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.

Parallelization of implicit finite difference schemes in computational fluid dynamics

NASA Technical Reports Server (NTRS)

Decker, Naomi H.; Naik, Vijay K.; Nicoules, Michel

1990-01-01

Implicit finite difference schemes are often the preferred numerical schemes in computational fluid dynamics, requiring less stringent stability bounds than the explicit schemes. Each iteration in an implicit scheme involves global data dependencies in the form of second and higher order recurrences. Efficient parallel implementations of such iterative methods are considerably more difficult and non-intuitive. The parallelization of the implicit schemes that are used for solving the Euler and the thin layer Navier-Stokes equations and that require inversions of large linear systems in the form of block tri-diagonal and/or block penta-diagonal matrices is discussed. Three-dimensional cases are emphasized and schemes that minimize the total execution time are presented. Partitioning and scheduling schemes for alleviating the effects of the global data dependencies are described. An analysis of the communication and the computation aspects of these methods is presented. The effect of the boundary conditions on the parallel schemes is also discussed.

Iterative algorithms for tridiagonal matrices on a WSI-multiprocessor

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

Gajski, D.D.; Sameh, A.H.; Wisniewski, J.A.

1982-01-01

With the rapid advances in semiconductor technology, the construction of Wafer Scale Integration (WSI)-multiprocessors consisting of a large number of processors is now feasible. We illustrate the implementation of some basic linear algebra algorithms on such multiprocessors.

BCYCLIC: A parallel block tridiagonal matrix cyclic solver

NASA Astrophysics Data System (ADS)

Hirshman, S. P.; Perumalla, K. S.; Lynch, V. E.; Sanchez, R.

2010-09-01

A block tridiagonal matrix is factored with minimal fill-in using a cyclic reduction algorithm that is easily parallelized. Storage of the factored blocks allows the application of the inverse to multiple right-hand sides which may not be known at factorization time. Scalability with the number of block rows is achieved with cyclic reduction, while scalability with the block size is achieved using multithreaded routines (OpenMP, GotoBLAS) for block matrix manipulation. This dual scalability is a noteworthy feature of this new solver, as well as its ability to efficiently handle arbitrary (non-powers-of-2) block row and processor numbers. Comparison with a state-of-the art parallel sparse solver is presented. It is expected that this new solver will allow many physical applications to optimally use the parallel resources on current supercomputers. Example usage of the solver in magneto-hydrodynamic (MHD), three-dimensional equilibrium solvers for high-temperature fusion plasmas is cited.

A fast direct method for block triangular Toeplitz-like with tri-diagonal block systems from time-fractional partial differential equations

NASA Astrophysics Data System (ADS)

Ke, Rihuan; Ng, Michael K.; Sun, Hai-Wei

2015-12-01

In this paper, we study the block lower triangular Toeplitz-like with tri-diagonal blocks system which arises from the time-fractional partial differential equation. Existing fast numerical solver (e.g., fast approximate inversion method) cannot handle such linear system as the main diagonal blocks are different. The main contribution of this paper is to propose a fast direct method for solving this linear system, and to illustrate that the proposed method is much faster than the classical block forward substitution method for solving this linear system. Our idea is based on the divide-and-conquer strategy and together with the fast Fourier transforms for calculating Toeplitz matrix-vector multiplication. The complexity needs O (MNlog2 ⁡ M) arithmetic operations, where M is the number of blocks (the number of time steps) in the system and N is the size (number of spatial grid points) of each block. Numerical examples from the finite difference discretization of time-fractional partial differential equations are also given to demonstrate the efficiency of the proposed method.

A GPU-accelerated semi-implicit fractional-step method for numerical solutions of incompressible Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Ha, Sanghyun; Park, Junshin; You, Donghyun

2018-01-01

Utility of the computational power of Graphics Processing Units (GPUs) is elaborated for solutions of incompressible Navier-Stokes equations which are integrated using a semi-implicit fractional-step method. The Alternating Direction Implicit (ADI) and the Fourier-transform-based direct solution methods used in the semi-implicit fractional-step method take advantage of multiple tridiagonal matrices whose inversion is known as the major bottleneck for acceleration on a typical multi-core machine. A novel implementation of the semi-implicit fractional-step method designed for GPU acceleration of the incompressible Navier-Stokes equations is presented. Aspects of the programing model of Compute Unified Device Architecture (CUDA), which are critical to the bandwidth-bound nature of the present method are discussed in detail. A data layout for efficient use of CUDA libraries is proposed for acceleration of tridiagonal matrix inversion and fast Fourier transform. OpenMP is employed for concurrent collection of turbulence statistics on a CPU while the Navier-Stokes equations are computed on a GPU. Performance of the present method using CUDA is assessed by comparing the speed of solving three tridiagonal matrices using ADI with the speed of solving one heptadiagonal matrix using a conjugate gradient method. An overall speedup of 20 times is achieved using a Tesla K40 GPU in comparison with a single-core Xeon E5-2660 v3 CPU in simulations of turbulent boundary-layer flow over a flat plate conducted on over 134 million grids. Enhanced performance of 48 times speedup is reached for the same problem using a Tesla P100 GPU.

Communication-avoiding symmetric-indefinite factorization

DOE PAGES

Ballard, Grey Malone; Becker, Dulcenia; Demmel, James; ...

2014-11-13

We describe and analyze a novel symmetric triangular factorization algorithm. The algorithm is essentially a block version of Aasen's triangular tridiagonalization. It factors a dense symmetric matrix A as the product A=PLTL TP T where P is a permutation matrix, L is lower triangular, and T is block tridiagonal and banded. The algorithm is the first symmetric-indefinite communication-avoiding factorization: it performs an asymptotically optimal amount of communication in a two-level memory hierarchy for almost any cache-line size. Adaptations of the algorithm to parallel computers are likely to be communication efficient as well; one such adaptation has been recently published. Asmore » a result, the current paper describes the algorithm, proves that it is numerically stable, and proves that it is communication optimal.« less

Communication-avoiding symmetric-indefinite factorization

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

Ballard, Grey Malone; Becker, Dulcenia; Demmel, James

We describe and analyze a novel symmetric triangular factorization algorithm. The algorithm is essentially a block version of Aasen's triangular tridiagonalization. It factors a dense symmetric matrix A as the product A=PLTL TP T where P is a permutation matrix, L is lower triangular, and T is block tridiagonal and banded. The algorithm is the first symmetric-indefinite communication-avoiding factorization: it performs an asymptotically optimal amount of communication in a two-level memory hierarchy for almost any cache-line size. Adaptations of the algorithm to parallel computers are likely to be communication efficient as well; one such adaptation has been recently published. Asmore » a result, the current paper describes the algorithm, proves that it is numerically stable, and proves that it is communication optimal.« less

Fast Euler solver for transonic airfoils. I - Theory. II - Applications

NASA Technical Reports Server (NTRS)

Dadone, Andrea; Moretti, Gino

1988-01-01

Equations written in terms of generalized Riemann variables are presently integrated by inverting six bidiagonal matrices and two tridiagonal matrices, using an implicit Euler solver that is based on the lambda-formulation. The solution is found on a C-grid whose boundaries are very close to the airfoil. The fast solver is then applied to the computation of several flowfields on a NACA 0012 airfoil at various Mach number and alpha values, yielding results that are primarily concerned with transonic flows. The effects of grid fineness and boundary distances are analyzed; the code is found to be robust and accurate, as well as fast.

