing

2017-01-01

A previous study in our laboratory demonstrated that transfusion of plasma collected at the late phase of remote ischemic preconditioning (RIPC) could reduce myocardial infarct size. Here, we tested whether the reperfusion injury salvage kinase (RISK) and survivor activating factor enhancement (SAFE) pathways are involved in transferring protection. In a two-part study, donor rats ( n = 3) donated plasma 48 hours after RIPC (preconditioned plasma) or control (nonpreconditioned plasma). Normal (part 1) or ischemic (part 2) myocardia were collected from recipients ( n = 6) 24 hours after receiving normal saline, nonpreconditioned plasma, and preconditioned plasma or after further suffering ischemia reperfusion. Western blot was performed to analyze STAT3, Akt, and Erk1/2 phosphorylation in normal and ischemic myocardium (central area and border area). In normal myocardia, preconditioned plasma increased Akt and Erk1/2 phosphorylation significantly compared to nonpreconditioned plasma and normal saline; no STAT3 phosphorylation was detected. In ischemic myocardia, preconditioned plasma increased Akt and Erk1/2 phosphorylation significantly in both central and border areas compared to other fluids; no significant difference in STAT3 phosphorylation occurred among groups. Transfusion of preconditioned plasma collected at the late phase of RIPC could activate the RISK but not SAFE pathway, suggesting that RISK pathway may be involved in transferring protection.

Derivation of an eigenvalue probability density function relating to the Poincaré disk

NASA Astrophysics Data System (ADS)

Forrester, Peter J.; Krishnapur, Manjunath

2009-09-01

A result of Zyczkowski and Sommers (2000 J. Phys. A: Math. Gen. 33 2045-57) gives the eigenvalue probability density function for the top N × N sub-block of a Haar distributed matrix from U(N + n). In the case n >= N, we rederive this result, starting from knowledge of the distribution of the sub-blocks, introducing the Schur decomposition and integrating over all variables except the eigenvalues. The integration is done by identifying a recursive structure which reduces the dimension. This approach is inspired by an analogous approach which has been recently applied to determine the eigenvalue probability density function for random matrices A-1B, where A and B are random matrices with entries standard complex normals. We relate the eigenvalue distribution of the sub-blocks to a many-body quantum state, and to the one-component plasma, on the pseudosphere.

Asymptotics of empirical eigenstructure for high dimensional spiked covariance.

PubMed

Wang, Weichen; Fan, Jianqing

2017-06-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.

Asymptotics of empirical eigenstructure for high dimensional spiked covariance

PubMed Central

Wang, Weichen

2017-01-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies. PMID:28835726

The construction of partner potential from the general potential anharmonic in D-dimensional Schrodinger system

NASA Astrophysics Data System (ADS)

Suparmi; Cari, C.; Wea, K. N.; Wahyulianti

2018-03-01

The Schrodinger equation is the fundamental equation in quantum physics. The characteristic of the particle in physics potential field can be explained by using the Schrodinger equation. In this study, the solution of 4 dimensional Schrodinger equation for the anharmonic potential and the anharmonic partner potential have done. The method that used to solve the Schrodinger equation was the ansatz wave method, while to construction the partner potential was the supersymmetric method. The construction of partner potential used to explain the experiment result that cannot be explained by the original potential. The eigenvalue for anharmonic potential and the anharmonic partner potential have the same characteristic. Every increase of quantum orbital number the eigenvalue getting smaller. This result corresponds to Bohrn’s atomic theory that the eigenvalue is inversely proportional to the atomic shell. But the eigenvalue for the anharmonic partner potential higher than the eigenvalue for the anharmonic original potential.

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...

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 preconditioning-induced neuroprotection.

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 mechanisms are likely to play a role in preconditioning-induced neuroprotection. PMID:24885038

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.

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.

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.

Iterative Methods for Elliptic Problems and the Discovery of ’q’.

DTIC Science & Technology

1984-07-01

K = M’IlN LN 12 is a nonnegative irreducible matrix. Hence the Perron - Frobenius theory [19] tells us that there is exactly one eigenvalue A with W = p...earlier, the Perron - Frobenius theory implies that p is itself an eigenvalue. However, as we have said, in this instance the eigenvalue problem (l.12a

Asymptotic analysis on a pseudo-Hermitian Riemann-zeta Hamiltonian

NASA Astrophysics Data System (ADS)

Bender, Carl M.; Brody, Dorje C.

2018-04-01

The differential-equation eigenvalue problem associated with a recently-introduced Hamiltonian, whose eigenvalues correspond to the zeros of the Riemann zeta function, is analyzed using Fourier and WKB analysis. The Fourier analysis leads to a challenging open problem concerning the formulation of the eigenvalue problem in the momentum space. The WKB analysis gives the exact asymptotic behavior of the eigenfunction.

Applying nonlinear diffusion acceleration to the neutron transport k-Eigenvalue problem with anisotropic scattering

DOE PAGES

Willert, Jeffrey; Park, H.; Taitano, William

2015-11-01

High-order/low-order (or moment-based acceleration) algorithms have been used to significantly accelerate the solution to the neutron transport k-eigenvalue problem over the past several years. Recently, the nonlinear diffusion acceleration algorithm has been extended to solve fixed-source problems with anisotropic scattering sources. In this paper, we demonstrate that we can extend this algorithm to k-eigenvalue problems in which the scattering source is anisotropic and a significant acceleration can be achieved. Lastly, we demonstrate that the low-order, diffusion-like eigenvalue problem can be solved efficiently using a technique known as nonlinear elimination.

Solving complex band structure problems with the FEAST eigenvalue algorithm

NASA Astrophysics Data System (ADS)

Laux, S. E.

2012-08-01

With straightforward extension, the FEAST eigenvalue algorithm [Polizzi, Phys. Rev. B 79, 115112 (2009)] is capable of solving the generalized eigenvalue problems representing traveling-wave problems—as exemplified by the complex band-structure problem—even though the matrices involved are complex, non-Hermitian, and singular, and hence outside the originally stated range of applicability of the algorithm. The obtained eigenvalues/eigenvectors, however, contain spurious solutions which must be detected and removed. The efficiency and parallel structure of the original algorithm are unaltered. The complex band structures of Si layers of varying thicknesses and InAs nanowires of varying radii are computed as test problems.

Complex eigenvalue extraction in NASTRAN by the tridiagonal reduction (FEER) method

NASA Technical Reports Server (NTRS)

Newman, M.; Mann, F. I.

1977-01-01

An extension of the Tridiagonal Reduction (FEER) method to complex eigenvalue analysis in NASTRAN is described. As in the case of real eigenvalue analysis, the eigensolutions closest to a selected point in the eigenspectrum are extracted from a reduced, symmetric, tridiagonal eigenmatrix whose order is much lower than that of the full size problem. The reduction process is effected automatically, and thus avoids the arbitrary lumping of masses and other physical quantities at selected grid points. The statement of the algebraic eigenvalue problem admits mass, damping and stiffness matrices which are unrestricted in character, i.e., they may be real, complex, symmetric or unsymmetric, singular or non-singular.

Comment on ‘Numerical estimates of the spectrum for anharmonic PT symmetric potentials’

NASA Astrophysics Data System (ADS)

Amore, Paolo; Fernández, Francisco M.

2013-04-01

We show that the authors of the commented paper (Bowen et al 2012 Phys. Scr. 85 065005) draw their conclusions from the eigenvalues of truncated Hamiltonian matrices that do not converge as the matrix dimension increases. In some of the studied examples, the authors missed the real positive eigenvalues that already converge towards the exact eigenvalues of the non-Hermitian operators and focused their attention on the complex ones that do not. We also show that the authors misread Bender's argument about the eigenvalues of the harmonic oscillator with boundary conditions in the complex-x plane (Bender 2007 Rep. Prog. Phys. 70 947).

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.

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

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.

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.

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.

Repeated applications of a transdermal patch: analytical solution and optimal control of the delivery rate.

PubMed

Simon, L

2007-10-01

The integral transform technique was implemented to solve a mathematical model developed for percutaneous drug absorption. The model included repeated application and removal of a patch from the skin. Fick's second law of diffusion was used to study the transport of a medicinal agent through the vehicle and subsequent penetration into the stratum corneum. Eigenmodes and eigenvalues were computed and introduced into an inversion formula to estimate the delivery rate and the amount of drug in the vehicle and the skin. A dynamic programming algorithm calculated the optimal doses necessary to achieve a desired transdermal flux. The analytical method predicted profiles that were in close agreement with published numerical solutions and provided an automated strategy to perform therapeutic drug monitoring and control.

Robust L1-norm two-dimensional linear discriminant analysis.

PubMed

Li, Chun-Na; Shao, Yuan-Hai; Deng, Nai-Yang

2015-05-01

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-2DLDA) with robust performance. Different from the conventional two-dimensional linear discriminant analysis with L2-norm (L2-2DLDA), where the optimization problem is transferred to a generalized eigenvalue problem, the optimization problem in our L1-2DLDA is solved by a simple justifiable iterative technique, and its convergence is guaranteed. Compared with L2-2DLDA, our L1-2DLDA is more robust to outliers and noises since the L1-norm is used. This is supported by our preliminary experiments on toy example and face datasets, which show the improvement of our L1-2DLDA over L2-2DLDA. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design of fused-silica rectangular transmission gratings for polarizing beam splitter based on modal method.

PubMed

Zhao, Huajun; Yuan, Dairong

2010-02-10

Examples of optimal designs for a fused-silica transmitted grating with high-intensity tolerance are discussed. It has the potential of placing up to 99% incident polarized light in a single diffraction order. The modal method has been used to analyze the effective indices for TE and TM polarization propagating through the grating region, and the eigenvalue equation of the modal method is transformed to a new form. It is shown that the effective indices of the first two modes depend on the value of the period under Littrow mounting with filling factor f=0.5. The polarization properties of the polarizing beam splitter are analyzed by rigorous coupled-wave analysis (RCWA) at the wavelength of 1.064 microm. The optimal design perfectly matches the RCWA simulation result.

Optimal mistuning for enhanced aeroelastic stability of transonic fans

NASA Technical Reports Server (NTRS)

Hall, K. C.; Crawley, E. F.

1983-01-01

An inverse design procedure was developed for the design of a mistuned rotor. The design requirements are that the stability margin of the eigenvalues of the aeroelastic system be greater than or equal to some minimum stability margin, and that the mass added to each blade be positive. The objective was to achieve these requirements with a minimal amount of mistuning. Hence, the problem was posed as a constrained optimization problem. The constrained minimization problem was solved by the technique of mathematical programming via augmented Lagrangians. The unconstrained minimization phase of this technique was solved by the variable metric method. The bladed disk was modelled as being composed of a rigid disk mounted on a rigid shaft. Each of the blades were modelled with a single tosional degree of freedom.

Piecewise linear approximation for hereditary control problems

NASA Technical Reports Server (NTRS)

Propst, Georg

1987-01-01

Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.

Swimming of a sphere in a viscous incompressible fluid with inertia

NASA Astrophysics Data System (ADS)

Felderhof, B. U.; Jones, R. B.

2017-08-01

The swimming of a sphere immersed in a viscous incompressible fluid with inertia is studied for surface modulations of small amplitude on the basis of the Navier-Stokes equations. The mean swimming velocity and the mean rate of dissipation are expressed as quadratic forms in term of the surface displacements. With a choice of a basis set of modes the quadratic forms correspond to two Hermitian matrices. Optimization of the mean swimming velocity for given rate of dissipation requires the solution of a generalized eigenvalue problem involving the two matrices. It is found for surface modulations of low multipole order that the optimal swimming efficiency depends in intricate fashion on a dimensionless scale number involving the radius of the sphere, the period of the cycle, and the kinematic viscosity of the fluid.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Efficient exact-exchange time-dependent density-functional theory methods and their relation to time-dependent Hartree-Fock.

PubMed

Hesselmann, Andreas; Görling, Andreas

2011-01-21

A recently introduced time-dependent exact-exchange (TDEXX) method, i.e., a response method based on time-dependent density-functional theory that treats the frequency-dependent exchange kernel exactly, is reformulated. In the reformulated version of the TDEXX method electronic excitation energies can be calculated by solving a linear generalized eigenvalue problem while in the original version of the TDEXX method a laborious frequency iteration is required in the calculation of each excitation energy. The lowest eigenvalues of the new TDEXX eigenvalue equation corresponding to the lowest excitation energies can be efficiently obtained by, e.g., a version of the Davidson algorithm appropriate for generalized eigenvalue problems. Alternatively, with the help of a series expansion of the new TDEXX eigenvalue equation, standard eigensolvers for large regular eigenvalue problems, e.g., the standard Davidson algorithm, can be used to efficiently calculate the lowest excitation energies. With the help of the series expansion as well, the relation between the TDEXX method and time-dependent Hartree-Fock is analyzed. Several ways to take into account correlation in addition to the exact treatment of exchange in the TDEXX method are discussed, e.g., a scaling of the Kohn-Sham eigenvalues, the inclusion of (semi)local approximate correlation potentials, or hybrids of the exact-exchange kernel with kernels within the adiabatic local density approximation. The lowest lying excitations of the molecules ethylene, acetaldehyde, and pyridine are considered as examples.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Ultrarelativistic bound states in the spherical well

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

Żaba, Mariusz; Garbaczewski, Piotr

2016-07-15

We address an eigenvalue problem for the ultrarelativistic (Cauchy) operator (−Δ){sup 1/2}, whose action is restricted to functions that vanish beyond the interior of a unit sphere in three spatial dimensions. We provide high accuracy spectral data for lowest eigenvalues and eigenfunctions of this infinite spherical well problem. Our focus is on radial and orbital shapes of eigenfunctions. The spectrum consists of an ordered set of strictly positive eigenvalues which naturally splits into non-overlapping, orbitally labelled E{sub (k,l)} series. For each orbital label l = 0, 1, 2, …, the label k = 1, 2, … enumerates consecutive lth seriesmore » eigenvalues. Each of them is 2l + 1-degenerate. The l = 0 eigenvalues series E{sub (k,0)} are identical with the set of even labeled eigenvalues for the d = 1 Cauchy well: E{sub (k,0)}(d = 3) = E{sub 2k}(d = 1). Likewise, the eigenfunctions ψ{sub (k,0)}(d = 3) and ψ{sub 2k}(d = 1) show affinity. We have identified the generic functional form of eigenfunctions of the spherical well which appear to be composed of a product of a solid harmonic and of a suitable purely radial function. The method to evaluate (approximately) the latter has been found to follow the universal pattern which effectively allows to skip all, sometimes involved, intermediate calculations (those were in usage, while computing the eigenvalues for l ≤ 3).« 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.

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.

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.

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).

Optimizing the wireless power transfer over MIMO Channels

NASA Astrophysics Data System (ADS)

Wiedmann, Karsten; Weber, Tobias

2017-09-01

In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.

Towards a generalized computational fluid dynamics technique for all Mach numbers

NASA Technical Reports Server (NTRS)

Walters, R. W.; Slack, D. C.; Godfrey, A. G.

1993-01-01

Currently there exists no single unified approach for efficiently and accurately solving computational fluid dynamics (CFD) problems across the Mach number regime, from truly low speed incompressible flows to hypersonic speeds. There are several CFD codes that have evolved into sophisticated prediction tools with a wide variety of features including multiblock capabilities, generalized chemistry and thermodynamics models among other features. However, as these codes evolve, the demand placed on the end user also increases simply because of the myriad of features that are incorporated into these codes. In order for a user to be able to solve a wide range of problems, several codes may be needed requiring the user to be familiar with the intricacies of each code and their rather complicated input files. Moreover, the cost of training users and maintaining several codes becomes prohibitive. The objective of the current work is to extend the compressible, characteristic-based, thermochemical nonequilibrium Navier-Stokes code GASP to very low speed flows and simultaneously improve convergence at all speeds. Before this work began, the practical speed range of GASP was Mach numbers on the order of 0.1 and higher. In addition, a number of new techniques have been developed for more accurate physical and numerical modeling. The primary focus has been on the development of optimal preconditioning techniques for the Euler and the Navier-Stokes equations with general finite-rate chemistry models and both equilibrium and nonequilibrium thermodynamics models. We began with the work of Van Leer, Lee, and Roe for inviscid, one-dimensional perfect gases and extended their approach to include three-dimensional reacting flows. The basic steps required to accomplish this task were a transformation to stream-aligned coordinates, the formulation of the preconditioning matrix, incorporation into both explicit and implicit temporal integration schemes, and modification of the numerical flux formulae. In addition, we improved the convergence rate of the implicit time integration schemes in GASP through the use of inner iteration strategies and the use of the GMRES (General Minimized Resisual) which belongs to the class of algorithms referred to as Krylov subspace iteration. Finally, we significantly improved the practical utility of GASP through the addition of mesh sequencing, a technique in which computations begin on a coarse grid and get interpolated onto successively finer grids. The fluid dynamic problems of interest to the propulsion community involve complex flow physics spanning different velocity regimes and possibly involving chemical reactions. This class of problems results in widely disparate time scales causing numerical stiffness. Even in the absence of chemical reactions, eigenvalue stiffness manifests itself at transonic and very low speed flows which can be quantified by the large condition number of the system and evidenced by slow convergence rates. This results in the need for thorough numerical analysis and subsequent implementation of sophisticated numerical techniques for these difficult yet practical problems. As a result of this work, we have been able to extend the range of applicability of compressible codes to very low speed inviscid flows (M = .001) and reacting flows.

A divide and conquer approach to the nonsymmetric eigenvalue problem

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

Jessup, E.R.

1991-01-01

Serial computation combined with high communication costs on distributed-memory multiprocessors make parallel implementations of the QR method for the nonsymmetric eigenvalue problem inefficient. This paper introduces an alternative algorithm for the nonsymmetric tridiagonal eigenvalue problem based on rank two tearing and updating of the matrix. The parallelism of this divide and conquer approach stems from independent solution of the updating problems. 11 refs.