Two dimensional J-matrix approach to quantum scattering

NASA Astrophysics Data System (ADS)

Olumegbon, Ismail Adewale

We present an extension of the J-matrix method of scattering to two dimensions in cylindrical coordinates. In the J-matrix approach we select a zeroth order Hamiltonian, H0, which is exactly solvable in the sense that we select a square integrable basis set that enable us to have an infinite tridiagonal representation for H0. Expanding the wavefunction in this basis makes the wave equation equivalent to a three-term recursion relation for the expansion coefficients. Consequently, finding solutions of the recursion relation is equivalent to solving the original H0 problem (i.e., determining the expansion coefficients of the system's wavefunction). The part of the original potential interaction which cannot be brought to an exact tridiagonal form is cut in an NxN basis space and its matrix elements are computed numerically using Gauss quadrature approach. Hence, this approach embodies powerful tools in the analysis of solutions of the wave equation by exploiting the intimate connection and interplay between tridiagonal matrices and the theory of orthogonal polynomials. In such analysis, one is at liberty to employ a wide range of well established methods and numerical techniques associated with these settings such as quadrature approximation and continued fractions. To demonstrate the utility, usefulness, and accuracy of the extended method we use it to obtain the bound states for an illustrative short range potential problem.

Two dimensional J-matrix approach to quantum scattering

NASA Astrophysics Data System (ADS)

Olumegbon, Ismail Adewale

2013-01-01

We present an extension of the J-matrix method of scattering to two dimensions in cylindrical coordinates. In the J-matrix approach we select a zeroth order Hamiltonian, H0, which is exactly solvable in the sense that we select a square integrable basis set that enable us to have an infinite tridiagonal representation for H0. Expanding the wavefunction in this basis makes the wave equation equivalent to a three-term recursion relation for the expansion coefficients. Consequently, finding solutions of the recursion relation is equivalent to solving the original H0 problem (i.e., determining the expansion coefficients of the system's wavefunction). The part of the original potential interaction which cannot be brought to an exact tridiagonal form is cut in an NxN basis space and its matrix elements are computed numerically using Gauss quadrature approach. Hence, this approach embodies powerful tools in the analysis of solutions of the wave equation by exploiting the intimate connection and interplay between tridiagonal matrices and the theory of orthogonal polynomials. In such analysis, one is at liberty to employ a wide range of well established methods and numerical techniques associated with these settings such as quadrature approximation and continued fractions. To demonstrate the utility, usefulness, and accuracy of the extended method we use it to obtain the bound states for an illustrative short range potential problem.

Performance and Accuracy of LAPACK's Symmetric TridiagonalEigensolvers

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

Demmel, Jim W.; Marques, Osni A.; Parlett, Beresford N.

2007-04-19

We compare four algorithms from the latest LAPACK 3.1 release for computing eigenpairs of a symmetric tridiagonal matrix. These include QR iteration, bisection and inverse iteration (BI), the Divide-and-Conquer method (DC), and the method of Multiple Relatively Robust Representations (MR). Our evaluation considers speed and accuracy when computing all eigenpairs, and additionally subset computations. Using a variety of carefully selected test problems, our study includes a variety of today's computer architectures. Our conclusions can be summarized as follows. (1) DC and MR are generally much faster than QR and BI on large matrices. (2) MR almost always does the fewestmore » floating point operations, but at a lower MFlop rate than all the other algorithms. (3) The exact performance of MR and DC strongly depends on the matrix at hand. (4) DC and QR are the most accurate algorithms with observed accuracy O({radical}ne). The accuracy of BI and MR is generally O(ne). (5) MR is preferable to BI for subset computations.« less

An incremental block-line-Gauss-Seidel method for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Napolitano, M.; Walters, R. W.

1985-01-01

A block-line-Gauss-Seidel (LGS) method is developed for solving the incompressible and compressible Navier-Stokes equations in two dimensions. The method requires only one block-tridiagonal solution process per iteration and is consequently faster per step than the linearized block-ADI methods. Results are presented for both incompressible and compressible separated flows: in all cases the proposed block-LGS method is more efficient than the block-ADI methods. Furthermore, for high Reynolds number weakly separated incompressible flow in a channel, which proved to be an impossible task for a block-ADI method, solutions have been obtained very efficiently by the new scheme.

Parallel O(log n) algorithms for open- and closed-chain rigid multibody systems based on a new mass matrix factorization technique

NASA Technical Reports Server (NTRS)

Fijany, Amir

1993-01-01

In this paper, parallel O(log n) algorithms for computation of rigid multibody dynamics are developed. These parallel algorithms are derived by parallelization of new O(n) algorithms for the problem. The underlying feature of these O(n) algorithms is a drastically different strategy for decomposition of interbody force which leads to a new factorization of the mass matrix (M). Specifically, it is shown that a factorization of the inverse of the mass matrix in the form of the Schur Complement is derived as M(exp -1) = C - B(exp *)A(exp -1)B, wherein matrices C, A, and B are block tridiagonal matrices. The new O(n) algorithm is then derived as a recursive implementation of this factorization of M(exp -1). For the closed-chain systems, similar factorizations and O(n) algorithms for computation of Operational Space Mass Matrix lambda and its inverse lambda(exp -1) are also derived. It is shown that these O(n) algorithms are strictly parallel, that is, they are less efficient than other algorithms for serial computation of the problem. But, to our knowledge, they are the only known algorithms that can be parallelized and that lead to both time- and processor-optimal parallel algorithms for the problem, i.e., parallel O(log n) algorithms with O(n) processors. The developed parallel algorithms, in addition to their theoretical significance, are also practical from an implementation point of view due to their simple architectural requirements.

Convergence rates for finite element problems with singularities. Part 1: Antiplane shear. [crack

NASA Technical Reports Server (NTRS)

Plunkett, R.

1980-01-01

The problem of a finite crack in an infinite medium under antiplane shear load is considered. It is shown that the nodal forces at the tip of the crack accurately gives the order of singularity, that n energy release methods can give the strength to better than 1 percent with element size 1/10 the crack length, and that nodal forces give a much better estimate of the stress field than do the elements themselves. The finite element formulation and the factoring of tridiagonal matrices are discussed.

The use of Lanczos's method to solve the large generalized symmetric definite eigenvalue problem

NASA Technical Reports Server (NTRS)

Jones, Mark T.; Patrick, Merrell L.

1989-01-01

The generalized eigenvalue problem, Kx = Lambda Mx, is of significant practical importance, especially in structural enginering where it arises as the vibration and buckling problem. A new algorithm, LANZ, based on Lanczos's method is developed. LANZ uses a technique called dynamic shifting to improve the efficiency and reliability of the Lanczos algorithm. A new algorithm for solving the tridiagonal matrices that arise when using Lanczos's method is described. A modification of Parlett and Scott's selective orthogonalization algorithm is proposed. Results from an implementation of LANZ on a Convex C-220 show it to be superior to a subspace iteration code.

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.

3D Gaussian Beam Modeling

DTIC Science & Technology

2011-09-01

optimized building blocks such as a parallelized tri-diagonal linear solver (used in the “implicit finite differences ” and split-step Pade PE models...and Ding Lee. “A finite - difference treatment of interface conditions for the parabolic wave equation: The horizontal interface.” The Journal of the...Acoustical Society of America, 71(4):855, 1982. 3. Ding Lee and Suzanne T. McDaniel. “A finite - difference treatment of interface conditions for

Numerical Aspects of Atomic Physics: Helium Basis Sets and Matrix Diagonalization

NASA Astrophysics Data System (ADS)

Jentschura, Ulrich; Noble, Jonathan

2014-03-01

We present a matrix diagonalization algorithm for complex symmetric matrices, which can be used in order to determine the resonance energies of auto-ionizing states of comparatively simple quantum many-body systems such as helium. The algorithm is based in multi-precision arithmetic and proceeds via a tridiagonalization of the complex symmetric (not necessarily Hermitian) input matrix using generalized Householder transformations. Example calculations involving so-called PT-symmetric quantum systems lead to reference values which pertain to the imaginary cubic perturbation (the imaginary cubic anharmonic oscillator). We then proceed to novel basis sets for the helium atom and present results for Bethe logarithms in hydrogen and helium, obtained using the enhanced numerical techniques. Some intricacies of ``canned'' algorithms such as those used in LAPACK will be discussed. Our algorithm, for complex symmetric matrices such as those describing cubic resonances after complex scaling, is faster than LAPACK's built-in routines, for specific classes of input matrices. It also offer flexibility in terms of the calculation of the so-called implicit shift, which is used in order to ``pivot'' the system toward the convergence to diagonal form. We conclude with a wider overview.