The ELPA library: scalable parallel eigenvalue solutions for electronic structure theory and computational science.

PubMed

Marek, A; Blum, V; Johanni, R; Havu, V; Lang, B; Auckenthaler, T; Heinecke, A; Bungartz, H-J; Lederer, H

2014-05-28

Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structure theory and many other areas of computational science. The computational effort formally scales as O(N(3)) with the size of the investigated problem, N (e.g. the electron count in electronic structure theory), and thus often defines the system size limit that practical calculations cannot overcome. In many cases, more than just a small fraction of the possible eigenvalue/eigenvector pairs is needed, so that iterative solution strategies that focus only on a few eigenvalues become ineffective. Likewise, it is not always desirable or practical to circumvent the eigenvalue solution entirely. We here review some current developments regarding dense eigenvalue solvers and then focus on the Eigenvalue soLvers for Petascale Applications (ELPA) library, which facilitates the efficient algebraic solution of symmetric and Hermitian eigenvalue problems for dense matrices that have real-valued and complex-valued matrix entries, respectively, on parallel computer platforms. ELPA addresses standard as well as generalized eigenvalue problems, relying on the well documented matrix layout of the Scalable Linear Algebra PACKage (ScaLAPACK) library but replacing all actual parallel solution steps with subroutines of its own. For these steps, ELPA significantly outperforms the corresponding ScaLAPACK routines and proprietary libraries that implement the ScaLAPACK interface (e.g. Intel's MKL). The most time-critical step is the reduction of the matrix to tridiagonal form and the corresponding backtransformation of the eigenvectors. ELPA offers both a one-step tridiagonalization (successive Householder transformations) and a two-step transformation that is more efficient especially towards larger matrices and larger numbers of CPU cores. ELPA is based on the MPI standard, with an early hybrid MPI-OpenMPI implementation available as well. Scalability beyond 10,000 CPU cores for problem sizes arising in the field of electronic structure theory is demonstrated for current high-performance computer architectures such as Cray or Intel/Infiniband. For a matrix of dimension 260,000, scalability up to 295,000 CPU cores has been shown on BlueGene/P.

Neuron specific metabolic adaptations following multi-day exposures to oxygen glucose deprivation.

PubMed

Zeiger, Stephanie L H; McKenzie, Jennifer R; Stankowski, Jeannette N; Martin, Jacob A; Cliffel, David E; McLaughlin, BethAnn

2010-11-01

Prior exposure to sub toxic insults can induce a powerful endogenous neuroprotective program known as ischemic preconditioning. Current models typically rely on a single stress episode to induce neuroprotection whereas the clinical reality is that patients may experience multiple transient ischemic attacks (TIAs) prior to suffering a stroke. We sought to develop a neuron-enriched preconditioning model using multiple oxygen glucose deprivation (OGD) episodes to assess the endogenous protective mechanisms neurons implement at the metabolic and cellular level. We found that neurons exposed to a five minute period of glucose deprivation recovered oxygen utilization and lactate production using novel microphysiometry techniques. Using the non-toxic and energetically favorable five minute exposure, we developed a preconditioning paradigm where neurons are exposed to this brief OGD for three consecutive days. These cells experienced a 45% greater survival following an otherwise lethal event and exhibited a longer lasting window of protection in comparison to our previous in vitro preconditioning model using a single stress. As in other models, preconditioned cells exhibited mild caspase activation, an increase in oxidized proteins and a requirement for reactive oxygen species for neuroprotection. Heat shock protein 70 was upregulated during preconditioning, yet the majority of this protein was released extracellularly. We believe coupling this neuron-enriched multi-day model with microphysiometry will allow us to assess neuronal specific real-time metabolic adaptations necessary for preconditioning. Copyright © 2010 Elsevier B.V. All rights reserved.

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.

Electrical Resistivity Tomography using a finite element based BFGS algorithm with algebraic multigrid preconditioning

NASA Astrophysics Data System (ADS)

Codd, A. L.; Gross, L.

2018-03-01

We present a new inversion method for Electrical Resistivity Tomography which, in contrast to established approaches, minimizes the cost function prior to finite element discretization for the unknown electric conductivity and electric potential. Minimization is performed with the Broyden-Fletcher-Goldfarb-Shanno method (BFGS) in an appropriate function space. BFGS is self-preconditioning and avoids construction of the dense Hessian which is the major obstacle to solving large 3-D problems using parallel computers. In addition to the forward problem predicting the measurement from the injected current, the so-called adjoint problem also needs to be solved. For this problem a virtual current is injected through the measurement electrodes and an adjoint electric potential is obtained. The magnitude of the injected virtual current is equal to the misfit at the measurement electrodes. This new approach has the advantage that the solution process of the optimization problem remains independent to the meshes used for discretization and allows for mesh adaptation during inversion. Computation time is reduced by using superposition of pole loads for the forward and adjoint problems. A smoothed aggregation algebraic multigrid (AMG) preconditioned conjugate gradient is applied to construct the potentials for a given electric conductivity estimate and for constructing a first level BFGS preconditioner. Through the additional reuse of AMG operators and coarse grid solvers inversion time for large 3-D problems can be reduced further. We apply our new inversion method to synthetic survey data created by the resistivity profile representing the characteristics of subsurface fluid injection. We further test it on data obtained from a 2-D surface electrode survey on Heron Island, a small tropical island off the east coast of central Queensland, Australia.

The remote ischemic preconditioning algorithm: effect of number of cycles, cycle duration and effector organ mass on efficacy of protection.

PubMed

Johnsen, Jacob; Pryds, Kasper; Salman, Rasha; Løfgren, Bo; Kristiansen, Steen Buus; Bøtker, Hans Erik

2016-03-01

Remote ischemic preconditioning (rIPC), induced by cycles of transient limb ischemia and reperfusion (IR), is cardioprotective. The optimal rIPC-algorithm is not established. We investigated the effect of cycle numbers and ischemia duration within each rIPC-cycle and the influence of effector organ mass on the efficacy of cardioprotection. Furthermore, the duration of the early phase of protection by rIPC was investigated. Using a tourniquet tightened at the inguinal level, we subjected C57Bl/6NTac mice to intermittent hind-limb ischemia and reperfusion. The rIPC-protocols consisted of (I) two, four, six or eight cycles, (II) 2, 5 or 10 min of ischemia in each cycle, (III) single or two hind-limb occlusions and (IV) 0.5, 1.5, 2.0 or 2.5 h intervals from rIPC to index cardiac ischemia. All rIPC algorithms were followed by 5 min of reperfusion. The hearts were subsequently exposed to 25 min of global ischemia and 60 min of reperfusion in an ex vivo Langendorff model. Cardioprotection was evaluated by infarct size and post-ischemic hemodynamic recovery. Four to six rIPC cycles yielded significant cardioprotection with no further protection by eight cycles. Ischemic cycles lasting 2 min offered the same protection as cycles of 5 min ischemia, whereas prolonged cycles lasting 10 min abrogated protection. One and two hind-limb preconditioning were equally protective. In our mouse model, the duration of protection by rIPC was 1.5 h. These findings indicate that the number and duration of cycles rather than the tissue mass exposed to rIPC determines the efficacy of rIPC.

The method of fundamental solutions for computing acoustic interior transmission eigenvalues

NASA Astrophysics Data System (ADS)

Kleefeld, Andreas; Pieronek, Lukas

2018-03-01

We analyze the method of fundamental solutions (MFS) in two different versions with focus on the computation of approximate acoustic interior transmission eigenvalues in 2D for homogeneous media. Our approach is mesh- and integration free, but suffers in general from the ill-conditioning effects of the discretized eigenoperator, which we could then successfully balance using an approved stabilization scheme. Our numerical examples cover many of the common scattering objects and prove to be very competitive in accuracy with the standard methods for PDE-related eigenvalue problems. We finally give an approximation analysis for our framework and provide error estimates, which bound interior transmission eigenvalue deviations in terms of some generalized MFS output.

[Effect of electroacupuncture and moxibustion preconditioning on blood endothelin and creatine kinase contents and myocardial HSP 70 expression in rabbits with myocardial ischemia-reperfusion injury].

PubMed

Wang, Chao; Xie, Wen-juan; Liu, Mi; Yan, Jie; Zhang, Jia-li; Liu, Zhao; Guo, Li-na

2014-10-01

To observe the effect of electroacupuncture (EA) and moxibustion (Moxi) preconditioning of bi- lateral "Neiguan" (PC 6) on plasma endothelin (ET) and serum creatine kinase (CK) contents and myocardial hot shock protein 70 (HSP 70) expression in myocardial ischemia-reperfusion injury (MIRI) rabbits, so as to revel their mechanisms underlying prevention of myocardial ischemia. A total of 72 New Zealand rabbits were randomly divided into sham operation, MIRI model, EA preconditioning and Moxi preconditioning groups (n = 18/group). Each group was further divided into 0 h, 24 h and 48 h (time-point) subgroups (n=6 in each subgroup). The MIRI model was established by occlusion of the anterior descending branch of the left coronary artery for 40 min and reperfusion for 60 min. The contents of plasma ET and serum CK were detected by ELISA, and myocardial HSP 70 expression was detected by immunohistochemistry. EA and Moxi preconditioning were respectively applied to bilateral PC 6 for 20 min, once daily for 5 days. Following MIRI, contents of plasma ET and serum CK contents were significantly increased at 0 h, 24 h and 48 h in comparison with the sham group (P<0.01, P<0.05), while myo- cardial HSP 70 expression at the 3 time-points was moderately increased (P>0.05). Compared with the model groups, plasma ET contents at both 24 h and 48 h in the EA preconditioning group and at 48 h in the Moxi preconditioning group, CK contents at both 24 h and 48 h only in the EA preconditioning group were significantly down-regulated (P<0.01, P<0.05). Myocardial HSP 70 expression levels in the EA and Moxi preconditioning groups were considerably up-regulated at the three time-points in comparison with the model group(P<0.05, P<0.01). Acupuncture and moxibustion pretreatment may suppress MIRI-induced increase of plasma ET and serum CK and up-regulate myocardial HSP 70 protein expression in MIRI rabbits, suggesting a preventive protection action on ischemic myocardium.

Eigenvalue assignment strategies in rotor systems

NASA Technical Reports Server (NTRS)

Youngblood, J. N.; Welzyn, K. J.

1986-01-01

The work done to establish the control and direction of effective eigenvalue excursions of lightly damped, speed dependent rotor systems using passive control is discussed. Both second order and sixth order bi-axis, quasi-linear, speed dependent generic models were investigated. In every case a single, bi-directional control bearing was used in a passive feedback stabilization loop to resist modal destabilization above the rotor critical speed. Assuming incomplete state measurement, sub-optimal control strategies were used to define the preferred location of the control bearing, the most effective measurement locations, and the best set of control gains to extend the speed range of stable operation. Speed dependent control gains were found by Powell's method to maximize the minimum modal damping ratio for the speed dependent linear model. An increase of 300 percent in stable speed operation was obtained for the sixth order linear system using passive control. Simulations were run to examine the effectiveness of the linear control law on nonlinear rotor models with bearing deadband. The maximum level of control effort (force) required by the control bearing to stabilize the rotor at speeds above the critical was determined for the models with bearing deadband.

An accurate and efficient acoustic eigensolver based on a fast multipole BEM and a contour integral method

NASA Astrophysics Data System (ADS)

Zheng, Chang-Jun; Gao, Hai-Feng; Du, Lei; Chen, Hai-Bo; Zhang, Chuanzeng

2016-01-01

An accurate numerical solver is developed in this paper for eigenproblems governed by the Helmholtz equation and formulated through the boundary element method. A contour integral method is used to convert the nonlinear eigenproblem into an ordinary eigenproblem, so that eigenvalues can be extracted accurately by solving a set of standard boundary element systems of equations. In order to accelerate the solution procedure, the parameters affecting the accuracy and efficiency of the method are studied and two contour paths are compared. Moreover, a wideband fast multipole method is implemented with a block IDR (s) solver to reduce the overall solution cost of the boundary element systems of equations with multiple right-hand sides. The Burton-Miller formulation is employed to identify the fictitious eigenfrequencies of the interior acoustic problems with multiply connected domains. The actual effect of the Burton-Miller formulation on tackling the fictitious eigenfrequency problem is investigated and the optimal choice of the coupling parameter as α = i / k is confirmed through exterior sphere examples. Furthermore, the numerical eigenvalues obtained by the developed method are compared with the results obtained by the finite element method to show the accuracy and efficiency of the developed method.

Linear instabilities near the DIII-D edge simulated in fluid models

NASA Astrophysics Data System (ADS)

Bass, Eric; Holland, Christopher

2017-10-01

The linear instability spectrum is reported near the DIII-D edge (within the separatrix) for L-mode and H-mode shots using the new eigenvalue solver FluTES (Fluid Toroidal Eigenvalue Solver). FluTES circumvents difficulties with convergence to clean linear eigenmodes (required for diagnosis of nonlinear simulations in codes such as BOUT++) often encountered with fluid initial-value solvers. FluTES is well-verified in analytic cases and against a BOUT++/ELITE benchmark toroidal case. We report results for both a 3-field, one-fluid model (the well-known ``elm-pb'' model) and a 5-field, two-fluid model. For the peeling-ballooning-dominated H-mode, the two solutions are qualitatively the same. In the driftwave-dominated L-mode edge, only the two-fluid solution gives robust instabilities which occur primarily at n > 50 . FluTES is optimized for this regime (near-flutelike limit, toroidally spectral). Cross-separatrix, coupled fluid and drift instabilities may play a role in explaining the gyrokinetic L-mode edge transport shortfall. Extension of FluTES into the open-field-line region is underway. Prepared by UCSD under Contract Number DE-FG02-06ER54871.

Improved recovery of cryotherapy-treated shoot tips following thermotherapy of in vitro-grown stock shoots of raspberry (Rubus idaeus L.).

PubMed

Wang, Qiaochun; Valkonen, Jari P T

2009-01-01

Raspberry bushy dwarf virus (RBDV) can be efficiently eradicated from raspberry plants (Rubus idaeus) by a procedure combining thermotherapy and cryotherapy. However, the bottleneck of this procedure is that, following thermotherapy, cryopreserved shoot tips become chlorotic during regrowth and eventually die after several subcultures. In addition, survival of heat-treated stock shoots and recovery of cryopreserved shoot tips following thermotherapy are low. The present study focused towards improving regrowth of cryopreserved raspberry shoot tips following thermotherapy. Results showed that preconditioning stock shoots with salicylic acid (SA; 0.01-0.1 mM) markedly increased survival of stock shoots after 4 weeks of thermotherapy. Regrowth of cryopreserved shoot tips following thermotherapy was also significantly enhanced when SA (0.05-0.1 mM) was used for preconditioning stock shoots. Addition of either Fe-ethylenediaminetetracetic acid (Fe-EDTA, 50 mg per L) or Fe-ethylenediaminedi(o)hydroxyphenylacetic acid (Fe-EDDHA, 50 mg per L) to post-culture medium strongly promoted regrowth and totally prevented chlorosis of shoots regenerated from cryopreserved shoot tips following thermotherapy. Using the parameters optimized in the present study, about 80 percent survival of heat-treated stock shoots and about 33 percent regrowth of cryopreserved shoot tips following thermotherapy were obtained. Morphology of plants regenerated from cryopreserved shoot tips following thermotherapy was identical to that of control plants, based on observations of leaf shape and size, internode length and plant height. Optimization of the thermotherapy procedure followed by cryotherapy will facilitate the wider application of this technique to eliminate viruses which can invade meristems.

Aeroelastic Stability of Idling Wind Turbines

NASA Astrophysics Data System (ADS)

Wang, Kai; Riziotis, Vasilis A.; Voutsinas, Spyros G.

2016-09-01

Wind turbine rotors in idling operation mode can experience high angles of attack, within the post stall region that are capable of triggering stall-induced vibrations. In the present paper rotor stability in slow idling operation is assessed on the basis of non-linear time domain and linear eigenvalue analysis. Analysis is performed for a 10 MW conceptual wind turbine designed by DTU. First the flow conditions that are likely to favour stall induced instabilities are identified through non-linear time domain aeroelastic analysis. Next, for the above specified conditions, eigenvalue stability simulations are performed aiming at identifying the low damped modes of the turbine. Finally the results of the eigenvalue analysis are evaluated through computations of the work of the aerodynamic forces by imposing harmonic vibrations following the shape and frequency of the various modes. Eigenvalue analysis indicates that the asymmetric and symmetric out-of-plane modes have the lowest damping. The results of the eigenvalue analysis agree well with those of the time domain analysis.

Substructure Versus Property-Level Dispersed Modes Calculation

NASA Technical Reports Server (NTRS)

Stewart, Eric C.; Peck, Jeff A.; Bush, T. Jason; Fulcher, Clay W.

2016-01-01

This paper calculates the effect of perturbed finite element mass and stiffness values on the eigenvectors and eigenvalues of the finite element model. The structure is perturbed in two ways: at the "subelement" level and at the material property level. In the subelement eigenvalue uncertainty analysis the mass and stiffness of each subelement is perturbed by a factor before being assembled into the global matrices. In the property-level eigenvalue uncertainty analysis all material density and stiffness parameters of the structure are perturbed modified prior to the eigenvalue analysis. The eigenvalue and eigenvector dispersions of each analysis (subelement and property-level) are also calculated using an analytical sensitivity approximation. Two structural models are used to compare these methods: a cantilevered beam model, and a model of the Space Launch System. For each structural model it is shown how well the analytical sensitivity modes approximate the exact modes when the uncertainties are applied at the subelement level and at the property level.