Navier-Stokes simulation of plume/Vertical Launching System interaction flowfields

NASA Astrophysics Data System (ADS)

York, B. J.; Sinha, N.; Dash, S. M.; Anderson, L.; Gominho, L.

1992-01-01

The application of Navier-Stokes methodology to the analysis of Vertical Launching System/missile exhaust plume interactions is discussed. The complex 3D flowfields related to the Vertical Launching System are computed utilizing the PARCH/RNP Navier-Stokes code. PARCH/RNP solves the fully-coupled system of fluid, two-equation turbulence (k-epsilon) and chemical species equations via the implicit, approximately factored, Beam-Warming algorithm utilizing a block-tridiagonal inversion procedure.

An efficient three-dimensional Poisson solver for SIMD high-performance-computing architectures

NASA Technical Reports Server (NTRS)

Cohl, H.

1994-01-01

We present an algorithm that solves the three-dimensional Poisson equation on a cylindrical grid. The technique uses a finite-difference scheme with operator splitting. This splitting maps the banded structure of the operator matrix into a two-dimensional set of tridiagonal matrices, which are then solved in parallel. Our algorithm couples FFT techniques with the well-known ADI (Alternating Direction Implicit) method for solving Elliptic PDE's, and the implementation is extremely well suited for a massively parallel environment like the SIMD architecture of the MasPar MP-1. Due to the highly recursive nature of our problem, we believe that our method is highly efficient, as it avoids excessive interprocessor communication.

Applications and accuracy of the parallel diagonal dominant algorithm

NASA Technical Reports Server (NTRS)

Sun, Xian-He

1993-01-01

The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiagonal solver. In this paper, a detailed study of the PDD algorithm is given. First the PDD algorithm is introduced. Then the algorithm is extended to solve periodic tridiagonal systems. A variant, the reduced PDD algorithm, is also proposed. Accuracy analysis is provided for a class of tridiagonal systems, the symmetric, and anti-symmetric Toeplitz tridiagonal systems. Implementation results show that the analysis gives a good bound on the relative error, and the algorithm is a good candidate for the emerging massively parallel machines.

On K-Line and K x K Block Iterative Schemes for a Problem Arising in 3-D Elliptic Difference Equations.

DTIC Science & Technology

1980-01-01

VPARTER. , STEUERWALT No 0I 76_C-03AI UNCLASSIFIED CSTR -374 ML M EMON~hEE 111112.08 12.5 111112 1.4 1 1. KWOCP RSLINTS CHR NA11~ L .R~l0 ___VRD I-l...4b) are obtained from the well known algorithm for solving diagonally dominant tridiagonal sys- tems; see (16, 10]. The monotonicity of the Ej and the

Navier-Stokes computation of compressible turbulent flows with a second order closure

NASA Technical Reports Server (NTRS)

Dingus, C.; Kollmann, W.

1991-01-01

The objective was the development of a complete second order closure for wall bounded flows, including all components of the dissipation rate tensor and a numerical solution procedure for the resulting system of equations. The main topics discussed are the closure of the pressure correlations and the viscous destruction terms in the dissipation rate equations and the numerical solution scheme based on a block-tridiagonal solver for the nine equations required for the prediction of plane or axisymmetric flows.

Performance Comparison of a Set of Periodic and Non-Periodic Tridiagonal Solvers on SP2 and Paragon Parallel Computers

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Moitra, Stuti

1996-01-01

Various tridiagonal solvers have been proposed in recent years for different parallel platforms. In this paper, the performance of three tridiagonal solvers, namely, the parallel partition LU algorithm, the parallel diagonal dominant algorithm, and the reduced diagonal dominant algorithm, is studied. These algorithms are designed for distributed-memory machines and are tested on an Intel Paragon and an IBM SP2 machines. Measured results are reported in terms of execution time and speedup. Analytical study are conducted for different communication topologies and for different tridiagonal systems. The measured results match the analytical results closely. In addition to address implementation issues, performance considerations such as problem sizes and models of speedup are also discussed.

Implicit and Multigrid Method for Ideal Multigrid Convergence: Direct Numerical Simulation of Separated Flow Around NACA 0012 Airfoil

NASA Technical Reports Server (NTRS)

Liu, Chao-Qun; Shan, H.; Jiang, L.

1999-01-01

Numerical investigation of flow separation over a NACA 0012 airfoil at large angles of attack has been carried out. The numerical calculation is performed by solving the full Navier-Stokes equations in generalized curvilinear coordinates. The second-order LU-SGS implicit scheme is applied for time integration. This scheme requires no tridiagonal inversion and is capable of being completely vectorized, provided the corresponding Jacobian matrices are properly selected. A fourth-order centered compact scheme is used for spatial derivatives. In order to reduce numerical oscillation, a sixth-order implicit filter is employed. Non-reflecting boundary conditions are imposed at the far-field and outlet boundaries to avoid possible non-physical wave reflection. Complex flow separation and vortex shedding phenomenon have been observed and discussed.

Structure preserving noise and dissipation in the Toda lattice

NASA Astrophysics Data System (ADS)

Arnaudon, Alexis

2018-05-01

In this paper, we use Flaschka’s change of variables of the open Toda lattice and its interpretation in terms of the group structure of the LU factorisation as a coadjoint motion on a certain dual of the Lie algebra to implement a structure preserving noise and dissipation. Both preserve the structure of the coadjoint orbit, that is the space of symmetric tri-diagonal matrices and arise as a new type of multiplicative noise and nonlinear dissipation of the Toda lattice. We investigate some of the properties of these deformations and, in particular, the continuum limit as a stochastic Burger equation with a nonlinear viscosity. This work is meant to be exploratory, and open more questions that we can answer with simple mathematical tools and without numerical simulations.

A tridiagonal parsimonious higher order multivariate Markov chain model

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.

A Fast parallel tridiagonal algorithm for a class of CFD applications

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Sun, Xian-He

1996-01-01

The parallel diagonal dominant (PDD) algorithm is an efficient tridiagonal solver. This paper presents for study a variation of the PDD algorithm, the reduced PDD algorithm. The new algorithm maintains the minimum communication provided by the PDD algorithm, but has a reduced operation count. The PDD algorithm also has a smaller operation count than the conventional sequential algorithm for many applications. Accuracy analysis is provided for the reduced PDD algorithm for symmetric Toeplitz tridiagonal (STT) systems. Implementation results on Langley's Intel Paragon and IBM SP2 show that both the PDD and reduced PDD algorithms are efficient and scalable.

Encoders for block-circulant LDPC codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Abbasfar, Aliazam (Inventor); Jones, Christopher R. (Inventor); Dolinar, Samuel J. (Inventor); Thorpe, Jeremy C. (Inventor); Andrews, Kenneth S. (Inventor); Yao, Kung (Inventor)

2009-01-01

Methods and apparatus to encode message input symbols in accordance with an accumulate-repeat-accumulate code with repetition three or four are disclosed. Block circulant matrices are used. A first method and apparatus make use of the block-circulant structure of the parity check matrix. A second method and apparatus use block-circulant generator matrices.

Solution of a tridiagonal system of equations on the finite element machine

NASA Technical Reports Server (NTRS)

Bostic, S. W.