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

NASA Astrophysics Data System (ADS)

Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo

2017-12-01

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

Spectrum of walk matrix for Koch network and its application

NASA Astrophysics Data System (ADS)

Xie, Pinchen; Lin, Yuan; Zhang, Zhongzhi

2015-06-01

Various structural and dynamical properties of a network are encoded in the eigenvalues of walk matrix describing random walks on the network. In this paper, we study the spectra of walk matrix of the Koch network, which displays the prominent scale-free and small-world features. Utilizing the particular architecture of the network, we obtain all the eigenvalues and their corresponding multiplicities. Based on the link between the eigenvalues of walk matrix and random target access time defined as the expected time for a walker going from an arbitrary node to another one selected randomly according to the steady-state distribution, we then derive an explicit solution to the random target access time for random walks on the Koch network. Finally, we corroborate our computation for the eigenvalues by enumerating spanning trees in the Koch network, using the connection governing eigenvalues and spanning trees, where a spanning tree of a network is a subgraph of the network, that is, a tree containing all the nodes.

Approximation of eigenvalues of some differential equations by zeros of orthogonal polynomials

NASA Astrophysics Data System (ADS)

Volkmer, Hans

2008-04-01

Sequences of polynomials, orthogonal with respect to signed measures, are associated with a class of differential equations including the Mathieu, Lame and Whittaker-Hill equation. It is shown that the zeros of pn form sequences which converge to the eigenvalues of the corresponding differential equations. Moreover, interlacing properties of the zeros of pn are found. Applications to the numerical treatment of eigenvalue problems are given.

Eigenvectors determination of the ribosome dynamics model during mRNA translation using the Kleene Star algorithm

NASA Astrophysics Data System (ADS)

Ernawati; Carnia, E.; Supriatna, A. K.

2018-03-01

Eigenvalues and eigenvectors in max-plus algebra have the same important role as eigenvalues and eigenvectors in conventional algebra. In max-plus algebra, eigenvalues and eigenvectors are useful for knowing dynamics of the system such as in train system scheduling, scheduling production systems and scheduling learning activities in moving classes. In the translation of proteins in which the ribosome move uni-directionally along the mRNA strand to recruit the amino acids that make up the protein, eigenvalues and eigenvectors are used to calculate protein production rates and density of ribosomes on the mRNA. Based on this, it is important to examine the eigenvalues and eigenvectors in the process of protein translation. In this paper an eigenvector formula is given for a ribosome dynamics during mRNA translation by using the Kleene star algorithm in which the resulting eigenvector formula is simpler and easier to apply to the system than that introduced elsewhere. This paper also discusses the properties of the matrix {B}λ \\otimes n of model. Among the important properties, it always has the same elements in the first column for n = 1, 2,… if the eigenvalue is the time of initiation, λ = τin , and the column is the eigenvector of the model corresponding to λ.

Eigenvalue Attraction

NASA Astrophysics Data System (ADS)

Movassagh, Ramis

2016-02-01

We prove that the complex conjugate (c.c.) eigenvalues of a smoothly varying real matrix attract (Eq. 15). We offer a dynamical perspective on the motion and interaction of the eigenvalues in the complex plane, derive their governing equations and discuss applications. C.c. pairs closest to the real axis, or those that are ill-conditioned, attract most strongly and can collide to become exactly real. As an application we consider random perturbations of a fixed matrix M. If M is Normal, the total expected force on any eigenvalue is shown to be only the attraction of its c.c. (Eq. 24) and when M is circulant the strength of interaction can be related to the power spectrum of white noise. We extend this by calculating the expected force (Eq. 41) for real stochastic processes with zero-mean and independent intervals. To quantify the dominance of the c.c. attraction, we calculate the variance of other forces. We apply the results to the Hatano-Nelson model and provide other numerical illustrations. It is our hope that the simple dynamical perspective herein might help better understanding of the aggregation and low density of the eigenvalues of real random matrices on and near the real line respectively. In the appendix we provide a Matlab code for plotting the trajectories of the eigenvalues.

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

A comparison of acceleration methods for solving the neutron transport k-eigenvalue problem

NASA Astrophysics Data System (ADS)

Willert, Jeffrey; Park, H.; Knoll, D. A.

2014-10-01

Over the past several years a number of papers have been written describing modern techniques for numerically computing the dominant eigenvalue of the neutron transport criticality problem. These methods fall into two distinct categories. The first category of methods rewrite the multi-group k-eigenvalue problem as a nonlinear system of equations and solve the resulting system using either a Jacobian-Free Newton-Krylov (JFNK) method or Nonlinear Krylov Acceleration (NKA), a variant of Anderson Acceleration. These methods are generally successful in significantly reducing the number of transport sweeps required to compute the dominant eigenvalue. The second category of methods utilize Moment-Based Acceleration (or High-Order/Low-Order (HOLO) Acceleration). These methods solve a sequence of modified diffusion eigenvalue problems whose solutions converge to the solution of the original transport eigenvalue problem. This second class of methods is, in our experience, always superior to the first, as most of the computational work is eliminated by the acceleration from the LO diffusion system. In this paper, we review each of these methods. Our computational results support our claim that the choice of which nonlinear solver to use, JFNK or NKA, should be secondary. The primary computational savings result from the implementation of a HOLO algorithm. We display computational results for a series of challenging multi-dimensional test problems.

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.

Changes in diffusion tensor imaging (DTI) eigenvalues of skeletal muscle due to hybrid exercise training.

PubMed

Okamoto, Yoshikazu; Kemp, Graham J; Isobe, Tomonori; Sato, Eisuke; Hirano, Yuji; Shoda, Junichi; Minami, Manabu

2014-12-01

Several studies have proposed the cell membrane as the main water diffusion restricting factor in the skeletal muscle cell. We sought to establish whether a particular form of exercise training (which is likely to affect only intracellular components) could affect water diffusion. The purpose of this study is to characterise prospectively the changes in diffusion tensor imaging (DTI) eigenvalues of thigh muscle resulting from hybrid training (HYBT) in patients with non-alcoholic fatty liver disease (NAFLD). Twenty-one NAFLD patients underwent HYBT for 30 minutes per day, twice a week for 6 months. Patients were scanned using DTI of the thigh pre- and post-HYBT. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), the three eigenvalues lambda 1 (λ1), λ2, λ3, and the maximal cross sectional area (CSA) were measured in bilateral thigh muscles: knee flexors (biceps femoris (BF), semitendinosus (ST), semimembranous (SM)) and knee extensors (medial vastus (MV), intermediate vastus (IV), lateral vastus (LV), and rectus femoris (RF)), and compared pre- and post-HYBT by paired t-test. Muscle strength of extensors (P<0.01), but not flexors, increased significantly post-HYBT. For FA, ADC and eigenvalues, the overall picture was of increase. Some (P<0.05 in λ2 and P<0.01 in λ1) eigenvalues of flexors and all (λ1-λ3) eigenvalues of extensors increased significantly (P<0.01) post-HYBT. HYBT increased all 3 eigenvalues. We suggest this might be caused by enlargement of muscle intracellular space. Copyright © 2014 Elsevier Inc. All rights reserved.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments.

PubMed

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D , observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄ . When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

PubMed Central

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561

MO-G-17A-07: Improved Image Quality in Brain F-18 FDG PET Using Penalized-Likelihood Image Reconstruction Via a Generalized Preconditioned Alternating Projection Algorithm: The First Patient Results

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

Schmidtlein, CR; Beattie, B; Humm, J

2014-06-15

Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1stmore » order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved with clinical OSEM reconstructions.« less

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

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

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.

Acoustic and elastic waveform inversion best practices

NASA Astrophysics Data System (ADS)

Modrak, Ryan T.

Reaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence, one or two test cases are not enough to reliably inform such decisions. We identify best practices instead using two global, one regional and four near-surface acoustic test problems. To obtain meaningful quantitative comparisons, we carry out hundreds acoustic inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that L-BFGS provides computational savings over nonlinear conjugate gradient methods in a wide variety of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization, and total variation regularization are effective in different contexts. Besides these issues, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details have a strong effect on computational cost, regardless of the chosen material parameterization or nonlinear optimization algorithm. Building on the acoustic inversion results, we carry out elastic experiments with four test problems, three objective functions, and four material parameterizations. The choice of parameterization for isotropic elastic media is found to be more complicated than previous studies suggests, with "wavespeed-like'' parameters performing well with phase-based objective functions and Lame parameters performing well with amplitude-based objective functions. Reliability and efficiency can be even harder to achieve in transversely isotropic elastic inversions because rotation angle parameters describing fast-axis direction are difficult to recover. Using Voigt or Chen-Tromp parameters avoids the need to include rotation angles explicitly and provides an effective strategy for anisotropic inversion. The need for flexible and portable workflow management tools for seismic inversion also poses a major challenge. In a final chapter, the software used to the carry out the above experiments is described and instructions for reproducing experimental results are given.

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.

Big Data-Based Approach to Detect, Locate, and Enhance the Stability of an Unplanned Microgrid Islanding

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

Jiang, Huaiguang; Li, Yan; Zhang, Yingchen

In this paper, a big data-based approach is proposed for the security improvement of an unplanned microgrid islanding (UMI). The proposed approach contains two major steps: the first step is big data analysis of wide-area monitoring to detect a UMI and locate it; the second step is particle swarm optimization (PSO)-based stability enhancement for the UMI. First, an optimal synchrophasor measurement device selection (OSMDS) and matching pursuit decomposition (MPD)-based spatial-temporal analysis approach is proposed to significantly reduce the volume of data while keeping appropriate information from the synchrophasor measurements. Second, a random forest-based ensemble learning approach is trained to detectmore » the UMI. When combined with grid topology, the UMI can be located. Then the stability problem of the UMI is formulated as an optimization problem and the PSO is used to find the optimal operational parameters of the UMI. An eigenvalue-based multiobjective function is proposed, which aims to improve the damping and dynamic characteristics of the UMI. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed approach.« less

Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.

PubMed

Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David

2017-01-01

We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.

Topology optimization of embedded piezoelectric actuators considering control spillover effects

NASA Astrophysics Data System (ADS)

Gonçalves, Juliano F.; De Leon, Daniel M.; Perondi, Eduardo A.

2017-02-01

This article addresses the problem of active structural vibration control by means of embedded piezoelectric actuators. The topology optimization method using the solid isotropic material with penalization (SIMP) approach is employed in this work to find the optimum design of actuators taken into account the control spillover effects. A coupled finite element model of the structure is derived assuming a two-phase material and this structural model is written into the state-space representation. The proposed optimization formulation aims to determine the distribution of piezoelectric material which maximizes the controllability for a given vibration mode. The undesirable effects of the feedback control on the residual modes are limited by including a spillover constraint term containing the residual controllability Gramian eigenvalues. The optimization of the shape and placement of the conventionally embedded piezoelectric actuators are performed using a Sequential Linear Programming (SLP) algorithm. Numerical examples are presented considering the control of the bending vibration modes for a cantilever and a fixed beam. A Linear-Quadratic Regulator (LQR) is synthesized for each case of controlled structure in order to compare the influence of the additional constraint.

Algorithm-Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices from a Limited Number of Samples

DTIC Science & Technology

2015-03-01

ALGORITHM—EIGENVALUE ESTIMATION OF HYPERSPECTRAL WISHART COVARIANCE MATRICES FROM A LIMITED NUMBER OF SAMPLES ECBC-TN-067 Avishai Ben- David ...NUMBER 6. AUTHOR(S) Ben- David , Avishai (ECBC) and Davidson, Charles E. (STC) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7...and published by Avishai Ben- David and Charles E. Davidson (Eigenvalue Estimation of Hyperspectral WishartCovariance Matrices from Limited Number of

Multigrid techniques for nonlinear eigenvalue probems: Solutions of a nonlinear Schroedinger eigenvalue problem in 2D and 3D

NASA Technical Reports Server (NTRS)

Costiner, Sorin; Taasan, Shlomo

1994-01-01

This paper presents multigrid (MG) techniques for nonlinear eigenvalue problems (EP) and emphasizes an MG algorithm for a nonlinear Schrodinger EP. The algorithm overcomes the mentioned difficulties combining the following techniques: an MG projection coupled with backrotations for separation of solutions and treatment of difficulties related to clusters of close and equal eigenvalues; MG subspace continuation techniques for treatment of the nonlinearity; an MG simultaneous treatment of the eigenvectors at the same time with the nonlinearity and with the global constraints. The simultaneous MG techniques reduce the large number of self consistent iterations to only a few or one MG simultaneous iteration and keep the solutions in a right neighborhood where the algorithm converges fast.

Asymptotics of eigenvalues and eigenvectors of Toeplitz matrices

NASA Astrophysics Data System (ADS)

Böttcher, A.; Bogoya, J. M.; Grudsky, S. M.; Maximenko, E. A.

2017-11-01

Analysis of the asymptotic behaviour of the spectral characteristics of Toeplitz matrices as the dimension of the matrix tends to infinity has a history of over 100 years. For instance, quite a number of versions of Szegő's theorem on the asymptotic behaviour of eigenvalues and of the so-called strong Szegő theorem on the asymptotic behaviour of the determinants of Toeplitz matrices are known. Starting in the 1950s, the asymptotics of the maximum and minimum eigenvalues were actively investigated. However, investigation of the individual asymptotics of all the eigenvalues and eigenvectors of Toeplitz matrices started only quite recently: the first papers on this subject were published in 2009-2010. A survey of this new field is presented here. Bibliography: 55 titles.

The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach

PubMed Central

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2015-01-01

This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence. Specifically, the value range of the maximum eigenvalue is partitioned into three subintervals: viruses tend to extinction very quickly or approach extinction or persist depending on into which subinterval the maximum eigenvalue of the propagation network falls. Consequently, computer virus can be contained by adjusting the propagation network so that its maximum eigenvalue falls into the desired subinterval. PMID:26222539

The role of hypoxia-inducible factor-1α and vascular endothelial growth factor in late-phase preconditioning with xenon, isoflurane and levosimendan in rat cardiomyocytes

PubMed Central

Goetzenich, Andreas; Hatam, Nima; Preuss, Stephanie; Moza, Ajay; Bleilevens, Christian; Roehl, Anna B.; Autschbach, Rüdiger; Bernhagen, Jürgen; Stoppe, Christian

2014-01-01

OBJECTIVES The protective effects of late-phase preconditioning can be triggered by several stimuli. Unfortunately, the transfer from bench to bedside still represents a challenge, as concomitant medication or diseases influence the complex signalling pathways involved. In an established model of primary neonatal rat cardiomyocytes, we analysed the cardioprotective effects of three different stimulating pharmaceuticals of clinical relevance. The effect of additional β-blocker treatment was studied as these were previously shown to negatively influence preconditioning. METHODS Twenty-four hours prior to hypoxia, cells pre-treated with or without metoprolol (0.55 µg/ml) were preconditioned with isoflurane, levosimendan or xenon. The influences of these stimuli on hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) as well as inducible and endothelial nitric synthase (iNOS/eNOS) and cyclooxygenase-2 (COX-2) were analysed by polymerase chain reaction and western blotting. The preconditioning was proved by trypan blue cell counts following 5 h of hypoxia and confirmed by fluorescence staining. RESULTS Five hours of hypoxia reduced cell survival in unpreconditioned control cells to 44 ± 4%. Surviving cell count was significantly higher in cells preconditioned either by 2 × 15 min isoflurane (70 ± 16%; P = 0.005) or by xenon (59 ± 8%; P = 0.049). Xenon-preconditioned cells showed a significantly elevated content of VEGF (0.025 ± 0.010 IDV [integrated density values when compared with GAPDH] vs 0.003 ± 0.006 IDV in controls; P = 0.0003). The protein expression of HIF-1α was increased both by levosimendan (0.563 ± 0.175 IDV vs 0.142 ± 0.042 IDV in controls; P = 0.0289) and by xenon (0.868 ± 0.222 IDV; P < 0.0001) pretreatment. A significant elevation of mRNA expression of iNOS was measureable following preconditioning by xenon but not by the other chosen stimuli. eNOS mRNA expression was found to be suppressed by β-blocker treatment for all stimuli. In our model, independently of the chosen stimulus, β-blocker treatment had no significant effect on cell survival. CONCLUSIONS We found that the stimulation of late-phase preconditioning involves several distinct pathways that are variably addressed by the different stimuli. In contrast to isoflurane treatment, xenon-induced preconditioning does not lead to an increase in COX-2 gene transcription but to a significant increase in HIF-1α and subsequently VEGF. PMID:24351506

The role of hypoxia-inducible factor-1α and vascular endothelial growth factor in late-phase preconditioning with xenon, isoflurane and levosimendan in rat cardiomyocytes.

PubMed

Goetzenich, Andreas; Hatam, Nima; Preuss, Stephanie; Moza, Ajay; Bleilevens, Christian; Roehl, Anna B; Autschbach, Rüdiger; Bernhagen, Jürgen; Stoppe, Christian

2014-03-01

The protective effects of late-phase preconditioning can be triggered by several stimuli. Unfortunately, the transfer from bench to bedside still represents a challenge, as concomitant medication or diseases influence the complex signalling pathways involved. In an established model of primary neonatal rat cardiomyocytes, we analysed the cardioprotective effects of three different stimulating pharmaceuticals of clinical relevance. The effect of additional β-blocker treatment was studied as these were previously shown to negatively influence preconditioning. Twenty-four hours prior to hypoxia, cells pre-treated with or without metoprolol (0.55 µg/ml) were preconditioned with isoflurane, levosimendan or xenon. The influences of these stimuli on hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) as well as inducible and endothelial nitric synthase (iNOS/eNOS) and cyclooxygenase-2 (COX-2) were analysed by polymerase chain reaction and western blotting. The preconditioning was proved by trypan blue cell counts following 5 h of hypoxia and confirmed by fluorescence staining. Five hours of hypoxia reduced cell survival in unpreconditioned control cells to 44 ± 4%. Surviving cell count was significantly higher in cells preconditioned either by 2 × 15 min isoflurane (70 ± 16%; P = 0.005) or by xenon (59 ± 8%; P = 0.049). Xenon-preconditioned cells showed a significantly elevated content of VEGF (0.025 ± 0.010 IDV [integrated density values when compared with GAPDH] vs 0.003 ± 0.006 IDV in controls; P = 0.0003). The protein expression of HIF-1α was increased both by levosimendan (0.563 ± 0.175 IDV vs 0.142 ± 0.042 IDV in controls; P = 0.0289) and by xenon (0.868 ± 0.222 IDV; P < 0.0001) pretreatment. A significant elevation of mRNA expression of iNOS was measureable following preconditioning by xenon but not by the other chosen stimuli. eNOS mRNA expression was found to be suppressed by β-blocker treatment for all stimuli. In our model, independently of the chosen stimulus, β-blocker treatment had no significant effect on cell survival. We found that the stimulation of late-phase preconditioning involves several distinct pathways that are variably addressed by the different stimuli. In contrast to isoflurane treatment, xenon-induced preconditioning does not lead to an increase in COX-2 gene transcription but to a significant increase in HIF-1α and subsequently VEGF.