1984-01-01

Two parallel algorithms for the solution of tridiagonal systems of equations were implemented on the Finite Element Machine. The Accelerated Parallel Gauss method, an iterative method, and the Buneman algorithm, a direct method, are discussed and execution statistics are presented.

Numerical Calculation of Neoclassical Distribution Functions and Current Profiles in Low Collisionality, Axisymmetric Plasmas

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

B.C. Lyons, S.C. Jardin, and J.J. Ramos

2012-06-28

A new code, the Neoclassical Ion-Electron Solver (NIES), has been written to solve for stationary, axisymmetric distribution functions (f ) in the conventional banana regime for both ions and elec trons using a set of drift-kinetic equations (DKEs) with linearized Fokker-Planck-Landau collision operators. Solvability conditions on the DKEs determine the relevant non-adiabatic pieces of f (called h ). We work in a 4D phase space in which Ψ defines a flux surface, θ is the poloidal angle, v is the total velocity referenced to the mean flow velocity, and λ is the dimensionless magnetic moment parameter. We expand h inmore » finite elements in both v and λ . The Rosenbluth potentials, φ and ψ, which define the integral part of the collision operator, are expanded in Legendre series in cos χ , where χ is the pitch angle, Fourier series in cos θ , and finite elements in v . At each ψ , we solve a block tridiagonal system for hi (independent of fe ), then solve another block tridiagonal system for he (dependent on fi ). We demonstrate that such a formulation can be accurately and efficiently solved. NIES is coupled to the MHD equilibrium code JSOLVER [J. DeLucia, et al., J. Comput. Phys. 37 , pp 183-204 (1980).] allowing us to work with realistic magnetic geometries. The bootstrap current is calculated as a simple moment of the distribution function. Results are benchmarked against the Sauter analytic formulas and can be used as a kinetic closure for an MHD code (e.g., M3D-C1 [S.C. Jardin, et al ., Computational Science & Discovery, 4 (2012).]).« less

Vectorization of transport and diffusion computations on the CDC Cyber 205

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

Abu-Shumays, I.K.

1986-01-01

The development and testing of alternative numerical methods and computational algorithms specifically designed for the vectorization of transport and diffusion computations on a Control Data Corporation (CDC) Cyber 205 vector computer are described. Two solution methods for the discrete ordinates approximation to the transport equation are summarized and compared. Factors of 4 to 7 reduction in run times for certain large transport problems were achieved on a Cyber 205 as compared with run times on a CDC-7600. The solution of tridiagonal systems of linear equations, central to several efficient numerical methods for multidimensional diffusion computations and essential for fluid flowmore » and other physics and engineering problems, is also dealt with. Among the methods tested, a combined odd-even cyclic reduction and modified Cholesky factorization algorithm for solving linear symmetric positive definite tridiagonal systems is found to be the most effective for these systems on a Cyber 205. For large tridiagonal systems, computation with this algorithm is an order of magnitude faster on a Cyber 205 than computation with the best algorithm for tridiagonal systems on a CDC-7600.« less

Numerical stability in problems of linear algebra.

NASA Technical Reports Server (NTRS)

Babuska, I.

1972-01-01

Mathematical problems are introduced as mappings from the space of input data to that of the desired output information. Then a numerical process is defined as a prescribed recurrence of elementary operations creating the mapping of the underlying mathematical problem. The ratio of the error committed by executing the operations of the numerical process (the roundoff errors) to the error introduced by perturbations of the input data (initial error) gives rise to the concept of lambda-stability. As examples, several processes are analyzed from this point of view, including, especially, old and new processes for solving systems of linear algebraic equations with tridiagonal matrices. In particular, it is shown how such a priori information can be utilized as, for instance, a knowledge of the row sums of the matrix. Information of this type is frequently available where the system arises in connection with the numerical solution of differential equations.

An adaptive grid algorithm for one-dimensional nonlinear equations

NASA Technical Reports Server (NTRS)

Gutierrez, William E.; Hills, Richard G.

1990-01-01

Richards' equation, which models the flow of liquid through unsaturated porous media, is highly nonlinear and difficult to solve. Step gradients in the field variables require the use of fine grids and small time step sizes. The numerical instabilities caused by the nonlinearities often require the use of iterative methods such as Picard or Newton interation. These difficulties result in large CPU requirements in solving Richards equation. With this in mind, adaptive and multigrid methods are investigated for use with nonlinear equations such as Richards' equation. Attention is focused on one-dimensional transient problems. To investigate the use of multigrid and adaptive grid methods, a series of problems are studied. First, a multigrid program is developed and used to solve an ordinary differential equation, demonstrating the efficiency with which low and high frequency errors are smoothed out. The multigrid algorithm and an adaptive grid algorithm is used to solve one-dimensional transient partial differential equations, such as the diffusive and convective-diffusion equations. The performance of these programs are compared to that of the Gauss-Seidel and tridiagonal methods. The adaptive and multigrid schemes outperformed the Gauss-Seidel algorithm, but were not as fast as the tridiagonal method. The adaptive grid scheme solved the problems slightly faster than the multigrid method. To solve nonlinear problems, Picard iterations are introduced into the adaptive grid and tridiagonal methods. Burgers' equation is used as a test problem for the two algorithms. Both methods obtain solutions of comparable accuracy for similar time increments. For the Burgers' equation, the adaptive grid method finds the solution approximately three times faster than the tridiagonal method. Finally, both schemes are used to solve the water content formulation of the Richards' equation. For this problem, the adaptive grid method obtains a more accurate solution in fewer work units and less computation time than required by the tridiagonal method. The performance of the adaptive grid method tends to degrade as the solution process proceeds in time, but still remains faster than the tridiagonal scheme.

Fast global image smoothing based on weighted least squares.

PubMed

Min, Dongbo; Choi, Sunghwan; Lu, Jiangbo; Ham, Bumsub; Sohn, Kwanghoon; Do, Minh N

2014-12-01

This paper presents an efficient technique for performing a spatially inhomogeneous edge-preserving image smoothing, called fast global smoother. Focusing on sparse Laplacian matrices consisting of a data term and a prior term (typically defined using four or eight neighbors for 2D image), our approach efficiently solves such global objective functions. In particular, we approximate the solution of the memory-and computation-intensive large linear system, defined over a d-dimensional spatial domain, by solving a sequence of 1D subsystems. Our separable implementation enables applying a linear-time tridiagonal matrix algorithm to solve d three-point Laplacian matrices iteratively. Our approach combines the best of two paradigms, i.e., efficient edge-preserving filters and optimization-based smoothing. Our method has a comparable runtime to the fast edge-preserving filters, but its global optimization formulation overcomes many limitations of the local filtering approaches. Our method also achieves high-quality results as the state-of-the-art optimization-based techniques, but runs ∼10-30 times faster. Besides, considering the flexibility in defining an objective function, we further propose generalized fast algorithms that perform Lγ norm smoothing (0 < γ < 2) and support an aggregated (robust) data term for handling imprecise data constraints. We demonstrate the effectiveness and efficiency of our techniques in a range of image processing and computer graphics applications.

Fast Algorithms for Structured Least Squares and Total Least Squares Problems

PubMed Central

Kalsi, Anoop; O’Leary, Dianne P.

2006-01-01

We consider the problem of solving least squares problems involving a matrix M of small displacement rank with respect to two matrices Z1 and Z2. We develop formulas for the generators of the matrix M HM in terms of the generators of M and show that the Cholesky factorization of the matrix M HM can be computed quickly if Z1 is close to unitary and Z2 is triangular and nilpotent. These conditions are satisfied for several classes of matrices, including Toeplitz, block Toeplitz, Hankel, and block Hankel, and for matrices whose blocks have such structure. Fast Cholesky factorization enables fast solution of least squares problems, total least squares problems, and regularized total least squares problems involving these classes of matrices. PMID:27274922

Fast Algorithms for Structured Least Squares and Total Least Squares Problems.

PubMed

Kalsi, Anoop; O'Leary, Dianne P

2006-01-01

We consider the problem of solving least squares problems involving a matrix M of small displacement rank with respect to two matrices Z 1 and Z 2. We develop formulas for the generators of the matrix M (H) M in terms of the generators of M and show that the Cholesky factorization of the matrix M (H) M can be computed quickly if Z 1 is close to unitary and Z 2 is triangular and nilpotent. These conditions are satisfied for several classes of matrices, including Toeplitz, block Toeplitz, Hankel, and block Hankel, and for matrices whose blocks have such structure. Fast Cholesky factorization enables fast solution of least squares problems, total least squares problems, and regularized total least squares problems involving these classes of matrices.

Band gap engineering in finite elongated graphene nanoribbon heterojunctions: Tight-binding model

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

Tayo, Benjamin O.

2015-08-15

A simple model based on the divide and conquer rule and tight-binding (TB) approximation is employed for studying the role of finite size effect on the electronic properties of elongated graphene nanoribbon (GNR) heterojunctions. In our model, the GNR heterojunction is divided into three parts: a left (L) part, middle (M) part, and right (R) part. The left part is a GNR of width W{sub L}, the middle part is a GNR of width W{sub M}, and the right part is a GNR of width W{sub R}. We assume that the left and right parts of the GNR heterojunction interactmore » with the middle part only. Under this approximation, the Hamiltonian of the system can be expressed as a block tridiagonal matrix. The matrix elements of the tridiagonal matrix are computed using real space nearest neighbor orthogonal TB approximation. The electronic structure of the GNR heterojunction is analyzed by computing the density of states. We demonstrate that for heterojunctions for which W{sub L} = W{sub R}, the band gap of the system can be tuned continuously by varying the length of the middle part, thus providing a new approach to band gap engineering in GNRs. Our TB results were compared with calculations employing divide and conquer rule in combination with density functional theory (DFT) and were found to agree nicely.« less

The Laguerre finite difference one-way equation solver

NASA Astrophysics Data System (ADS)

Terekhov, Andrew V.

2017-05-01

This paper presents a new finite difference algorithm for solving the 2D one-way wave equation with a preliminary approximation of a pseudo-differential operator by a system of partial differential equations. As opposed to the existing approaches, the integral Laguerre transform instead of Fourier transform is used. After carrying out the approximation of spatial variables it is possible to obtain systems of linear algebraic equations with better computing properties and to reduce computer costs for their solution. High accuracy of calculations is attained at the expense of employing finite difference approximations of higher accuracy order that are based on the dispersion-relationship-preserving method and the Richardson extrapolation in the downward continuation direction. The numerical experiments have verified that as compared to the spectral difference method based on Fourier transform, the new algorithm allows one to calculate wave fields with a higher degree of accuracy and a lower level of numerical noise and artifacts including those for non-smooth velocity models. In the context of solving the geophysical problem the post-stack migration for velocity models of the types Syncline and Sigsbee2A has been carried out. It is shown that the images obtained contain lesser noise and are considerably better focused as compared to those obtained by the known Fourier Finite Difference and Phase-Shift Plus Interpolation methods. There is an opinion that purely finite difference approaches do not allow carrying out the seismic migration procedure with sufficient accuracy, however the results obtained disprove this statement. For the supercomputer implementation it is proposed to use the parallel dichotomy algorithm when solving systems of linear algebraic equations with block-tridiagonal matrices.

Novel image compression-encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Zhang, Aidi; Zheng, Fen; Gong, Lihua

2014-10-01

The existing ways to encrypt images based on compressive sensing usually treat the whole measurement matrix as the key, which renders the key too large to distribute and memorize or store. To solve this problem, a new image compression-encryption hybrid algorithm is proposed to realize compression and encryption simultaneously, where the key is easily distributed, stored or memorized. The input image is divided into 4 blocks to compress and encrypt, then the pixels of the two adjacent blocks are exchanged randomly by random matrices. The measurement matrices in compressive sensing are constructed by utilizing the circulant matrices and controlling the original row vectors of the circulant matrices with logistic map. And the random matrices used in random pixel exchanging are bound with the measurement matrices. Simulation results verify the effectiveness, security of the proposed algorithm and the acceptable compression performance.

Face recognition using tridiagonal matrix enhanced multivariance products representation

NASA Astrophysics Data System (ADS)

Ã-zay, Evrim Korkmaz

2017-01-01

This study aims to retrieve face images from a database according to a target face image. For this purpose, Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is taken into consideration. TMEMPR is a recursive algorithm based on Enhanced Multivariance Products Representation (EMPR). TMEMPR decomposes a matrix into three components which are a matrix of left support terms, a tridiagonal matrix of weight parameters for each recursion, and a matrix of right support terms, respectively. In this sense, there is an analogy between Singular Value Decomposition (SVD) and TMEMPR. However TMEMPR is a more flexible algorithm since its initial support terms (or vectors) can be chosen as desired. Low computational complexity is another advantage of TMEMPR because the algorithm has been constructed with recursions of certain arithmetic operations without requiring any iteration. The algorithm has been trained and tested with ORL face image database with 400 different grayscale images of 40 different people. TMEMPR's performance has been compared with SVD's performance as a result.

A Perron-Frobenius theory for block matrices associated to a multiplex network

NASA Astrophysics Data System (ADS)

Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

2015-03-01

The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers.

Simplicity and Typical Rank Results for Three-Way Arrays

ERIC Educational Resources Information Center

ten Berge, Jos M. F.

2011-01-01

Matrices can be diagonalized by singular vectors or, when they are symmetric, by eigenvectors. Pairs of square matrices often admit simultaneous diagonalization, and always admit block wise simultaneous diagonalization. Generalizing these possibilities to more than two (non-square) matrices leads to methods of simplifying three-way arrays by…

Neutron Multiplicity: LANL W Covariance Matrix for Curve Fitting

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

Wendelberger, James G.

2016-12-08

In neutron multiplicity counting one may fit a curve by minimizing an objective function, χmore » $$2\\atop{n}$$. The objective function includes the inverse of an n by n matrix of covariances, W. The inverse of the W matrix has a closed form solution. In addition W -1 is a tri-diagonal matrix. The closed form and tridiagonal nature allows for a simpler expression of the objective function χ$$2\\atop{n}$$. Minimization of this simpler expression will provide the optimal parameters for the fitted curve.« less

Universality for 1d Random Band Matrices: Sigma-Model Approximation

NASA Astrophysics Data System (ADS)

Shcherbina, Mariya; Shcherbina, Tatyana

2018-02-01

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in (J Stat Phys 164:1233-1260, 2016; Commun Math Phys 351:1009-1044, 2017). We consider random Hermitian block band matrices consisting of W× W random Gaussian blocks (parametrized by j,k \\in Λ =[1,n]^d\\cap Z^d ) with a fixed entry's variance J_{jk}=δ _{j,k}W^{-1}+β Δ _{j,k}W^{-2} , β >0 in each block. Taking the limit W→ ∞ with fixed n and β , we derive the sigma-model approximation of the second correlation function similar to Efetov's one. Then, considering the limit β , n→ ∞, we prove that in the dimension d=1 the behaviour of the sigma-model approximation in the bulk of the spectrum, as β ≫ n , is determined by the classical Wigner-Dyson statistics.

Numerical methods on some structured matrix algebra problems

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

Jessup, E.R.