Single-photon quantum key distribution in the presence of loss

NASA Astrophysics Data System (ADS)

Curty, Marcos; Moroder, Tobias

2007-05-01

We investigate two-way and one-way single-photon quantum key distribution (QKD) protocols in the presence of loss introduced by the quantum channel. Our analysis is based on a simple precondition for secure QKD in each case. In particular, the legitimate users need to prove that there exists no separable state (in the case of two-way QKD), or that there exists no quantum state having a symmetric extension (one-way QKD), that is compatible with the available measurements results. We show that both criteria can be formulated as a convex optimization problem known as a semidefinite program, which can be efficiently solved. Moreover, we prove that the solution to the dual optimization corresponds to the evaluation of an optimal witness operator that belongs to the minimal verification set of them for the given two-way (or one-way) QKD protocol. A positive expectation value of this optimal witness operator states that no secret key can be distilled from the available measurements results. We apply such analysis to several well-known single-photon QKD protocols under losses.

Swimming of an assembly of rigid spheres at low Reynolds number.

PubMed

Felderhof, B U

2014-11-01

A matrix formulation is derived for the calculation of the swimming speed and the power required for swimming of an assembly of rigid spheres immersed in a viscous fluid of infinite extent. The spheres may have arbitrary radii and may interact with elastic forces. The analysis is based on the Stokes mobility matrix of the set of spheres, defined in low Reynolds number hydrodynamics. For small amplitude, swimming optimization of the swimming speed at given power leads to an eigenvalue problem. The method allows straightforward calculation of the swimming performance of structures modeled as assemblies of interacting rigid spheres.

Random matrix theory and portfolio optimization in Moroccan stock exchange

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2015-09-01

In this work, we use random matrix theory to analyze eigenvalues and see if there is a presence of pertinent information by using Marčenko-Pastur distribution. Thus, we study cross-correlation among stocks of Casablanca Stock Exchange. Moreover, we clean correlation matrix from noisy elements to see if the gap between predicted risk and realized risk would be reduced. We also analyze eigenvectors components distributions and their degree of deviations by computing the inverse participation ratio. This analysis is a way to understand the correlation structure among stocks of Casablanca Stock Exchange portfolio.

Quantum chi-squared and goodness of fit testing

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

Temme, Kristan; Verstraete, Frank

2015-01-15

A quantum mechanical hypothesis test is presented for the hypothesis that a certain setup produces a given quantum state. Although the classical and the quantum problems are very much related to each other, the quantum problem is much richer due to the additional optimization over the measurement basis. A goodness of fit test for i.i.d quantum states is developed and a max-min characterization for the optimal measurement is introduced. We find the quantum measurement which leads both to the maximal Pitman and Bahadur efficiencies, and determine the associated divergence rates. We discuss the relationship of the quantum goodness of fitmore » test to the problem of estimating multiple parameters from a density matrix. These problems are found to be closely related and we show that the largest error of an optimal strategy, determined by the smallest eigenvalue of the Fisher information matrix, is given by the divergence rate of the goodness of fit test.« less

Pericardial application as a new route for implanting stem-cell cardiospheres to treat myocardial infarction.

PubMed

Zhang, Jianhua; Wu, Zheng; Fan, Zepei; Qin, Zixi; Wang, Yingwei; Chen, Jiayuan; Wu, Maoxiong; Chen, Yangxin; Wu, Changhao; Wang, Jingfeng

2018-06-01

Cardiospheres (CSps) are a promising new form of cardiac stem cells with advantage over other stem cells for myocardial regeneration, but direct implantation of CSps by conventional routes has been limited due to potential embolism. We have implanted CSps into the pericardial cavity and systematically demonstrated its efficacy regarding myocardial infarction. Stem cell potency and cell viability can be optimized in vitro prior to implantation by pre-conditioning CSps with pericardial fluid and hydrogel packing. Transplantation of optimized CSps into the pericardial cavity improved cardiac function and alleviated myocardial fibrosis, increased myocardial cell survival and promoted angiogenesis. Mechanistically, CSps are able to directly differentiate into cardiomyocytes in vivo and promote regeneration of myocardial cells and blood vessels through a paracrine effect with released growth factors as potential paracrine mediators. These findings establish a new strategy for therapeutic myocardial regeneration to treat myocardial infarction. Cardiospheres (CSps) are a new form of cardiac stem cells with an advantage over other stem cells for myocardial regeneration. However, direct implantation of CSps by conventional routes to treat myocardial infarction has been limited due to potential embolism. We have implanted CSps into the pericardial cavity and systematically assessed its efficacy on myocardial infarction. Preconditioning with pericardial fluid enhanced the activity of CSps and matrix hydrogel prolonged their viability. This shows that pretransplant optimization of stem cell potency and maintenance of cell viability can be achieved with CSps. Transplantation of optimized CSps into the pericardial cavity improved cardiac function and alleviated myocardial fibrosis in the non-infarcted area, and increased myocardial cell survival and promoted angiogenesis in the infarcted area. Mechanistically, CSps were able to directly differentiate into cardiomyocytes in vivo and promoted regeneration of myocardial cells and blood vessels in the infarcted area through a paracrine effect with released growth factors in pericardial cavity serving as possible paracrine mediators. This is the first demonstration of direct pericardial administration of pre-optimized CSps, and its effectiveness on myocardial infarction by functional and morphological outcomes with distinct mechanisms. These findings establish a new strategy for therapeutic myocardial regeneration to treat myocardial infarction. © 2018 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

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

Efficient swimming of an assembly of rigid spheres at low Reynolds number.

PubMed

Felderhof, B U

2015-08-01

The swimming of an assembly of rigid spheres immersed in a viscous fluid of infinite extent is studied in low-Reynolds-number hydrodynamics. The instantaneous swimming velocity and rate of dissipation are expressed in terms of the time-dependent displacements of sphere centers about their collective motion. For small-amplitude swimming with periodically oscillating displacements, optimization of the mean swimming speed at given mean power leads to an eigenvalue problem involving a velocity matrix and a power matrix. The corresponding optimal stroke permits generalization to large-amplitude motion in a model of spheres with harmonic interactions and corresponding actuating forces. The method allows straightforward calculation of the swimming performance of structures modeled as assemblies of interacting rigid spheres. A model of three collinear spheres with motion along the common axis is studied as an example.

Control of mechanical systems by the mixed "time and expenditure" criterion

NASA Astrophysics Data System (ADS)

Alesova, I. M.; Babadzanjanz, L. K.; Pototskaya, I. Yu.; Pupysheva, Yu. Yu.; Saakyan, A. T.

2018-05-01

The optimal controlled motion of a mechanical system, that is determined by the linear system ODE with constant coefficients and piecewise constant control components, is considered. The number of control switching points and the heights of control steps are considered as preset. The optimized functional is combination of classical time criteria and "Expenditure criteria", that is equal to the total area of all steps of all control components. In the absence of control, the solution of the system is equal to the sum of components (frequency components) corresponding to different eigenvalues of the matrix of the ODE system. Admissible controls are those that turn to zero (at a non predetermined time moment) the previously chosen frequency components of the solution. An algorithm for the finding of control switching points, based on the necessary minimum conditions for mixed criteria, is proposed.

Using parallel banded linear system solvers in generalized eigenvalue problems

NASA Technical Reports Server (NTRS)

Zhang, Hong; Moss, William F.

1993-01-01

Subspace iteration is a reliable and cost effective method for solving positive definite banded symmetric generalized eigenproblems, especially in the case of large scale problems. This paper discusses an algorithm that makes use of two parallel banded solvers in subspace iteration. A shift is introduced to decompose the banded linear systems into relatively independent subsystems and to accelerate the iterations. With this shift, an eigenproblem is mapped efficiently into the memories of a multiprocessor and a high speed-up is obtained for parallel implementations. An optimal shift is a shift that balances total computation and communication costs. Under certain conditions, we show how to estimate an optimal shift analytically using the decay rate for the inverse of a banded matrix, and how to improve this estimate. Computational results on iPSC/2 and iPSC/860 multiprocessors are presented.

Weak Value Amplification is Suboptimal for Estimation and Detection

NASA Astrophysics Data System (ADS)

Ferrie, Christopher; Combes, Joshua

2014-01-01

We show by using statistically rigorous arguments that the technique of weak value amplification does not perform better than standard statistical techniques for the tasks of single parameter estimation and signal detection. Specifically, we prove that postselection, a necessary ingredient for weak value amplification, decreases estimation accuracy and, moreover, arranging for anomalously large weak values is a suboptimal strategy. In doing so, we explicitly provide the optimal estimator, which in turn allows us to identify the optimal experimental arrangement to be the one in which all outcomes have equal weak values (all as small as possible) and the initial state of the meter is the maximal eigenvalue of the square of the system observable. Finally, we give precise quantitative conditions for when weak measurement (measurements without postselection or anomalously large weak values) can mitigate the effect of uncharacterized technical noise in estimation.

OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms

DOE PAGES

Meng, Zhaoyi; Koniges, Alice; He, Yun Helen; ...

2016-09-21

In this paper, we investigate the OpenMP parallelization and optimization of two novel data classification algorithms. The new algorithms are based on graph and PDE solution techniques and provide significant accuracy and performance advantages over traditional data classification algorithms in serial mode. The methods leverage the Nystrom extension to calculate eigenvalue/eigenvectors of the graph Laplacian and this is a self-contained module that can be used in conjunction with other graph-Laplacian based methods such as spectral clustering. We use performance tools to collect the hotspots and memory access of the serial codes and use OpenMP as the parallelization language to parallelizemore » the most time-consuming parts. Where possible, we also use library routines. We then optimize the OpenMP implementations and detail the performance on traditional supercomputer nodes (in our case a Cray XC30), and test the optimization steps on emerging testbed systems based on Intel’s Knights Corner and Landing processors. We show both performance improvement and strong scaling behavior. Finally, a large number of optimization techniques and analyses are necessary before the algorithm reaches almost ideal scaling.« less

Augmenting the one-shot framework by additional constraints

DOE PAGES

Bosse, Torsten

2016-05-12

The (multistep) one-shot method for design optimization problems has been successfully implemented for various applications. To this end, a slowly convergent primal fixed-point iteration of the state equation is augmented by an adjoint iteration and a corresponding preconditioned design update. In this paper we present a modification of the method that allows for additional equality constraints besides the usual state equation. Finally, a retardation analysis and the local convergence of the method in terms of necessary and sufficient conditions are given, which depend on key characteristics of the underlying problem and the quality of the utilized preconditioner.

Augmenting the one-shot framework by additional constraints

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

Bosse, Torsten

The (multistep) one-shot method for design optimization problems has been successfully implemented for various applications. To this end, a slowly convergent primal fixed-point iteration of the state equation is augmented by an adjoint iteration and a corresponding preconditioned design update. In this paper we present a modification of the method that allows for additional equality constraints besides the usual state equation. Finally, a retardation analysis and the local convergence of the method in terms of necessary and sufficient conditions are given, which depend on key characteristics of the underlying problem and the quality of the utilized preconditioner.

The Pasinetti-Solow Growth Model with Optimal Saving Behaviour: A Local Bifurcation Analysis

NASA Astrophysics Data System (ADS)

Commendatore, P.; Palmisani, C.

We present a discrete time version of the Pasinetti-Solow economic growth model. Workers and capitalists are assumed to save on the basis of rational choices. Workers face a finite time horizon and base their consumption choices on a life-cycle motive, whereas capitalists behave like an infinitely-lived dynasty. The accumulation of both capitalists' and workers' wealth through time is reduced to a two-dimensional map whose local asymptotic stability properties are studied. Various types of bifurcation emerge (flip, Neimark-Sacker, saddle-node and transcritical): a precondition for chaotic dynamics.

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Mini-batch optimized full waveform inversion with geological constrained gradient filtering

NASA Astrophysics Data System (ADS)

Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai

2018-05-01

High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.

Simultaneous multigrid techniques for nonlinear eigenvalue problems: Solutions of the nonlinear Schrödinger-Poisson eigenvalue problem in two and three dimensions

NASA Astrophysics Data System (ADS)

Costiner, Sorin; Ta'asan, Shlomo

1995-07-01

Algorithms for nonlinear eigenvalue problems (EP's) often require solving self-consistently a large number of EP's. Convergence difficulties may occur if the solution is not sought in an appropriate region, if global constraints have to be satisfied, or if close or equal eigenvalues are present. Multigrid (MG) algorithms for nonlinear problems and for EP's obtained from discretizations of partial differential EP have often been shown to be more efficient than single level algorithms. This paper presents MG techniques and a MG algorithm for nonlinear Schrödinger Poisson EP's. The algorithm overcomes the above mentioned difficulties combining the following techniques: a MG simultaneous treatment of the eigenvectors and nonlinearity, and with the global constrains; MG stable subspace continuation techniques for the treatment of nonlinearity; and a MG projection coupled with backrotations for separation of solutions. These techniques keep the solutions in an appropriate region, where the algorithm converges fast, and reduce the large number of self-consistent iterations to only a few or one MG simultaneous iteration. The MG projection makes it possible to efficiently overcome difficulties related to clusters of close and equal eigenvalues. Computational examples for the nonlinear Schrödinger-Poisson EP in two and three dimensions, presenting special computational difficulties that are due to the nonlinearity and to the equal and closely clustered eigenvalues are demonstrated. For these cases, the algorithm requires O(qN) operations for the calculation of q eigenvectors of size N and for the corresponding eigenvalues. One MG simultaneous cycle per fine level was performed. The total computational cost is equivalent to only a few Gauss-Seidel relaxations per eigenvector. An asymptotic convergence rate of 0.15 per MG cycle is attained.

Eigentime identities for on weighted polymer networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Tang, Hualong; Zou, Jiahui; He, Di; Sun, Yu; Su, Weiyi

2018-01-01

In this paper, we first analytically calculate the eigenvalues of the transition matrix of a structure with very complex architecture and their multiplicities. We call this structure polymer network. Based on the eigenvalues obtained in the iterative manner, we then calculate the eigentime identity. We highlight two scaling behaviors (logarithmic and linear) for this quantity, strongly depending on the value of the weight factor. Finally, by making use of the obtained eigenvalues, we determine the weighted counting of spanning trees.

A New Measure of Wireless Network Connectivity

DTIC Science & Technology

2014-10-31

matrix QG. From Lemma 1, QG is a non-zero nonnegative matrix. Thus from the Perron - Frobenius Theorem, [24], its largest magni- tude eigenvalue, known as...the Perron - Frobenius eigenvalue is real and positive. Further as QG is symmetric, all its eigenval- ues are real, and its largest magnitude...eigenvalue λmax(QG) is also its largest singular value. Also from the Perron - Frobenius Theorem, should the network be connected, i.e. QG is positive as opposed

Asymptotic theory of a slender rotating beam with end masses.

NASA Technical Reports Server (NTRS)

Whitman, A. M.; Abel, J. M.

1972-01-01

The method of matched asymptotic expansions is employed to solve the singular perturbation problem of the vibrations of a rotating beam of small flexural rigidity with concentrated end masses. The problem is complicated by the appearance of the eigenvalue in the boundary conditions. Eigenfunctions and eigenvalues are developed as power series in the perturbation parameter beta to the 1/2 power, and results are given for mode shapes and eigenvalues through terms of the order of beta.

Almost analytical Karhunen-Loeve representation of irregular waves based on the prolate spheroidal wave functions

NASA Astrophysics Data System (ADS)

Lee, Gibbeum; Cho, Yeunwoo

2017-11-01

We present an almost analytical new approach to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of solving this matrix eigenvalue problem purely numerically, which may suffer from the computational inaccuracy for big data, first, we consider a pair of integral and differential equations, which are related to the so-called prolate spheroidal wave functions (PSWF). For the PSWF differential equation, the pair of the eigenvectors (PSWF) and eigenvalues can be obtained from a relatively small number of analytical Legendre functions. Then, the eigenvalues in the PSWF integral equation are expressed in terms of functional values of the PSWF and the eigenvalues of the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data; ordinary irregular waves and rogue waves. We found that the present almost analytical method is better than the conventional data-independent Fourier representation and, also, the conventional direct numerical K-L representation in terms of both accuracy and computational cost. This work was supported by the National Research Foundation of Korea (NRF). (NRF-2017R1D1A1B03028299).