1996-06-01

This proposal concerned the design, analysis, and implementation of serial and parallel algorithms for certain structured matrix algebra problems. It emphasized large order problems and so focused on methods that can be implemented efficiently on distributed-memory MIMD multiprocessors. Such machines supply the computing power and extensive memory demanded by the large order problems. We proposed to examine three classes of matrix algebra problems: the symmetric and nonsymmetric eigenvalue problems (especially the tridiagonal cases) and the solution of linear systems with specially structured coefficient matrices. As all of these are of practical interest, a major goal of this work was tomore » translate our research in linear algebra into useful tools for use by the computational scientists interested in these and related applications. Thus, in addition to software specific to the linear algebra problems, we proposed to produce a programming paradigm and library to aid in the design and implementation of programs for distributed-memory MIMD computers. We now report on our progress on each of the problems and on the programming tools.« less

An efficient parallel algorithm for the solution of a tridiagonal linear system of equations

NASA Technical Reports Server (NTRS)

Stone, H. S.

1971-01-01

Tridiagonal linear systems of equations are solved on conventional serial machines in a time proportional to N, where N is the number of equations. The conventional algorithms do not lend themselves directly to parallel computations on computers of the ILLIAC IV class, in the sense that they appear to be inherently serial. An efficient parallel algorithm is presented in which computation time grows as log sub 2 N. The algorithm is based on recursive doubling solutions of linear recurrence relations, and can be used to solve recurrence relations of all orders.

Efficient Parallel Algorithm For Direct Numerical Simulation of Turbulent Flows

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Gatski, Thomas B.

1997-01-01

A distributed algorithm for a high-order-accurate finite-difference approach to the direct numerical simulation (DNS) of transition and turbulence in compressible flows is described. This work has two major objectives. The first objective is to demonstrate that parallel and distributed-memory machines can be successfully and efficiently used to solve computationally intensive and input/output intensive algorithms of the DNS class. The second objective is to show that the computational complexity involved in solving the tridiagonal systems inherent in the DNS algorithm can be reduced by algorithm innovations that obviate the need to use a parallelized tridiagonal solver.

Block-circulant matrices with circulant blocks, Weil sums, and mutually unbiased bases. II. The prime power case

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

Combescure, Monique

2009-03-15

In our previous paper [Combescure, M., 'Circulant matrices, Gauss sums and the mutually unbiased bases. I. The prime number case', Cubo A Mathematical Journal (unpublished)] we have shown that the theory of circulant matrices allows to recover the result that there exists p+1 mutually unbiased bases in dimension p, p being an arbitrary prime number. Two orthonormal bases B, B{sup '} of C{sup d} are said mutually unbiased if for all b(set-membership sign)B, for all b{sup '}(set-membership sign)B{sup '} one has that |b{center_dot}b{sup '}|=1/{radical}(d) (b{center_dot}b{sup '} Hermitian scalar product in C{sup d}). In this paper we show that the theorymore » of block-circulant matrices with circulant blocks allows to show very simply the known result that if d=p{sup n} (p a prime number and n any integer) there exists d+1 mutually unbiased bases in C{sup d}. Our result relies heavily on an idea of Klimov et al. [''Geometrical approach to the discrete Wigner function,'' J. Phys. A 39, 14471 (2006)]. As a subproduct we recover properties of quadratic Weil sums for p{>=}3, which generalizes the fact that in the prime case the quadratic Gauss sum properties follow from our results.« less

Arikan and Alamouti matrices based on fast block-wise inverse Jacket transform

NASA Astrophysics Data System (ADS)

Lee, Moon Ho; Khan, Md Hashem Ali; Kim, Kyeong Jin

2013-12-01

Recently, Lee and Hou (IEEE Signal Process Lett 13: 461-464, 2006) proposed one-dimensional and two-dimensional fast algorithms for block-wise inverse Jacket transforms (BIJTs). Their BIJTs are not real inverse Jacket transforms from mathematical point of view because their inverses do not satisfy the usual condition, i.e., the multiplication of a matrix with its inverse matrix is not equal to the identity matrix. Therefore, we mathematically propose a fast block-wise inverse Jacket transform of orders N = 2 k , 3 k , 5 k , and 6 k , where k is a positive integer. Based on the Kronecker product of the successive lower order Jacket matrices and the basis matrix, the fast algorithms for realizing these transforms are obtained. Due to the simple inverse and fast algorithms of Arikan polar binary and Alamouti multiple-input multiple-output (MIMO) non-binary matrices, which are obtained from BIJTs, they can be applied in areas such as 3GPP physical layer for ultra mobile broadband permutation matrices design, first-order q-ary Reed-Muller code design, diagonal channel design, diagonal subchannel decompose for interference alignment, and 4G MIMO long-term evolution Alamouti precoding design.

Automatic Blocking Of QR and LU Factorizations for Locality

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

Yi, Q; Kennedy, K; You, H

2004-03-26

QR and LU factorizations for dense matrices are important linear algebra computations that are widely used in scientific applications. To efficiently perform these computations on modern computers, the factorization algorithms need to be blocked when operating on large matrices to effectively exploit the deep cache hierarchy prevalent in today's computer memory systems. Because both QR (based on Householder transformations) and LU factorization algorithms contain complex loop structures, few compilers can fully automate the blocking of these algorithms. Though linear algebra libraries such as LAPACK provides manually blocked implementations of these algorithms, by automatically generating blocked versions of the computations, moremore » benefit can be gained such as automatic adaptation of different blocking strategies. This paper demonstrates how to apply an aggressive loop transformation technique, dependence hoisting, to produce efficient blockings for both QR and LU with partial pivoting. We present different blocking strategies that can be generated by our optimizer and compare the performance of auto-blocked versions with manually tuned versions in LAPACK, both using reference BLAS, ATLAS BLAS and native BLAS specially tuned for the underlying machine architectures.« less

Non-linear three dimensional spectral model of the Venusian thermosphere with super-rotation. I - Formulation and numerical technique. II - Temperature, composition and winds

NASA Technical Reports Server (NTRS)

Stevens-Rayburn, D. R.; Mengel, J. G.; Harris, I.; Mayr, H. G.

1989-01-01

A three-dimensional spectral model for the Venusion thermosphere is presented which uses spherical harmonics to represent the horizontal variations in longitude and latitude and which uses Fourier harmonics to represent the LT variations due to atmospheric rotation. A differencing scheme with tridiagonal block elimination is used to perform the height integration. Quadratic nonlinearities are taken into account. In the second part, numerical results obtained with the model are shown to reproduce the observed broad daytime maxima in CO2 and CO and the significantly larger values at dawn than at dusk. It is found that the diurnal variations in He are most sensitive to thermospheric superrotation, and that, given a globally uniform atmosphere as input, larger heating rates yield a larger temperature contrast between day and night.

Numerical methods for the unsymmetric tridiagonal eigenvalue problem

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

Jessup, E.R.

1996-12-31

This report summarizes the results of our project {open_quotes}Numerical Methods for the Unsymmetric Tridiagonal Eigenvalue Problem{close_quotes}. It was funded by both by a DOE grant (No. DE-FG02-92ER25122, 6/1/92-5/31/94, $100,000) and by an NSF Research Initiation Award (No. CCR-9109785, 7/1/91-6/30/93, $46,564.) The publications resulting from that project during the DOE funding period are listed below. Two other journal papers and two other conference papers were produced during the NSF funding period. Most of the listed conference papers are early or partial versions of the listed journal papers.

A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices.

PubMed

Brusco, Michael; Steinley, Douglas

2011-10-01

Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where the goal is to identify partitions for the row and column objects such that the clusters of the row and column objects form blocks that are either complete (all 1s) or null (all 0s) to the greatest extent possible. Multiple restarts of an object relocation heuristic that seeks to minimize the number of inconsistencies (i.e., 1s in null blocks and 0s in complete blocks) with ideal block structure is the predominant approach for tackling this problem. As an alternative, we propose a fast and effective implementation of tabu search. Computational comparisons across a set of 48 large network matrices revealed that the new tabu-search heuristic always provided objective function values that were better than those of the relocation heuristic when the two methods were constrained to the same amount of computation time.