The wasteland of random supergravities

NASA Astrophysics Data System (ADS)

Marsh, David; McAllister, Liam; Wrase, Timm

2012-03-01

We show that in a general {N} = {1} supergravity with N ≫ 1 scalar fields, an exponentially small fraction of the de Sitter critical points are metastable vacua. Taking the superpotential and Kähler potential to be random functions, we construct a random matrix model for the Hessian matrix, which is well-approximated by the sum of a Wigner matrix and two Wishart matrices. We compute the eigenvalue spectrum analytically from the free convolution of the constituent spectra and find that in typical configurations, a significant fraction of the eigenvalues are negative. Building on the Tracy-Widom law governing fluctuations of extreme eigenvalues, we determine the probability P of a large fluctuation in which all the eigenvalues become positive. Strong eigenvalue repulsion makes this extremely unlikely: we find P ∝ exp(- c N p ), with c, p being constants. For generic critical points we find p ≈ 1 .5, while for approximately-supersymmetric critical points, p ≈ 1 .3. Our results have significant implications for the counting of de Sitter vacua in string theory, but the number of vacua remains vast.

Shape sensitivity analysis of flutter response of a laminated wing

NASA Technical Reports Server (NTRS)

Bergen, Fred D.; Kapania, Rakesh K.

1988-01-01

A method is presented for calculating the shape sensitivity of a wing aeroelastic response with respect to changes in geometric shape. Yates' modified strip method is used in conjunction with Giles' equivalent plate analysis to predict the flutter speed, frequency, and reduced frequency of the wing. Three methods are used to calculate the sensitivity of the eigenvalue. The first method is purely a finite difference calculation of the eigenvalue derivative directly from the solution of the flutter problem corresponding to the two different values of the shape parameters. The second method uses an analytic expression for the eigenvalue sensitivities of a general complex matrix, where the derivatives of the aerodynamic, mass, and stiffness matrices are computed using a finite difference approximation. The third method also uses an analytic expression for the eigenvalue sensitivities, but the aerodynamic matrix is computed analytically. All three methods are found to be in good agreement with each other. The sensitivities of the eigenvalues were used to predict the flutter speed, frequency, and reduced frequency. These approximations were found to be in good agreement with those obtained using a complete reanalysis.

Kelch-like ECH-associated Protein 1-dependent Nuclear Factor-E2-related Factor 2 Activation in Relation to Antioxidation Induced by Sevoflurane Preconditioning.

PubMed

Cai, Min; Tong, Li; Dong, Beibei; Hou, Wugang; Shi, Likai; Dong, Hailong

2017-03-01

The authors have reported that antioxidative effects play a crucial role in the volatile anesthetic-induced neuroprotection. Accumulated evidence shows that endogenous antioxidation could be up-regulated by nuclear factor-E2-related factor 2 through multiple pathways. However, whether nuclear factor-E2-related factor 2 activation is modulated by sevoflurane preconditioning and, if so, what is the signaling cascade underlying upstream of this activation are still unknown. Sevoflurane preconditioning in mice was performed with sevoflurane (2.5%) 1 h per day for five consecutive days. Focal cerebral ischemia/reperfusion injury was induced by middle cerebral artery occlusion. Expression of nuclear factor-E2-related factor 2, kelch-like ECH-associated protein 1, manganese superoxide dismutase, thioredoxin-1, and nicotinamide adenine dinucleotide phosphate quinolone oxidoreductase-1 was detected (n = 6). The antioxidant activities and oxidative product expression were also examined. To determine the role of kelch-like ECH-associated protein 1 inhibition-dependent nuclear factor-E2-related factor 2 activation in sevoflurane preconditioning-induced neuroprotection, the kelch-like ECH-associated protein 1-nuclear factor-E2-related factor 2 signal was modulated by nuclear factor-E2-related factor 2 knockout, kelch-like ECH-associated protein 1 overexpression lentivirus, and kelch-like ECH-associated protein 1 deficiency small interfering RNA (n = 8). The infarct volume, neurologic scores, and cellular apoptosis were assessed. Sevoflurane preconditioning elicited neuroprotection and increased nuclear factor-E2-related factor 2 nuclear translocation, which in turn up-regulated endogenous antioxidation and reduced oxidative injury. Sevoflurane preconditioning reduced kelch-like ECH-associated protein 1 expression. Nuclear factor-E2-related factor 2 ablation abolished neuroprotection and reversed sevoflurane preconditioning by mediating the up-regulation of antioxidants. Kelch-like ECH-associated protein 1 overexpression reversed nuclear factor-E2-related factor 2 up-regulation and abolished the neuroprotection induced by sevoflurane preconditioning. Kelch-like ECH-associated protein 1 small interfering RNA administration improved nuclear factor-E2-related factor 2 expression and the outcome of mice subjected to ischemia/reperfusion injury. Kelch-like ECH-associated protein 1 down-regulation-dependent nuclear factor-E2-related factor 2 activation underlies the ability of sevoflurane preconditioning to activate the endogenous antioxidant response, which elicits its neuroprotection.

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 hypoxia-exposed or hypoxic preconditioned cells. ► SIRT1 deacetylates c-Myc and β-catenin ► HIF-1α is up-regulated by down-regulation of c-Myc and β-catenin expression. ► Polyphenolic SIRT1 activators mimics hypoxic preconditioning.« less

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.

The involvement of protein kinase C-ε in isoflurane induced preconditioning of human embryonic stem cell--derived Nkx2.5(+) cardiac progenitor cells.

PubMed

Song, In-Ae; Oh, Ah-Young; Kim, Jin-Hee; Choi, Young-Min; Jeon, Young-Tae; Ryu, Jung-Hee; Hwang, Jung-Won

2016-02-20

Anesthetic preconditioning can improve survival of cardiac progenitor cells exposed to oxidative stress. We investigated the role of protein kinase C and isoform protein kinase C-ε in isoflurane-induced preconditioning of cardiac progenitor cells exposed to oxidative stress. Cardiac progenitor cells were obtained from undifferentiated human embryonic stem cells. Immunostaining with anti-Nkx2.5 was used to confirm the differentiated cardiac progenitor cells. Oxidative stress was induced by H2O2 and FeSO4. For anesthetic preconditioning, cardiac progenitor cells were exposed to 0.25, 0.5, and 1.0 mM of isoflurane. PMA and chelerythrine were used for protein kinase C activation and inhibition, while εψRACK and εV1-2 were used for protein kinase C -ε activation and inhibition, respectively. Isoflurane-preconditioning decreased the death rate of Cardiac progenitor cells exposed to oxidative stress (death rates isoflurane 0.5 mM 12.7 ± 9.3%, 1.0 mM 12.0 ± 7.7% vs. control 31.4 ± 10.2%). Inhibitors of both protein kinase C and protein kinase C -ε abolished the preconditioning effect of isoflurane 0.5 mM (death rates 27.6 ± 13.5% and 25.9 ± 8.7% respectively), and activators of both protein kinase C and protein kinase C - ε had protective effects from oxidative stress (death rates 16.0 ± 3.2% and 10.6 ± 3.8% respectively). Both PKC and PKC-ε are involved in isoflurane-induced preconditioning of human embryonic stem cells -derived Nkx2.5(+) Cardiac progenitor cells under oxidative stress.

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.

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

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

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.

The eigenvalue problem in phase space.

PubMed

Cohen, Leon

2018-06-30

We formulate the standard quantum mechanical eigenvalue problem in quantum phase space. The equation obtained involves the c-function that corresponds to the quantum operator. We use the Wigner distribution for the phase space function. We argue that the phase space eigenvalue equation obtained has, in addition to the proper solutions, improper solutions. That is, solutions for which no wave function exists which could generate the distribution. We discuss the conditions for ascertaining whether a position momentum function is a proper phase space distribution. We call these conditions psi-representability conditions, and show that if these conditions are imposed, one extracts the correct phase space eigenfunctions. We also derive the phase space eigenvalue equation for arbitrary phase space distributions functions. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A multilevel finite element method for Fredholm integral eigenvalue problems

NASA Astrophysics Data System (ADS)

Xie, Hehu; Zhou, Tao

2015-12-01

In this work, we proposed a multigrid finite element (MFE) method for solving the Fredholm integral eigenvalue problems. The main motivation for such studies is to compute the Karhunen-Loève expansions of random fields, which play an important role in the applications of uncertainty quantification. In our MFE framework, solving the eigenvalue problem is converted to doing a series of integral iterations and eigenvalue solving in the coarsest mesh. Then, any existing efficient integration scheme can be used for the associated integration process. The error estimates are provided, and the computational complexity is analyzed. It is noticed that the total computational work of our method is comparable with a single integration step in the finest mesh. Several numerical experiments are presented to validate the efficiency of the proposed numerical method.

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.

Method for computing self-consistent solution in a gun code

DOEpatents

Nelson, Eric M

2014-09-23

Complex gun code computations can be made to converge more quickly based on a selection of one or more relaxation parameters. An eigenvalue analysis is applied to error residuals to identify two error eigenvalues that are associated with respective error residuals. Relaxation values can be selected based on these eigenvalues so that error residuals associated with each can be alternately reduced in successive iterations. In some examples, relaxation values that would be unstable if used alone can be used.

PT-symmetric eigenvalues for homogeneous potentials

NASA Astrophysics Data System (ADS)

Eremenko, Alexandre; Gabrielov, Andrei

2018-05-01

We consider one-dimensional Schrödinger equations with potential x2M(ix)ɛ, where M ≥ 1 is an integer and ɛ is real, under appropriate parity and time (PT)-symmetric boundary conditions. We prove the phenomenon which was discovered by Bender and Boettcher by numerical computation: as ɛ changes, the real spectrum suddenly becomes non-real in the sense that all but finitely many eigenvalues become non-real. We find the limit arguments of these non-real eigenvalues E as E → ∞.

Spectral properties of Google matrix of Wikipedia and other networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2013-05-01

We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method, we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between PageRank and CheiRank vectors distinguishes different organizations of information flow on BBC and Le Monde web sites.

An accurate method for solving a class of fractional Sturm-Liouville eigenvalue problems

NASA Astrophysics Data System (ADS)

Kashkari, Bothayna S. H.; Syam, Muhammed I.

2018-06-01

This article is devoted to both theoretical and numerical study of the eigenvalues of nonsingular fractional second-order Sturm-Liouville problem. In this paper, we implement a fractional-order Legendre Tau method to approximate the eigenvalues. This method transforms the Sturm-Liouville problem to a sparse nonsingular linear system which is solved using the continuation method. Theoretical results for the considered problem are provided and proved. Numerical results are presented to show the efficiency of the proposed method.

Spatial Search by Quantum Walk is Optimal for Almost all Graphs.

PubMed

Chakraborty, Shantanav; Novo, Leonardo; Ambainis, Andris; Omar, Yasser

2016-03-11

The problem of finding a marked node in a graph can be solved by the spatial search algorithm based on continuous-time quantum walks (CTQW). However, this algorithm is known to run in optimal time only for a handful of graphs. In this work, we prove that for Erdös-Renyi random graphs, i.e., graphs of n vertices where each edge exists with probability p, search by CTQW is almost surely optimal as long as p≥log^{3/2}(n)/n. Consequently, we show that quantum spatial search is in fact optimal for almost all graphs, meaning that the fraction of graphs of n vertices for which this optimality holds tends to one in the asymptotic limit. We obtain this result by proving that search is optimal on graphs where the ratio between the second largest and the largest eigenvalue is bounded by a constant smaller than 1. Finally, we show that we can extend our results on search to establish high fidelity quantum communication between two arbitrary nodes of a random network of interacting qubits, namely, to perform quantum state transfer, as well as entanglement generation. Our work shows that quantum information tasks typically designed for structured systems retain performance in very disordered structures.

A "Reverse-Schur" Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design.

PubMed

Bardhan, Jaydeep P; Altman, Michael D; Tidor, B; White, Jacob K

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule's electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts-in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method.

A “Reverse-Schur” Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design

PubMed Central

Bardhan, Jaydeep P.; Altman, Michael D.

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule’s electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts–in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method. PMID:23055839

Statistical inference methods for sparse biological time series data.

PubMed

Ndukum, Juliet; Fonseca, Luís L; Santos, Helena; Voit, Eberhard O; Datta, Susmita

2011-04-25

Comparing metabolic profiles under different biological perturbations has become a powerful approach to investigating the functioning of cells. The profiles can be taken as single snapshots of a system, but more information is gained if they are measured longitudinally over time. The results are short time series consisting of relatively sparse data that cannot be analyzed effectively with standard time series techniques, such as autocorrelation and frequency domain methods. In this work, we study longitudinal time series profiles of glucose consumption in the yeast Saccharomyces cerevisiae under different temperatures and preconditioning regimens, which we obtained with methods of in vivo nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis we first fit several nonlinear mixed effect regression models to the longitudinal profiles and then used an ANOVA likelihood ratio method in order to test for significant differences between the profiles. The proposed methods are capable of distinguishing metabolic time trends resulting from different treatments and associate significance levels to these differences. Among several nonlinear mixed-effects regression models tested, a three-parameter logistic function represents the data with highest accuracy. ANOVA and likelihood ratio tests suggest that there are significant differences between the glucose consumption rate profiles for cells that had been--or had not been--preconditioned by heat during growth. Furthermore, pair-wise t-tests reveal significant differences in the longitudinal profiles for glucose consumption rates between optimal conditions and heat stress, optimal and recovery conditions, and heat stress and recovery conditions (p-values <0.0001). We have developed a nonlinear mixed effects model that is appropriate for the analysis of sparse metabolic and physiological time profiles. The model permits sound statistical inference procedures, based on ANOVA likelihood ratio tests, for testing the significance of differences between short time course data under different biological perturbations.

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.

Preconditioning of bone marrow-derived mesenchymal stromal cells by tetramethylpyrazine enhances cell migration and improves functional recovery after focal cerebral ischemia in rats.

PubMed

Li, Lin; Chu, Lisheng; Fang, Yan; Yang, Yan; Qu, Tiebing; Zhang, Jianping; Yin, Yuanjun; Gu, Jingjing

2017-05-12

Transplantation of bone marrow-derived mesenchymal stem cells (BMSCs) is one of the new therapeutic strategies for treating ischemic stroke. However, the relatively poor migratory capacity of BMSCs toward infarcted regions limited the therapeutic potential of this approach. Pharmacological preconditioning can increase the expression of CXC chemokine receptor 4 (CXCR4) in BMSCs and enhance cell migration toward the injury site. In the present study, we investigated whether tetramethylpyrazine (TMP) preconditioning could enhance BMSCs migration to the ischemic brain and improve functional recovery through upregulating CXCR4 expression. BMSCs were identified by flow cytometry analysis. BMSCs migration was evaluated in vitro by transwell migration assay, and CXCR4 expression was measured by quantitative reverse transcription-polymerase chain reaction and western blot analysis. In rats with focal cerebral ischemia, the neurological function was evaluated by the modified neurological severity score, the adhesive removal test and the corner test. The homing BMSCs and angiogenesis were detected by immunofluorescence, and expression of stromal cell-derived factor-1 (SDF-1) and CXCR4 was measured by western blot analysis. Flow cytometry analysis demonstrated that BMSCs expressed CD29 and CD90, but not CD34 and CD45. TMP pretreatment dose-dependently induced BMSCs migration and CXCR4 expression in vitro, which was significantly inhibited by AMD3100, a CXCR4 antagonist. In rat stroke models, we found more TMP-preconditioned BMSCs homing toward the infarcted regions than nonpreconditioned cells, leading to improved neurological performance and enhanced angiogenesis. Moreover, TMP-preconditioned BMSCs significantly upregulated the protein expression of SDF-1 and CXCR4 in the ischemic boundary regions. These beneficial effects of TMP preconditioning were blocked by AMD3100. TMP preconditioning enhances the migration and homing ability of BMSCs, increases CXCR4 expression, promotes angiogenesis, and improves neurological performance. Therefore, TMP preconditioning may be an effective strategy to improve the therapeutic potency of BMSCs for ischemic stroke due to enhanced BMSCs migration to ischemic regions.

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 effect could not be added to that of ischemic or metabolic preconditioning in these models.

Preconditioning of adipose tissue-derived mesenchymal stem cells with deferoxamine increases the production of pro-angiogenic, neuroprotective and anti-inflammatory factors: Potential application in the treatment of diabetic neuropathy.

PubMed

Oses, Carolina; Olivares, Belén; Ezquer, Marcelo; Acosta, Cristian; Bosch, Paul; Donoso, Macarena; Léniz, Patricio; Ezquer, Fernando

2017-01-01

Diabetic neuropathy (DN) is one of the most frequent and troublesome complications of diabetes mellitus. Evidence from diabetic animal models and diabetic patients suggests that reduced availability of neuroprotective and pro-angiogenic factors in the nerves in combination with a chronic pro-inflammatory microenvironment and high level of oxidative stress, contribute to the pathogenesis of DN. Mesenchymal stem cells (MSCs) are of great interest as therapeutic agents for regenerative purposes, since they can secrete a broad range of cytoprotective and anti-inflammatory factors. Therefore, the use of the MSC secretome may represent a promising approach for DN treatment. Recent data indicate that the paracrine potential of MSCs could be boosted by preconditioning these cells with an environmental or pharmacological stimulus, enhancing their therapeutic efficacy. In the present study, we observed that the preconditioning of human adipose tissue-derived MSCs (AD-MSCs) with 150μM or 400μM of the iron chelator deferoxamine (DFX) for 48 hours, increased the abundance of the hypoxia inducible factor 1 alpha (HIF-1α) in a concentration dependent manner, without affecting MSC morphology and survival. Activation of HIF-1α led to the up-regulation of the mRNA levels of pro-angiogenic factors like vascular endothelial growth factor alpha and angiopoietin 1. Furthermore this preconditioning increased the expression of potent neuroprotective factors, including nerve growth factor, glial cell-derived neurotrophic factor and neurotrophin-3, and cytokines with anti-inflammatory activity like IL4 and IL5. Additionally, we observed that these molecules, which could also be used as therapeutics, were also increased in the secretome of MSCs preconditioned with DFX compared to the secretome obtained from non-preconditioned cells. Moreover, DFX preconditioning significantly increased the total antioxidant capacity of the MSC secretome and they showed neuroprotective effects when evaluated in an in vitro model of DN. Altogether, our findings suggest that DFX preconditioning of AD-MSCs improves their therapeutic potential and should be considered as a potential strategy for the generation of new alternatives for DN treatment.

Preconditioning of adipose tissue-derived mesenchymal stem cells with deferoxamine increases the production of pro-angiogenic, neuroprotective and anti-inflammatory factors: Potential application in the treatment of diabetic neuropathy

PubMed Central

Oses, Carolina; Olivares, Belén; Ezquer, Marcelo; Acosta, Cristian; Bosch, Paul; Donoso, Macarena; Léniz, Patricio

2017-01-01

Diabetic neuropathy (DN) is one of the most frequent and troublesome complications of diabetes mellitus. Evidence from diabetic animal models and diabetic patients suggests that reduced availability of neuroprotective and pro-angiogenic factors in the nerves in combination with a chronic pro-inflammatory microenvironment and high level of oxidative stress, contribute to the pathogenesis of DN. Mesenchymal stem cells (MSCs) are of great interest as therapeutic agents for regenerative purposes, since they can secrete a broad range of cytoprotective and anti-inflammatory factors. Therefore, the use of the MSC secretome may represent a promising approach for DN treatment. Recent data indicate that the paracrine potential of MSCs could be boosted by preconditioning these cells with an environmental or pharmacological stimulus, enhancing their therapeutic efficacy. In the present study, we observed that the preconditioning of human adipose tissue-derived MSCs (AD-MSCs) with 150μM or 400μM of the iron chelator deferoxamine (DFX) for 48 hours, increased the abundance of the hypoxia inducible factor 1 alpha (HIF-1α) in a concentration dependent manner, without affecting MSC morphology and survival. Activation of HIF-1α led to the up-regulation of the mRNA levels of pro-angiogenic factors like vascular endothelial growth factor alpha and angiopoietin 1. Furthermore this preconditioning increased the expression of potent neuroprotective factors, including nerve growth factor, glial cell-derived neurotrophic factor and neurotrophin-3, and cytokines with anti-inflammatory activity like IL4 and IL5. Additionally, we observed that these molecules, which could also be used as therapeutics, were also increased in the secretome of MSCs preconditioned with DFX compared to the secretome obtained from non-preconditioned cells. Moreover, DFX preconditioning significantly increased the total antioxidant capacity of the MSC secretome and they showed neuroprotective effects when evaluated in an in vitro model of DN. Altogether, our findings suggest that DFX preconditioning of AD-MSCs improves their therapeutic potential and should be considered as a potential strategy for the generation of new alternatives for DN treatment. PMID:28542352

A control system design approach for flexible spacecraft

NASA Technical Reports Server (NTRS)

Silverberg, L. M.

1985-01-01

A control system design approach for flexible spacecraft is presented. The control system design is carried out in two steps. The first step consists of determining the ideal control system in terms of a desirable dynamic performance. The second step consists of designing a control system using a limited number of actuators that possess a dynamic performance that is close to the ideal dynamic performance. The effects of using a limited number of actuators is that the actual closed-loop eigenvalues differ from the ideal closed-loop eigenvalues. A method is presented to approximate the actual closed-loop eigenvalues so that the calculation of the actual closed-loop eigenvalues can be avoided. Depending on the application, it also may be desirable to apply the control forces as impulses. The effect of digitizing the control to produce the appropriate impulses is also examined.

Fine structure of spectral properties for random correlation matrices: An application to financial markets

NASA Astrophysics Data System (ADS)

Livan, Giacomo; Alfarano, Simone; Scalas, Enrico

2011-07-01

We study some properties of eigenvalue spectra of financial correlation matrices. In particular, we investigate the nature of the large eigenvalue bulks which are observed empirically, and which have often been regarded as a consequence of the supposedly large amount of noise contained in financial data. We challenge this common knowledge by acting on the empirical correlation matrices of two data sets with a filtering procedure which highlights some of the cluster structure they contain, and we analyze the consequences of such filtering on eigenvalue spectra. We show that empirically observed eigenvalue bulks emerge as superpositions of smaller structures, which in turn emerge as a consequence of cross correlations between stocks. We interpret and corroborate these findings in terms of factor models, and we compare empirical spectra to those predicted by random matrix theory for such models.

The Theory of Quantized Fields. III

DOE R&D Accomplishments Database

Schwinger, J.

1953-05-01

In this paper we discuss the electromagnetic field, as perturbed by a prescribed current. All quantities of physical interest in various situations, eigenvalues, eigenfunctions, and transformation probabilities, are derived from a general transformation function which is expressed in a non-Hermitian representation. The problems treated are: the determination of the energy-momentum eigenvalues and eigenfunctions for the isolated electromagnetic field, and the energy eigenvalues and eigenfunctions for the field perturbed by a time-independent current that departs from zero only within a finite time interval, and for a time-dependent current that assumes non-vanishing time-independent values initially and finally. The results are applied in a discussion of the intra-red catastrophe and of the adiabatic theorem. It is shown how the latter can be exploited to give a uniform formulation for all problems requiring the evaluation of transition probabilities or eigenvalue displacements.

Multigrid method for stability problems

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo

1988-01-01

The problem of calculating the stability of steady state solutions of differential equations is addressed. Leading eigenvalues of large matrices that arise from discretization are calculated, and an efficient multigrid method for solving these problems is presented. The resulting grid functions are used as initial approximations for appropriate eigenvalue problems. The method employs local relaxation on all levels together with a global change on the coarsest level only, which is designed to separate the different eigenfunctions as well as to update their corresponding eigenvalues. Coarsening is done using the FAS formulation in a nonstandard way in which the right-hand side of the coarse grid equations involves unknown parameters to be solved on the coarse grid. This leads to a new multigrid method for calculating the eigenvalues of symmetric problems. Numerical experiments with a model problem are presented which demonstrate the effectiveness of the method.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Computing eigenfunctions and eigenvalues of boundary-value problems with the orthogonal spectral renormalization method

NASA Astrophysics Data System (ADS)

Cartarius, Holger; Musslimani, Ziad H.; Schwarz, Lukas; Wunner, Günter

2018-03-01

The spectral renormalization method was introduced in 2005 as an effective way to compute ground states of nonlinear Schrödinger and Gross-Pitaevskii type equations. In this paper, we introduce an orthogonal spectral renormalization (OSR) method to compute ground and excited states (and their respective eigenvalues) of linear and nonlinear eigenvalue problems. The implementation of the algorithm follows four simple steps: (i) reformulate the underlying eigenvalue problem as a fixed-point equation, (ii) introduce a renormalization factor that controls the convergence properties of the iteration, (iii) perform a Gram-Schmidt orthogonalization process in order to prevent the iteration from converging to an unwanted mode, and (iv) compute the solution sought using a fixed-point iteration. The advantages of the OSR scheme over other known methods (such as Newton's and self-consistency) are (i) it allows the flexibility to choose large varieties of initial guesses without diverging, (ii) it is easy to implement especially at higher dimensions, and (iii) it can easily handle problems with complex and random potentials. The OSR method is implemented on benchmark Hermitian linear and nonlinear eigenvalue problems as well as linear and nonlinear non-Hermitian PT -symmetric models.

A new method for computation of eigenvector derivatives with distinct and repeated eigenvalues in structural dynamic analysis

NASA Astrophysics Data System (ADS)

Li, Zhengguang; Lai, Siu-Kai; Wu, Baisheng

2018-07-01

Determining eigenvector derivatives is a challenging task due to the singularity of the coefficient matrices of the governing equations, especially for those structural dynamic systems with repeated eigenvalues. An effective strategy is proposed to construct a non-singular coefficient matrix, which can be directly used to obtain the eigenvector derivatives with distinct and repeated eigenvalues. This approach also has an advantage that only requires eigenvalues and eigenvectors of interest, without solving the particular solutions of eigenvector derivatives. The Symmetric Quasi-Minimal Residual (SQMR) method is then adopted to solve the governing equations, only the existing factored (shifted) stiffness matrix from an iterative eigensolution such as the subspace iteration method or the Lanczos algorithm is utilized. The present method can deal with both cases of simple and repeated eigenvalues in a unified manner. Three numerical examples are given to illustrate the accuracy and validity of the proposed algorithm. Highly accurate approximations to the eigenvector derivatives are obtained within a few iteration steps, making a significant reduction of the computational effort. This method can be incorporated into a coupled eigensolver/derivative software module. In particular, it is applicable for finite element models with large sparse matrices.

Edge connectivity and the spectral gap of combinatorial and quantum graphs

NASA Astrophysics Data System (ADS)

Berkolaiko, Gregory; Kennedy, James B.; Kurasov, Pavel; Mugnolo, Delio

2017-09-01

We derive a number of upper and lower bounds for the first nontrivial eigenvalue of Laplacians on combinatorial and quantum graph in terms of the edge connectivity, i.e. the minimal number of edges which need to be removed to make the graph disconnected. On combinatorial graphs, one of the bounds corresponds to a well-known inequality of Fiedler, of which we give a new variational proof. On quantum graphs, the corresponding bound generalizes a recent result of Band and Lévy. All proofs are general enough to yield corresponding estimates for the p-Laplacian and allow us to identify the minimizers. Based on the Betti number of the graph, we also derive upper and lower bounds on all eigenvalues which are ‘asymptotically correct’, i.e. agree with the Weyl asymptotics for the eigenvalues of the quantum graph. In particular, the lower bounds improve the bounds of Friedlander on any given graph for all but finitely many eigenvalues, while the upper bounds improve recent results of Ariturk. Our estimates are also used to derive bounds on the eigenvalues of the normalized Laplacian matrix that improve known bounds of spectral graph theory.

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.

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.

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.

Major role of the PI3K/Akt pathway in ischemic tolerance induced by sublethal oxygen-glucose deprivation in cortical neurons in vitro.

PubMed

Bhuiyan, Mohammad Iqbal Hossain; Jung, Seo Yun; Kim, Hyoung Ja; Lee, Yong Sup; Jin, Changbae

2011-06-01

Ischemic preconditioning can provide protection to neurons from subsequent lethal ischemia. The molecular mechanisms of neuronal ischemic tolerance, however, are still not well-known. The present study, therefore, examined the role of MAPK and PI3K/Akt pathways in ischemic tolerance induced by preconditioning with sublethal oxygen-glucose deprivation (OGD) in cultured rat cortical neurons. Ischemic tolerance was simulated by preconditioning of the neurons with sublethal 1-h OGD imposed 12 h before lethal 3-h OGD. The time-course studies of relative phosphorylation and expression levels of ERK1/2, JNK and p38 MAPK showed lack of their involvement in ischemic tolerance. However, there were significant increases in Akt phosphorylation levels during the reperfusion period following preconditioned lethal OGD. In addition, Bcl-2 associated death promoter (Bad) and GSK-3β were also found to be inactivated during that reperfusion period. Finally, treatment with an inhibitor of PI3K, wortmannin, applied from 15 min before and during lethal OGD abolished not only the preconditioning-induced neuroprotection but also the Akt activation. Concomitant with blockade of the Akt activation, PI3K inhibition also resulted in activation of Bad and GSK-3β. The results suggest that ischemic tolerance induced by sublethal OGD preconditioning is primarily mediated through activation of the PI3K/Akt pathway, but not the MAPK pathway, in rat cortical neurons.

Parallel and Portable Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Lee, S. R.; Cummings, J. C.; Nolen, S. D.; Keen, N. D.

1997-08-01

We have developed a multi-group, Monte Carlo neutron transport code in C++ using object-oriented methods and the Parallel Object-Oriented Methods and Applications (POOMA) class library. This transport code, called MC++, currently computes k and α eigenvalues of the neutron transport equation on a rectilinear computational mesh. It is portable to and runs in parallel on a wide variety of platforms, including MPPs, clustered SMPs, and individual workstations. It contains appropriate classes and abstractions for particle transport and, through the use of POOMA, for portable parallelism. Current capabilities are discussed, along with physics and performance results for several test problems on a variety of hardware, including all three Accelerated Strategic Computing Initiative (ASCI) platforms. Current parallel performance indicates the ability to compute α-eigenvalues in seconds or minutes rather than days or weeks. Current and future work on the implementation of a general transport physics framework (TPF) is also described. This TPF employs modern C++ programming techniques to provide simplified user interfaces, generic STL-style programming, and compile-time performance optimization. Physics capabilities of the TPF will be extended to include continuous energy treatments, implicit Monte Carlo algorithms, and a variety of convergence acceleration techniques such as importance combing.

Understanding transient uncoupling induced synchronization through modified dynamic coupling

NASA Astrophysics Data System (ADS)

Ghosh, Anupam; Godara, Prakhar; Chakraborty, Sagar

2018-05-01

An important aspect of the recently introduced transient uncoupling scheme is that it induces synchronization for large values of coupling strength at which the coupled chaotic systems resist synchronization when continuously coupled. However, why this is so is an open problem? To answer this question, we recall the conventional wisdom that the eigenvalues of the Jacobian of the transverse dynamics measure whether a trajectory at a phase point is locally contracting or diverging with respect to another nearby trajectory. Subsequently, we go on to highlight a lesser appreciated fact that even when, under the corresponding linearised flow, the nearby trajectory asymptotically diverges away, its distance from the reference trajectory may still be contracting for some intermediate period. We term this phenomenon transient decay in line with the phenomenon of the transient growth. Using these facts, we show that an optimal coupling region, i.e., a region of the phase space where coupling is on, should ideally be such that at any of the constituent phase point either the maximum of the real parts of the eigenvalues is negative or the magnitude of the positive maximum is lesser than that of the negative minimum. We also invent and employ a modified dynamics coupling scheme—a significant improvement over the well-known dynamic coupling scheme—as a decisive tool to justify our results.

Optimal trajectories for aeroassisted orbital transfer

NASA Technical Reports Server (NTRS)

Miele, A.; Venkataraman, P.

1983-01-01

Consideration is given to classical and minimax problems involved in aeroassisted transfer from high earth orbit (HEO) to low earth orbit (LEO). The transfer is restricted to coplanar operation, with trajectory control effected by means of lift modulation. The performance of the maneuver is indexed to the energy expenditure or, alternatively, the time integral of the heating rate. Firist-order optimality conditions are defined for the classical approach, as are a sequential gradient-restoration algorithm and a combined gradient-restoration algorithm. Minimization techniques are presented for the aeroassisted transfer energy consumption and time-delay integral of the heating rate, as well as minimization of the pressure. It is shown that the eigenvalues of the Jacobian matrix of the differential system is both stiff and unstable, implying that the sequential gradient restoration algorithm in its present version is unsuitable. A new method, involving a multipoint approach to the two-poing boundary value problem, is recommended.

Optimal control of large space structures via generalized inverse matrix

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Fang, Xiaowen

1987-01-01

Independent Modal Space Control (IMSC) is a control scheme that decouples the space structure into n independent second-order subsystems according to n controlled modes and controls each mode independently. It is well-known that the IMSC eliminates control and observation spillover caused when the conventional coupled modal control scheme is employed. The independent control of each mode requires that the number of actuators be equal to the number of modelled modes, which is very high for a faithful modeling of large space structures. A control scheme is proposed that allows one to use a reduced number of actuators to control all modeled modes suboptimally. In particular, the method of generalized inverse matrices is employed to implement the actuators such that the eigenvalues of the closed-loop system are as closed as possible to those specified by the optimal IMSC. Computer simulation of the proposed control scheme on a simply supported beam is given.

GW quasiparticle bandgaps of anatase TiO2 starting from DFT + U.

PubMed

Patrick, Christopher E; Giustino, Feliciano

2012-05-23

We investigate the quasiparticle band structure of anatase TiO(2), a wide gap semiconductor widely employed in photovoltaics and photocatalysis. We obtain GW quasiparticle energies starting from density-functional theory (DFT) calculations including Hubbard U corrections. Using a simple iterative procedure we determine the value of the Hubbard parameter yielding a vanishing quasiparticle correction to the fundamental bandgap of anatase TiO(2). The bandgap (3.3 eV) calculated using this optimal Hubbard parameter is smaller than the value obtained by applying many-body perturbation theory to standard DFT eigenstates and eigenvalues (3.7 eV). We extend our analysis to the rutile polymorph of TiO(2) and reach similar conclusions. Our work highlights the role of the starting non-interacting Hamiltonian in the calculation of GW quasiparticle energies in TiO(2) and suggests an optimal Hubbard parameter for future calculations.

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 signs of inflammation in the animals receiving preconditioned ECFC. Acidic preconditioning improved ECFC survival and angiogenic activity in the presence of proinflammatory and damage signals present in the ischemic milieu, even under high glucose conditions, and increased their therapeutic potential for postischemia tissue regeneration in a murine model of type 2 diabetes. Collectively, our data suggest that acidic preconditioning of ECFC is a simple and inexpensive strategy to improve the effectiveness of cell transplantation in diabetes, where tissue repair is highly compromised.

Eigenvalue Detonation of Combined Effects Aluminized Explosives

NASA Astrophysics Data System (ADS)

Capellos, C.; Baker, E. L.; Nicolich, S.; Balas, W.; Pincay, J.; Stiel, L. I.

2007-12-01

Theory and performance for recently developed combined—effects aluminized explosives are presented. Our recently developed combined-effects aluminized explosives (PAX-29C, PAX-30, PAX-42) are capable of achieving excellent metal pushing, as well as high blast energies. Metal pushing capability refers to the early volume expansion work produced during the first few volume expansions associated with cylinder and wall velocities and Gurney energies. Eigenvalue detonation explains the observed detonation states achieved by these combined effects explosives. Cylinder expansion data and thermochemical calculations (JAGUAR and CHEETAH) verify the eigenvalue detonation behavior.