Genetic code, hamming distance and stochastic matrices.

PubMed

He, Matthew X; Petoukhov, Sergei V; Ricci, Paolo E

2004-09-01

In this paper we use the Gray code representation of the genetic code C=00, U=10, G=11 and A=01 (C pairs with G, A pairs with U) to generate a sequence of genetic code-based matrices. In connection with these code-based matrices, we use the Hamming distance to generate a sequence of numerical matrices. We then further investigate the properties of the numerical matrices and show that they are doubly stochastic and symmetric. We determine the frequency distributions of the Hamming distances, building blocks of the matrices, decomposition and iterations of matrices. We present an explicit decomposition formula for the genetic code-based matrix in terms of permutation matrices, which provides a hypercube representation of the genetic code. It is also observed that there is a Hamiltonian cycle in a genetic code-based hypercube.

An efficient parallel-processing method for transposing large matrices in place.

PubMed

Portnoff, M R

1999-01-01

We have developed an efficient algorithm for transposing large matrices in place. The algorithm is efficient because data are accessed either sequentially in blocks or randomly within blocks small enough to fit in cache, and because the same indexing calculations are shared among identical procedures operating on independent subsets of the data. This inherent parallelism makes the method well suited for a multiprocessor computing environment. The algorithm is easy to implement because the same two procedures are applied to the data in various groupings to carry out the complete transpose operation. Using only a single processor, we have demonstrated nearly an order of magnitude increase in speed over the previously published algorithm by Gate and Twigg for transposing a large rectangular matrix in place. With multiple processors operating in parallel, the processing speed increases almost linearly with the number of processors. A simplified version of the algorithm for square matrices is presented as well as an extension for matrices large enough to require virtual memory.

Solution of the nonlinear mixed Volterra-Fredholm integral equations by hybrid of block-pulse functions and Bernoulli polynomials.

PubMed

Mashayekhi, S; Razzaghi, M; Tripak, O

2014-01-01

A new numerical method for solving the nonlinear mixed Volterra-Fredholm integral equations is presented. This method is based upon hybrid functions approximation. The properties of hybrid functions consisting of block-pulse functions and Bernoulli polynomials are presented. The operational matrices of integration and product are given. These matrices are then utilized to reduce the nonlinear mixed Volterra-Fredholm integral equations to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.

Solution of the Nonlinear Mixed Volterra-Fredholm Integral Equations by Hybrid of Block-Pulse Functions and Bernoulli Polynomials

PubMed Central

Mashayekhi, S.; Razzaghi, M.; Tripak, O.

2014-01-01

A new numerical method for solving the nonlinear mixed Volterra-Fredholm integral equations is presented. This method is based upon hybrid functions approximation. The properties of hybrid functions consisting of block-pulse functions and Bernoulli polynomials are presented. The operational matrices of integration and product are given. These matrices are then utilized to reduce the nonlinear mixed Volterra-Fredholm integral equations to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique. PMID:24523638

An O(log sup 2 N) parallel algorithm for computing the eigenvalues of a symmetric tridiagonal matrix

NASA Technical Reports Server (NTRS)

Swarztrauber, Paul N.

1989-01-01

An O(log sup 2 N) parallel algorithm is presented for computing the eigenvalues of a symmetric tridiagonal matrix using a parallel algorithm for computing the zeros of the characteristic polynomial. The method is based on a quadratic recurrence in which the characteristic polynomial is constructed on a binary tree from polynomials whose degree doubles at each level. Intervals that contain exactly one zero are determined by the zeros of polynomials at the previous level which ensures that different processors compute different zeros. The exact behavior of the polynomials at the interval endpoints is used to eliminate the usual problems induced by finite precision arithmetic.

Solving the linear inviscid shallow water equations in one dimension, with variable depth, using a recursion formula

NASA Astrophysics Data System (ADS)

Hernandez-Walls, R.; Martín-Atienza, B.; Salinas-Matus, M.; Castillo, J.

2017-11-01

When solving the linear inviscid shallow water equations with variable depth in one dimension using finite differences, a tridiagonal system of equations must be solved. Here we present an approach, which is more efficient than the commonly used numerical method, to solve this tridiagonal system of equations using a recursion formula. We illustrate this approach with an example in which we solve for a rectangular channel to find the resonance modes. Our numerical solution agrees very well with the analytical solution. This new method is easy to use and understand by undergraduate students, so it can be implemented in undergraduate courses such as Numerical Methods, Lineal Algebra or Differential Equations.

Application of the implicit MacCormack scheme to the PNS equations

NASA Technical Reports Server (NTRS)

Lawrence, S. L.; Tannehill, J. C.; Chaussee, D. S.

1983-01-01

The two-dimensional parabolized Navier-Stokes equations are solved using MacCormack's (1981) implicit finite-difference scheme. It is shown that this method for solving the parabolized Navier-Stokes equations does not require the inversion of block tridiagonal systems of algebraic equations and allows the original explicit scheme to be employed in those regions where implicit treatment is not needed. The finite-difference algorithm is discussed and the computational results for two laminar test cases are presented. Results obtained using this method for the case of a flat plate boundary layer are compared with those obtained using the conventional Beam-Warming scheme, as well as those obtained from a boundary layer code. The computed results for a more severe test of the method, the hypersonic flow past a 15 deg compression corner, are found to compare favorably with experiment and a numerical solution of the complete Navier-Stokes equations.

Multiple-body simulation with emphasis on integrated Space Shuttle vehicle

NASA Technical Reports Server (NTRS)

Chiu, Ing-Tsau

1993-01-01

The program to obtain intergrid communications - Pegasus - was enhanced to make better use of computing resources. Periodic block tridiagonal and penta-diagonal diagonal routines in OVERFLOW were modified to use a better algorithm to speed up the calculation for grids with periodic boundary conditions. Several programs were added to collar grid tools and a user friendly shell script was developed to help users generate collar grids. User interface for HYPGEN was modified to cope with the changes in HYPGEN. ET/SRB attach hardware grids were added to the computational model for the space shuttle and is currently incorporated into the refined shuttle model jointly developed at Johnson Space Center and Ames Research Center. Flow simulation for the integrated space shuttle vehicle at flight Reynolds number was carried out and compared with flight data as well as the earlier simulation for wind tunnel Reynolds number.

Calculation of flow about two-dimensional bodies by means of the velocity-vorticity formulation on a staggered grid

NASA Technical Reports Server (NTRS)

Stremel, Paul M.

1991-01-01

A method for calculating the incompressible viscous flow about two-dimensional bodies, utilizing the velocity-vorticity form of the Navier-Stokes equations using a staggered-grid formulation is presented. The solution is obtained by employing an alternative-direction implicit method for the solution of the block tridiagonal matrix resulting from the finite-difference representation of the governing equations. The boundary vorticity and the conservation of mass are calculated implicitly as a part of the solution. The mass conservation is calculated to machine zero for the duration of the computation. Calculations for the flow about a circular cylinder, a 2-pct thick flat plate at 90-deg incidence, an elliptic cylinder at 45-deg incidence, and a NACA 0012, with and without a deflected flap, at - 90-deg incidence are performed and compared with the results of other numerical investigations.

Dynamics of a Dirac oscillator coupled to an external field: a new class of solvable problems

NASA Astrophysics Data System (ADS)

Sadurní, E.; Torres, J. M.; Seligman, T. H.

2010-07-01

The Dirac oscillator coupled to an external two-component field can retain its solvability, if couplings are appropriately chosen. This provides a new class of integrable systems. A simplified way of a solution is given by recasting the known solution of the Dirac oscillator into matrix form; there one notes that a block-diagonal form arises in a Hamiltonian formulation. The blocks are two dimensional. Choosing couplings that do not affect the block structure, these blow up the 2 × 2 matrices to 4 × 4 matrices, thus conserving solvability. The result can be cast again in covariant form. By way of an example we apply this exact solution to calculate the evolution of entanglement.