NASA Astrophysics Data System (ADS)

2018-05-01

Eigenvalues and eigenvectors, together, constitute the eigenstructure of the system. The design of vibrating systems aimed at satisfying specifications on eigenvalues and eigenvectors, which is commonly known as eigenstructure assignment, has drawn increasing interest over the recent years. The most natural mathematical framework for such problems is constituted by the inverse eigenproblems, which consist in the determination of the system model that features a desired set of eigenvalues and eigenvectors. Although such a problem is intrinsically challenging, several solutions have been proposed in the literature. The approaches to eigenstructure assignment can be basically divided into passive control and active control.

Dimension from covariance matrices.

PubMed

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

Extension of the tridiagonal reduction (FEER) method for complex eigenvalue problems in NASTRAN

NASA Technical Reports Server (NTRS)

Newman, M.; Mann, F. I.

1978-01-01

As in the case of real eigenvalue analysis, the eigensolutions closest to a selected point in the eigenspectrum were extracted from a reduced, symmetric, tridiagonal eigenmatrix whose order was much lower than that of the full size problem. The reduction process was effected automatically, and thus avoided the arbitrary lumping of masses and other physical quantities at selected grid points. The statement of the algebraic eigenvalue problem admitted mass, damping, and stiffness matrices which were unrestricted in character, i.e., they might be real, symmetric or nonsymmetric, singular or nonsingular.

Chebyshev polynomials in the spectral Tau method and applications to Eigenvalue problems

NASA Technical Reports Server (NTRS)

Johnson, Duane

1996-01-01

Chebyshev Spectral methods have received much attention recently as a technique for the rapid solution of ordinary differential equations. This technique also works well for solving linear eigenvalue problems. Specific detail is given to the properties and algebra of chebyshev polynomials; the use of chebyshev polynomials in spectral methods; and the recurrence relationships that are developed. These formula and equations are then applied to several examples which are worked out in detail. The appendix contains an example FORTRAN program used in solving an eigenvalue problem.

Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units.

PubMed

Qi, Ruxi; Botello-Smith, Wesley M; Luo, Ray

2017-07-11

Electrostatic interactions play crucial roles in biophysical processes such as protein folding and molecular recognition. Poisson-Boltzmann equation (PBE)-based models have emerged as widely used in modeling these important processes. Though great efforts have been put into developing efficient PBE numerical models, challenges still remain due to the high dimensionality of typical biomolecular systems. In this study, we implemented and analyzed commonly used linear PBE solvers for the ever-improving graphics processing units (GPU) for biomolecular simulations, including both standard and preconditioned conjugate gradient (CG) solvers with several alternative preconditioners. Our implementation utilizes the standard Nvidia CUDA libraries cuSPARSE, cuBLAS, and CUSP. Extensive tests show that good numerical accuracy can be achieved given that the single precision is often used for numerical applications on GPU platforms. The optimal GPU performance was observed with the Jacobi-preconditioned CG solver, with a significant speedup over standard CG solver on CPU in our diversified test cases. Our analysis further shows that different matrix storage formats also considerably affect the efficiency of different linear PBE solvers on GPU, with the diagonal format best suited for our standard finite-difference linear systems. Further efficiency may be possible with matrix-free operations and integrated grid stencil setup specifically tailored for the banded matrices in PBE-specific linear systems.

TRPV1 Agonist, Capsaicin, Induces Axon Outgrowth after Injury via Ca2+/PKA Signaling.

PubMed

Frey, Erin; Karney-Grobe, Scott; Krolak, Trevor; Milbrandt, Jeff; DiAntonio, Aaron

2018-01-01

Preconditioning nerve injuries activate a pro-regenerative program that enhances axon regeneration for most classes of sensory neurons. However, nociceptive sensory neurons and central nervous system neurons regenerate poorly. In hopes of identifying novel mechanisms that promote regeneration, we screened for drugs that mimicked the preconditioning response and identified a nociceptive ligand that activates a preconditioning-like response to promote axon outgrowth. We show that activating the ion channel TRPV1 with capsaicin induces axon outgrowth of cultured dorsal root ganglion (DRG) sensory neurons, and that this effect is blocked in TRPV1 knockout neurons. Regeneration occurs only in NF200-negative nociceptive neurons, consistent with a cell-autonomous mechanism. Moreover, we identify a signaling pathway in which TRPV1 activation leads to calcium influx and protein kinase A (PKA) activation to induce a preconditioning-like response. Finally, capsaicin administration to the mouse sciatic nerve activates a similar preconditioning-like response and induces enhanced axonal outgrowth, indicating that this pathway can be induced in vivo . These findings highlight the use of local ligands to induce regeneration and suggest that it may be possible to target selective neuronal populations for repair, including cell types that often fail to regenerate.

Involvement of adenosine and standardization of aqueous extract of garlic (Allium sativum Linn.) on cardioprotective and cardiodepressant properties in ischemic preconditioning and myocardial ischemia-reperfusion induced cardiac injury

PubMed Central

Sharma, Ashish Kumar; Munajjam, Arshee; Vaishnav, Bhawna; Sharma, Richa; Sharma, Ashok; Kishore, Kunal; Sharma, Akash; Sharma, Divya; Kumari, Rita; Tiwari, Ashish; Singh, Santosh Kumar; Gaur, Samir; Jatav, Vijay Singh; Srinivasan, Barthu Parthi; Agarwal, Shyam Sunder

2012-01-01

The present study investigated the effect of garlic (Allium sativum Linn.) aqueous extracts on ischemic preconditioning and ischemia-reperfusion induced cardiac injury, as well as adenosine involvement in ischemic preconditioning and garlic extract induced cardioprotection. A model of ischemia-reperfusion injury was established using Langendorff apparatus. Aqueous extract of garlic dose was standardized (0.5%, 0.4%, 0.3%, 0.2%, 0.1%, 0.07%, 0.05%, 0.03%, 0.01%), and the 0.05% dose was found to be the most effective. Higher doses (more than 0.05%) were highly toxic, causing arrhythmia and cardiodepression, whereas the lower doses were ineffective. Garlic exaggerated the cardioprotective effect of ischemic preconditioning. The cardioprotective effect of ischemic preconditioning and garlic cardioprotection was significantly attenuated by theophylline (1,000 µmol/L) and 8-SPT (10 mg/kg, i.p.) and expressed by increased myocardial infarct size, increased LDH level, and reduced nitrite and adenosine levels. These findings suggest that adenosine is involved in the pharmacological and molecular mechanism of garlic induced cardioprotection and mediated by the modulation of nitric oxide. PMID:23554727

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

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

Research and application of borehole structure optimization based on pre-drill risk assessment

NASA Astrophysics Data System (ADS)

Zhang, Guohui; Liu, Xinyun; Chenrong; Hugui; Yu, Wenhua; Sheng, Yanan; Guan, Zhichuan

2017-11-01

Borehole structure design based on pre-drill risk assessment and considering risks related to drilling operation is the pre-condition for safe and smooth drilling operation. Major risks of drilling operation include lost circulation, blowout, sidewall collapsing, sticking and failure of drilling tools etc. In the study, studying data from neighboring wells was used to calculate the profile of formation pressure with credibility in the target well, then the borehole structure design for the target well assessment by using the drilling risk assessment to predict engineering risks before drilling. Finally, the prediction results were used to optimize borehole structure design to prevent such drilling risks. The newly-developed technique provides a scientific basis for lowering probability and frequency of drilling engineering risks, and shortening time required to drill a well, which is of great significance for safe and high-efficient drilling.

Favourable Changes of the Risk-Benefit Ratio in Alpine Skiing

PubMed Central

Burtscher, Martin; Ruedl, Gerhard

2015-01-01

During the past five decades recreational alpine skiing has become increasingly safer. The numerous annual media reports on ski injuries have to be interpreted on the basis of the tremendous numbers of skiers. These favourable changes seem primarily be due to the introduction of short carving skis, more rigid and comfortable ski boots, the use of protective gear like helmets, and the optimized preparation of ski slopes. The associated health benefits from skiing, especially arising from its association with a healthier life style, and possibly also from effects related to hypoxia preconditioning and increasing subjective vitality by natural elements clearly outweigh the health hazards. Technical improvements will likely help further reducing the injury risk. At least hypothetically, each individual skier could help to prevent injuries by the development of an appropriate physical fitness and responsible behaviour on ski slopes thereby optimizing the risk-benefit ratio of alpine skiing. PMID:26035659

Preconditioning strategies for nonlinear conjugate gradient methods, based on quasi-Newton updates

NASA Astrophysics Data System (ADS)

Andrea, Caliciotti; Giovanni, Fasano; Massimo, Roma

2016-10-01

This paper reports two proposals of possible preconditioners for the Nonlinear Conjugate Gradient (NCG) method, in large scale unconstrained optimization. On one hand, the common idea of our preconditioners is inspired to L-BFGS quasi-Newton updates, on the other hand we aim at explicitly approximating in some sense the inverse of the Hessian matrix. Since we deal with large scale optimization problems, we propose matrix-free approaches where the preconditioners are built using symmetric low-rank updating formulae. Our distinctive new contributions rely on using information on the objective function collected as by-product of the NCG, at previous iterations. Broadly speaking, our first approach exploits the secant equation, in order to impose interpolation conditions on the objective function. In the second proposal we adopt and ad hoc modified-secant approach, in order to possibly guarantee some additional theoretical properties.

Robust Assignment Of Eigensystems For Flexible Structures

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lim, Kyong B.; Junkins, John L.

1992-01-01

Improved method for placement of eigenvalues and eigenvectors of closed-loop control system by use of either state or output feedback. Applied to reduced-order finite-element mathematical model of NASA's MAST truss beam structure. Model represents deployer/retractor assembly, inertial properties of Space Shuttle, and rigid platforms for allocation of sensors and actuators. Algorithm formulated in real arithmetic for efficient implementation. Choice of open-loop eigenvector matrix and its closest unitary matrix believed suitable for generating well-conditioned eigensystem with small control gains. Implication of this approach is that element of iterative search for "optimal" unitary matrix appears unnecessary in practice for many test problems.

Compressed modes for variational problems in mathematics and physics

PubMed Central

Ozoliņš, Vidvuds; Lai, Rongjie; Caflisch, Russel; Osher, Stanley

2013-01-01

This article describes a general formalism for obtaining spatially localized (“sparse”) solutions to a class of problems in mathematical physics, which can be recast as variational optimization problems, such as the important case of Schrödinger’s equation in quantum mechanics. Sparsity is achieved by adding an regularization term to the variational principle, which is shown to yield solutions with compact support (“compressed modes”). Linear combinations of these modes approximate the eigenvalue spectrum and eigenfunctions in a systematically improvable manner, and the localization properties of compressed modes make them an attractive choice for use with efficient numerical algorithms that scale linearly with the problem size. PMID:24170861

Optimization of cascade blade mistuning. I - Equations of motion and basic inherent properties

NASA Technical Reports Server (NTRS)

Nissim, E.

1985-01-01

Attention is given to the derivation of the equations of motion of mistuned compressor blades, interpolating aerodynamic coefficients by means of quadratic expressions in the reduced frequency. If the coefficients of the quadratic expressions are permitted to assume complex values, excellent accuracy is obtained and Pade rational expressions are obviated. On the basis of the resulting equations, it is shown analytically that the sum of all the real parts of the eigenvalues is independent of the mistuning introduced into the system. Blade mistuning is further treated through the aerodynamic energy approach, and the limiting vibration modes associated with alternative mistunings are identified.

Compressed modes for variational problems in mathematics and physics.

PubMed

Ozolins, Vidvuds; Lai, Rongjie; Caflisch, Russel; Osher, Stanley

2013-11-12

This article describes a general formalism for obtaining spatially localized ("sparse") solutions to a class of problems in mathematical physics, which can be recast as variational optimization problems, such as the important case of Schrödinger's equation in quantum mechanics. Sparsity is achieved by adding an regularization term to the variational principle, which is shown to yield solutions with compact support ("compressed modes"). Linear combinations of these modes approximate the eigenvalue spectrum and eigenfunctions in a systematically improvable manner, and the localization properties of compressed modes make them an attractive choice for use with efficient numerical algorithms that scale linearly with the problem size.

Modern digital flight control system design for VTOL aircraft

NASA Technical Reports Server (NTRS)

Broussard, J. R.; Berry, P. W.; Stengel, R. F.

1979-01-01

Methods for and results from the design and evaluation of a digital flight control system (DFCS) for a CH-47B helicopter are presented. The DFCS employed proportional-integral control logic to provide rapid, precise response to automatic or manual guidance commands while following conventional or spiral-descent approach paths. It contained altitude- and velocity-command modes, and it adapted to varying flight conditions through gain scheduling. Extensive use was made of linear systems analysis techniques. The DFCS was designed, using linear-optimal estimation and control theory, and the effects of gain scheduling are assessed by examination of closed-loop eigenvalues and time responses.

A new localization set for generalized eigenvalues.

PubMed

Gao, Jing; Li, Chaoqian

2017-01-01

A new localization set for generalized eigenvalues is obtained. It is shown that the new set is tighter than that in (Numer. Linear Algebra Appl. 16:883-898, 2009). Numerical examples are given to verify the corresponding results.

Symmetric quadratic Hamiltonians with pseudo-Hermitian matrix representation

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

Fernández, Francisco M., E-mail: fernande@quimica.unlp.edu.ar

2016-06-15

We prove that any symmetric Hamiltonian that is a quadratic function of the coordinates and momenta has a pseudo-Hermitian adjoint or regular matrix representation. The eigenvalues of the latter matrix are the natural frequencies of the Hamiltonian operator. When all the eigenvalues of the matrix are real, then the spectrum of the symmetric Hamiltonian is real and the operator is Hermitian. As illustrative examples we choose the quadratic Hamiltonians that model a pair of coupled resonators with balanced gain and loss, the electromagnetic self-force on an oscillating charged particle and an active LRC circuit. -- Highlights: •Symmetric quadratic operators aremore » useful models for many physical applications. •Any such operator exhibits a pseudo-Hermitian matrix representation. •Its eigenvalues are the natural frequencies of the Hamiltonian operator. •The eigenvalues may be real or complex and describe a phase transition.« less

Rich structure in the correlation matrix spectra in non-equilibrium steady states

NASA Astrophysics Data System (ADS)

Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H.

2017-01-01

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

Eigenvalue sensitivity analysis of planar frames with variable joint and support locations

NASA Technical Reports Server (NTRS)

Chuang, Ching H.; Hou, Gene J. W.

1991-01-01

Two sensitivity equations are derived in this study based upon the continuum approach for eigenvalue sensitivity analysis of planar frame structures with variable joint and support locations. A variational form of an eigenvalue equation is first derived in which all of the quantities are expressed in the local coordinate system attached to each member. Material derivative of this variational equation is then sought to account for changes in member's length and orientation resulting form the perturbation of joint and support locations. Finally, eigenvalue sensitivity equations are formulated in either domain quantities (by the domain method) or boundary quantities (by the boundary method). It is concluded that the sensitivity equation derived by the boundary method is more efficient in computation but less accurate than that of the domain method. Nevertheless, both of them in terms of computational efficiency are superior to the conventional direct differentiation method and the finite difference method.

A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus

NASA Astrophysics Data System (ADS)

Mohammadi, Jafar; Limmer, Steffen; Stańczak, Sławomir

2016-07-01

This paper considers eigenvalue estimation for the decentralized inference problem for spectrum sensing. We propose a decentralized eigenvalue computation algorithm based on the power method, which is referred to as generalized power method GPM; it is capable of estimating the eigenvalues of a given covariance matrix under certain conditions. Furthermore, we have developed a decentralized implementation of GPM by splitting the iterative operations into local and global computation tasks. The global tasks require data exchange to be performed among the nodes. For this task, we apply an average consensus algorithm to efficiently perform the global computations. As a special case, we consider a structured graph that is a tree with clusters of nodes at its leaves. For an accelerated distributed implementation, we propose to use computation over multiple access channel (CoMAC) as a building block of the algorithm. Numerical simulations are provided to illustrate the performance of the two algorithms.

Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects

NASA Astrophysics Data System (ADS)

Castellano, Claudio; Pastor-Satorras, Romualdo

2017-10-01

The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.

A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

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

Beer, M.

1980-12-01

The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

Intrinsic character of Stokes matrices

NASA Astrophysics Data System (ADS)

Gagnon, Jean-François; Rousseau, Christiane

2017-02-01

Two germs of linear analytic differential systems x k + 1Y‧ = A (x) Y with a non-resonant irregular singularity are analytically equivalent if and only if they have the same eigenvalues and equivalent collections of Stokes matrices. The Stokes matrices are the transition matrices between sectors on which the system is analytically equivalent to its formal normal form. Each sector contains exactly one separating ray for each pair of eigenvalues. A rotation in S allows supposing that R+ lies in the intersection of two sectors. Reordering of the coordinates of Y allows ordering the real parts of the eigenvalues, thus yielding triangular Stokes matrices. However, the choice of the rotation in x is not canonical. In this paper we establish how the collection of Stokes matrices depends on this rotation, and hence on a chosen order of the projection of the eigenvalues on a line through the origin.

Eigenvalue routines in NASTRAN: A comparison with the Block Lanczos method

NASA Technical Reports Server (NTRS)

Tischler, V. A.; Venkayya, Vipperla B.

1993-01-01

The NASA STRuctural ANalysis (NASTRAN) program is one of the most extensively used engineering applications software in the world. It contains a wealth of matrix operations and numerical solution techniques, and they were used to construct efficient eigenvalue routines. The purpose of this paper is to examine the current eigenvalue routines in NASTRAN and to make efficiency comparisons with a more recent implementation of the Block Lanczos algorithm by Boeing Computer Services (BCS). This eigenvalue routine is now available in the BCS mathematics library as well as in several commercial versions of NASTRAN. In addition, CRAY maintains a modified version of this routine on their network. Several example problems, with a varying number of degrees of freedom, were selected primarily for efficiency bench-marking. Accuracy is not an issue, because they all gave comparable results. The Block Lanczos algorithm was found to be extremely efficient, in particular, for very large size problems.

Eigenvalue statistics for the sum of two complex Wishart matrices

NASA Astrophysics Data System (ADS)

Kumar, Santosh

2014-09-01

The sum of independent Wishart matrices, taken from distributions with unequal covariance matrices, plays a crucial role in multivariate statistics, and has applications in the fields of quantitative finance and telecommunication. However, analytical results concerning the corresponding eigenvalue statistics have remained unavailable, even for the sum of two Wishart matrices. This can be attributed to the complicated and rotationally noninvariant nature of the matrix distribution that makes extracting the information about eigenvalues a nontrivial task. Using a generalization of the Harish-Chandra-Itzykson-Zuber integral, we find exact solution to this problem for the complex Wishart case when one of the covariance matrices is proportional to the identity matrix, while the other is arbitrary. We derive exact and compact expressions for the joint probability density and marginal density of eigenvalues. The analytical results are compared with numerical simulations and we find perfect agreement.

Rich structure in the correlation matrix spectra in non-equilibrium steady states.

PubMed

Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H

2017-01-17

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

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.

Implicit solvers for unstructured meshes

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.; Mavriplis, Dimitri J.

1991-01-01

Implicit methods for unstructured mesh computations are developed and tested. The approximate system which arises from the Newton-linearization of the nonlinear evolution operator is solved by using the preconditioned generalized minimum residual technique. These different preconditioners are investigated: the incomplete LU factorization (ILU), block diagonal factorization, and the symmetric successive over-relaxation (SSOR). The preconditioners have been optimized to have good vectorization properties. The various methods are compared over a wide range of problems. Ordering of the unknowns, which affects the convergence of these sparse matrix iterative methods, is also investigated. Results are presented for inviscid and turbulent viscous calculations on single and multielement airfoil configurations using globally and adaptively generated meshes.

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 outflow greatly influences the geoeffectiveness of magnetospheric storms.

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 reserved.

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 mesenchymal stem cells improved colonic immune capacity and enhanced tissue remodeling. © Society for Leukocyte Biology.

Replica approach to mean-variance portfolio optimization

NASA Astrophysics Data System (ADS)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  <  1, where N is the dimension of the portfolio and T the length of the time series used to estimate the covariance matrix. At the critical point r  =  1 a phase transition is taking place. The out of sample estimation error blows up at this point as 1/(1  -  r), independently of the covariance matrix or the expected return, displaying the universality not only of the critical exponent, but also the critical point. As a conspicuous illustration of the dangers of in-sample estimates, the optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

More insights into early brain development through statistical analyses of eigen-structural elements of diffusion tensor imaging using multivariate adaptive regression splines

PubMed Central

Chen, Yasheng; Zhu, Hongtu; An, Hongyu; Armao, Diane; Shen, Dinggang; Gilmore, John H.; Lin, Weili

2013-01-01

The aim of this study was to characterize the maturational changes of the three eigenvalues (λ1 ≥ λ2 ≥ λ3) of diffusion tensor imaging (DTI) during early postnatal life for more insights into early brain development. In order to overcome the limitations of using presumed growth trajectories for regression analysis, we employed Multivariate Adaptive Regression Splines (MARS) to derive data-driven growth trajectories for the three eigenvalues. We further employed Generalized Estimating Equations (GEE) to carry out statistical inferences on the growth trajectories obtained with MARS. With a total of 71 longitudinal datasets acquired from 29 healthy, full-term pediatric subjects, we found that the growth velocities of the three eigenvalues were highly correlated, but significantly different from each other. This paradox suggested the existence of mechanisms coordinating the maturations of the three eigenvalues even though different physiological origins may be responsible for their temporal evolutions. Furthermore, our results revealed the limitations of using the average of λ2 and λ3 as the radial diffusivity in interpreting DTI findings during early brain development because these two eigenvalues had significantly different growth velocities even in central white matter. In addition, based upon the three eigenvalues, we have documented the growth trajectory differences between central and peripheral white matter, between anterior and posterior limbs of internal capsule, and between inferior and superior longitudinal fasciculus. Taken together, we have demonstrated that more insights into early brain maturation can be gained through analyzing eigen-structural elements of DTI. PMID:23455648

COMPPAP - COMPOSITE PLATE BUCKLING ANALYSIS PROGRAM (IBM PC VERSION)

NASA Technical Reports Server (NTRS)

Smith, J. P.

1994-01-01

The Composite Plate Buckling Analysis Program (COMPPAP) was written to help engineers determine buckling loads of orthotropic (or isotropic) irregularly shaped plates without requiring hand calculations from design curves or extensive finite element modeling. COMPPAP is a one element finite element program that utilizes high-order displacement functions. The high order of the displacement functions enables the user to produce results more accurate than traditional h-finite elements. This program uses these high-order displacement functions to perform a plane stress analysis of a general plate followed by a buckling calculation based on the stresses found in the plane stress solution. The current version assumes a flat plate (constant thickness) subject to a constant edge load (normal or shear) on one or more edges. COMPPAP uses the power method to find the eigenvalues of the buckling problem. The power method provides an efficient solution when only one eigenvalue is desired. Once the eigenvalue is found, the eigenvector, which corresponds to the plate buckling mode shape, results as a by-product. A positive feature of the power method is that the dominant eigenvalue is the first found, which is this case is the plate buckling load. The reported eigenvalue expresses a load factor to induce plate buckling. COMPPAP is written in ANSI FORTRAN 77. Two machine versions are available from COSMIC: a PC version (MSC-22428), which is for IBM PC 386 series and higher computers and compatibles running MS-DOS; and a UNIX version (MSC-22286). The distribution medium for both machine versions includes source code for both single and double precision versions of COMPPAP. The PC version includes source code which has been optimized for implementation within DOS memory constraints as well as sample executables for both the single and double precision versions of COMPPAP. The double precision versions of COMPPAP have been successfully implemented on an IBM PC 386 compatible running MS-DOS, a Sun4 series computer running SunOS, an HP-9000 series computer running HP-UX, and a CRAY X-MP series computer running UNICOS. COMPPAP requires 1Mb of RAM and the BLAS and LINPACK math libraries, which are included on the distribution medium. The COMPPAP documentation provides instructions for using the commercial post-processing package PATRAN for graphical interpretation of COMPPAP output. The UNIX version includes two electronic versions of the documentation: one in LaTex format and one in PostScript format. The standard distribution medium for the PC version (MSC-22428) is a 5.25 inch 1.2Mb MS-DOS format diskette. The standard distribution medium for the UNIX version (MSC-22286) is a .25 inch streaming magnetic tape cartridge (Sun QIC-24) in UNIX tar format. For the UNIX version, alternate distribution media and formats are available upon request. COMPPAP was developed in 1992.

COMPPAP - COMPOSITE PLATE BUCKLING ANALYSIS PROGRAM (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Smith, J. P.

1994-01-01

The Composite Plate Buckling Analysis Program (COMPPAP) was written to help engineers determine buckling loads of orthotropic (or isotropic) irregularly shaped plates without requiring hand calculations from design curves or extensive finite element modeling. COMPPAP is a one element finite element program that utilizes high-order displacement functions. The high order of the displacement functions enables the user to produce results more accurate than traditional h-finite elements. This program uses these high-order displacement functions to perform a plane stress analysis of a general plate followed by a buckling calculation based on the stresses found in the plane stress solution. The current version assumes a flat plate (constant thickness) subject to a constant edge load (normal or shear) on one or more edges. COMPPAP uses the power method to find the eigenvalues of the buckling problem. The power method provides an efficient solution when only one eigenvalue is desired. Once the eigenvalue is found, the eigenvector, which corresponds to the plate buckling mode shape, results as a by-product. A positive feature of the power method is that the dominant eigenvalue is the first found, which is this case is the plate buckling load. The reported eigenvalue expresses a load factor to induce plate buckling. COMPPAP is written in ANSI FORTRAN 77. Two machine versions are available from COSMIC: a PC version (MSC-22428), which is for IBM PC 386 series and higher computers and compatibles running MS-DOS; and a UNIX version (MSC-22286). The distribution medium for both machine versions includes source code for both single and double precision versions of COMPPAP. The PC version includes source code which has been optimized for implementation within DOS memory constraints as well as sample executables for both the single and double precision versions of COMPPAP. The double precision versions of COMPPAP have been successfully implemented on an IBM PC 386 compatible running MS-DOS, a Sun4 series computer running SunOS, an HP-9000 series computer running HP-UX, and a CRAY X-MP series computer running UNICOS. COMPPAP requires 1Mb of RAM and the BLAS and LINPACK math libraries, which are included on the distribution medium. The COMPPAP documentation provides instructions for using the commercial post-processing package PATRAN for graphical interpretation of COMPPAP output. The UNIX version includes two electronic versions of the documentation: one in LaTex format and one in PostScript format. The standard distribution medium for the PC version (MSC-22428) is a 5.25 inch 1.2Mb MS-DOS format diskette. The standard distribution medium for the UNIX version (MSC-22286) is a .25 inch streaming magnetic tape cartridge (Sun QIC-24) in UNIX tar format. For the UNIX version, alternate distribution media and formats are available upon request. COMPPAP was developed in 1992.

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.

[The effect of hypoxia preconditioning no binding activity of HIF-1 on the HRE with EPO in the hippocampus of mice].

PubMed

Shao, Guo; Zhou, Wei-Hua; Gao, Cui-Ying; Zhang, Ran; Lu, Guo-Wei

2007-02-01

To observe change of binding activity of HIF-1 with erythropoietin (EPO) hypoxia response element (HRE) in the hippocampus of mice preconditioned to hypoxia and explore relationship between the changes and the preconditioning. The hippocampus was removed from mice exposed to hypoxia for 0 run (control group), 1 run (H1 group) and 4 runs(H4 group). Electrophoretic mobility shift assays (EMSA), chromatin immunoprecipitation (ChIP)and real time PCR were used to detect the change of activity of HIF-1 on HRE of EPO. Both in vitro and in vivo binding tests showed that the HIF-1 DNA-binding activities were increased in group H1 and markedly increased in group H4. The increase of HIF-1 and HRE of EPO binding activities is thought be involved in hypoxic preconditioning.

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.

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

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.

Gradient-Based Aerodynamic Shape Optimization Using ADI Method for Large-Scale Problems

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Baysal, Oktay

1997-01-01

A gradient-based shape optimization methodology, that is intended for practical three-dimensional aerodynamic applications, has been developed. It is based on the quasi-analytical sensitivities. The flow analysis is rendered by a fully implicit, finite volume formulation of the Euler equations.The aerodynamic sensitivity equation is solved using the alternating-direction-implicit (ADI) algorithm for memory efficiency. A flexible wing geometry model, that is based on surface parameterization and platform schedules, is utilized. The present methodology and its components have been tested via several comparisons. Initially, the flow analysis for for a wing is compared with those obtained using an unfactored, preconditioned conjugate gradient approach (PCG), and an extensively validated CFD code. Then, the sensitivities computed with the present method have been compared with those obtained using the finite-difference and the PCG approaches. Effects of grid refinement and convergence tolerance on the analysis and shape optimization have been explored. Finally the new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4. Despite the expected increase in the computational time, the results indicate that shape optimization, which require large numbers of grid points can be resolved with a gradient-based approach.

Development of Probiotic Formulation for the Treatment of Iron Deficiency Anemia.

PubMed

Korčok, Davor Jovan; Tršić-Milanović, Nada Aleksandar; Ivanović, Nevena Djuro; Đorđević, Brižita Ivan

2018-04-01

Probiotics are increasingly more present both as functional foods, and in pharmaceutical preparations with multiple levels of action that contribute to human health. Probiotics realize their positive effects with a proper dose, and by maintaining a declared number of probiotics cells by the expiration date. Important precondition for developing a probiotic product is the right choice of clinically proven probiotic strain, the choice of other active components, as well as, the optimization of the quantity of active component of probiotic per product dose. This scientific paper describes the optimization of the number of probiotics cells in the formulation of dietary supplement that contains probiotic culture Lactobacillus plantarum 299v, iron and vitamin C. Variations of the quantity of active component were analyzed in development batches of the encapsulated probiotic product categorized as dietary supplement with the following ingredients: probiotic culture, sucrosomal form of iron and vitamin C. Optimal quantity of active component L. plantarum of 50 mg, was selected. The purpose of this scientific paper is to select the optimal formulation of probiotic culture in a dietary supplement that contains iron and vitamin C, and to also determine its expiration date by the analysis of the number of viable probiotic cells.

Underlying construct of empathy, optimism, and burnout in medical students.

PubMed

Hojat, Mohammadreza; Vergare, Michael; Isenberg, Gerald; Cohen, Mitchell; Spandorfer, John

2015-01-29

This study was designed to explore the underlying construct of measures of empathy, optimism, and burnout in medical students. Three instruments for measuring empathy (Jefferson Scale of Empathy, JSE); Optimism (the Life Orientation Test-Revised, LOT-R); and burnout (the Maslach Burnout Inventory, MBI, which includes three scales of Emotional Exhaustion, Depersonalization, and Personal Accomplishment) were administered to 265 third-year students at Sidney Kimmel (formerly Jefferson) Medical College at Thomas Jefferson University. Data were subjected to factor analysis to examine relationships among measures of empathy, optimism, and burnout in a multivariate statistical model. Factor analysis (principal component with oblique rotation) resulted in two underlying constructs, each with an eigenvalue greater than one. The first factor involved "positive personality attributes" (factor coefficients greater than .58 for measures of empathy, optimism, and personal accomplishment). The second factor involved "negative personality attributes" (factor coefficients greater than .78 for measures of emotional exhaustion, and depersonalization). Results confirmed that an association exists between empathy in the context of patient care and personality characteristics that are conducive to relationship building, and considered to be "positive personality attributes," as opposed to personality characteristics that are considered as "negative personality attributes" that are detrimental to interpersonal relationships. Implications for the professional development of physicians-in-training and in-practice are discussed.

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.

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

Optimization of the sources in local hyperthermia using a combined finite element-genetic algorithm method.

PubMed

Siauve, N; Nicolas, L; Vollaire, C; Marchal, C

2004-12-01

This article describes an optimization process specially designed for local and regional hyperthermia in order to achieve the desired specific absorption rate in the patient. It is based on a genetic algorithm coupled to a finite element formulation. The optimization method is applied to real human organs meshes assembled from computerized tomography scans. A 3D finite element formulation is used to calculate the electromagnetic field in the patient, achieved by radiofrequency or microwave sources. Space discretization is performed using incomplete first order edge elements. The sparse complex symmetric matrix equation is solved using a conjugate gradient solver with potential projection pre-conditionning. The formulation is validated by comparison of calculated specific absorption rate distributions in a phantom to temperature measurements. A genetic algorithm is used to optimize the specific absorption rate distribution to predict the phases and amplitudes of the sources leading to the best focalization. The objective function is defined as the specific absorption rate ratio in the tumour and healthy tissues. Several constraints, regarding the specific absorption rate in tumour and the total power in the patient, may be prescribed. Results obtained with two types of applicators (waveguides and annular phased array) are presented and show the faculties of the developed optimization process.

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.

Complex energies and the polyelectronic Stark problem

NASA Astrophysics Data System (ADS)

Themelis, Spyros I.; Nicolaides, Cleanthes A.

2000-12-01

The problem of computing the energy shifts and widths of ground or excited N-electron atomic states perturbed by weak or strong static electric fields is dealt with by formulating a state-specific complex eigenvalue Schrödinger equation (CESE), where the complex energy contains the field-induced shift and width. The CESE is solved to all orders nonperturbatively, by using separately optimized N-electron function spaces, composed of real and complex one-electron functions, the latter being functions of a complex coordinate. The use of such spaces is a salient characteristic of the theory, leading to economy and manageability of calculation in terms of a two-step computational procedure. The first step involves only Hermitian matrices. The second adds complex functions and the overall computation becomes non-Hermitian. Aspects of the formalism and of computational strategy are compared with those of the complex absorption potential (CAP) method, which was recently applied for the calculation of field-induced complex energies in H and Li. Also compared are the numerical results of the two methods, and the questions of accuracy and convergence that were posed by Sahoo and Ho (Sahoo S and Ho Y K 2000 J. Phys. B: At. Mol. Opt. Phys. 33 2195) are explored further. We draw attention to the fact that, because in the region where the field strength is weak the tunnelling rate (imaginary part of the complex eigenvalue) diminishes exponentially, it is possible for even large-scale nonperturbative complex eigenvalue calculations either to fail completely or to produce seemingly stable results which, however, are wrong. It is in this context that the discrepancy in the width of Li 1s22s 2S between results obtained by the CAP method and those obtained by the CESE method is interpreted. We suggest that the very-weak-field regime must be computed by the golden rule, provided the continuum is represented accurately. In this respect, existing one-particle semiclassical formulae seem to be sufficient. In addition to the aforementioned comparisons and conclusions, we present a number of new results from the application of the state-specific CESE theory to the calculation of field-induced shifts and widths of the H n = 3 levels and of the prototypical Be 1s22s2 1S state, for a range of field strengths. Using the H n = 3 manifold as the example, it is shown how errors may occur for small values of the field, unless the function spaces are optimized carefully for each level.

Solution of the symmetric eigenproblem AX=lambda BX by delayed division

NASA Technical Reports Server (NTRS)

Thurston, G. A.; Bains, N. J. C.

1986-01-01

Delayed division is an iterative method for solving the linear eigenvalue problem AX = lambda BX for a limited number of small eigenvalues and their corresponding eigenvectors. The distinctive feature of the method is the reduction of the problem to an approximate triangular form by systematically dropping quadratic terms in the eigenvalue lambda. The report describes the pivoting strategy in the reduction and the method for preserving symmetry in submatrices at each reduction step. Along with the approximate triangular reduction, the report extends some techniques used in the method of inverse subspace iteration. Examples are included for problems of varying complexity.