Vibration and stress analysis of soft-bonded shuttle insulation tiles. Modal analysis with compact widely space stringers

NASA Technical Reports Server (NTRS)

Ojalvo, I. U.; Austin, F.; Levy, A.

1974-01-01

An efficient iterative procedure is described for the vibration and modal stress analysis of reusable surface insulation (RSI) of multi-tiled space shuttle panels. The method, which is quite general, is rapidly convergent and highly useful for this application. A user-oriented computer program based upon this procedure and titled RESIST (REusable Surface Insulation Stresses) has been prepared for the analysis of compact, widely spaced, stringer-stiffened panels. RESIST, which uses finite element methods, obtains three dimensional tile stresses in the isolator, arrestor (if any) and RSI materials. Two dimensional stresses are obtained in the tile coating and the stringer-stiffened primary structure plate. A special feature of the program is that all the usual detailed finite element grid data is generated internally from a minimum of input data. The program can accommodate tile idealizations with up to 850 nodes (2550 degrees-of-freedom) and primary structure idealizations with a maximum of 10,000 degrees-of-freedom. The primary structure vibration capability is achieved through the development of a new rapid eigenvalue program named ALARM (Automatic LArge Reduction of Matrices to tridiagonal form).

Ground State and Finite Temperature Lanczos Methods

NASA Astrophysics Data System (ADS)

Prelovšek, P.; Bonča, J.

The present review will focus on recent development of exact- diagonalization (ED) methods that use Lanczos algorithm to transform large sparse matrices onto the tridiagonal form. We begin with a review of basic principles of the Lanczos method for computing ground-state static as well as dynamical properties. Next, generalization to finite-temperatures in the form of well established finite-temperature Lanczos method is described. The latter allows for the evaluation of temperatures T>0 static and dynamic quantities within various correlated models. Several extensions and modification of the latter method introduced more recently are analysed. In particular, the low-temperature Lanczos method and the microcanonical Lanczos method, especially applicable within the high-T regime. In order to overcome the problems of exponentially growing Hilbert spaces that prevent ED calculations on larger lattices, different approaches based on Lanczos diagonalization within the reduced basis have been developed. In this context, recently developed method based on ED within a limited functional space is reviewed. Finally, we briefly discuss the real-time evolution of correlated systems far from equilibrium, which can be simulated using the ED and Lanczos-based methods, as well as approaches based on the diagonalization in a reduced basis.

CONTRIBUTION TO THE THEORY OF MATRICES PARTITIONED INTO BLOCKS.

DTIC Science & Technology

results were obtained on cones of matrices and vectors, and an extension of the well-known Perron - Frobenius theorem was proved. Also a necessary and...sufficient condition was derived, in order that to a given matrix corresponds a cone on which it is a positive operator. Easily computed upper and

Matrix Summaries Improve Research Reports: Secondary Analyses Using Published Literature

ERIC Educational Resources Information Center

Zientek, Linda Reichwein; Thompson, Bruce

2009-01-01

Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…

A Partitioning Algorithm for Block-Diagonal Matrices With Overlap

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

Guy Antoine Atenekeng Kahou; Laura Grigori; Masha Sosonkina

2008-02-02

We present a graph partitioning algorithm that aims at partitioning a sparse matrix into a block-diagonal form, such that any two consecutive blocks overlap. We denote this form of the matrix as the overlapped block-diagonal matrix. The partitioned matrix is suitable for applying the explicit formulation of Multiplicative Schwarz preconditioner (EFMS) described in [3]. The graph partitioning algorithm partitions the graph of the input matrix into K partitions, such that every partition {Omega}{sub i} has at most two neighbors {Omega}{sub i-1} and {Omega}{sub i+1}. First, an ordering algorithm, such as the reverse Cuthill-McKee algorithm, that reduces the matrix profile ismore » performed. An initial overlapped block-diagonal partition is obtained from the profile of the matrix. An iterative strategy is then used to further refine the partitioning by allowing nodes to be transferred between neighboring partitions. Experiments are performed on matrices arising from real-world applications to show the feasibility and usefulness of this approach.« less

Parallel solution of the symmetric tridiagonal eigenproblem. Research report

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

Jessup, E.R.

1989-10-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed-memory Multiple Instruction, Multiple Data multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speed up, and accuracy. Experiments on an IPSC hypercube multiprocessor reveal that Cuppen's method ismore » the most accurate approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effect of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptions of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Parallel solution of the symmetric tridiagonal eigenproblem

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

Jessup, E.R.

1989-01-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed memory MIMD multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues, and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speedup, and accuracy. Experiments on an iPSC hyper-cube multiprocessor reveal that Cuppen's method is the most accuratemore » approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effects of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptations of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Perceptual Optimization of DCT Color Quantization Matrices

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Statler, Irving C. (Technical Monitor)

1994-01-01

Many image compression schemes employ a block Discrete Cosine Transform (DCT) and uniform quantization. Acceptable rate/distortion performance depends upon proper design of the quantization matrix. In previous work, we showed how to use a model of the visibility of DCT basis functions to design quantization matrices for arbitrary display resolutions and color spaces. Subsequently, we showed how to optimize greyscale quantization matrices for individual images, for optimal rate/perceptual distortion performance. Here we describe extensions of this optimization algorithm to color images.

Algorithm 782 : codes for rank-revealing QR factorizations of dense matrices.

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

Bischof, C. H.; Quintana-Orti, G.; Mathematics and Computer Science

1998-06-01

This article describes a suite of codes as well as associated testing and timing drivers for computing rank-revealing QR (RRQR) factorizations of dense matrices. The main contribution is an efficient block algorithm for approximating an RRQR factorization, employing a windowed version of the commonly used Golub pivoting strategy and improved versions of the RRQR algorithms for triangular matrices originally suggested by Chandrasekaran and Ipsen and by Pan and Tang, respectively, We highlight usage and features of these codes.

Replica Fourier Tansforms on Ultrametric Trees, and Block-Diagonalizing Multi-Replica Matrices

NASA Astrophysics Data System (ADS)

de Dominicis, C.; Carlucci, D. M.; Temesvári, T.

1997-01-01

The analysis of objects living on ultrametric trees, in particular the block-diagonalization of 4-replica matrices M^{α β;γ^δ}, is shown to be dramatically simplified through the introduction of properly chosen operations on those objects. These are the Replica Fourier Transforms on ultrametric trees. Those transformations are defined and used in the present work. On montre que l'analyse d'objets vivant sur un arbre ultramétrique, en particulier, la diagonalisation par blocs d'une matrice M^{α β;γ^δ} dépendant de 4-répliques, se simplifie de façon dramatique si l'on introduit les opérations appropriées sur ces objets. Ce sont les Transformées de Fourier de Répliques sur un arbre ultramétrique. Ces transformations sont définies et utilisées dans le présent travail.

A Navier-Strokes Chimera Code on the Connection Machine CM-5: Design and Performance

NASA Technical Reports Server (NTRS)

Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

1994-01-01

We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.

Wall-crossing invariants: from quantum mechanics to knots

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

Galakhov, D., E-mail: galakhov@itep.ru, E-mail: galakhov@physics.rutgers.edu; Mironov, A., E-mail: mironov@lpi.ru; Morozov, A., E-mail: morozov@itep.ru

2015-03-15

We offer a pedestrian-level review of the wall-crossing invariants. The story begins from the scattering theory in quantum mechanics where the spectrum reshuffling can be related to permutations of S-matrices. In nontrivial situations, starting from spin chains and matrix models, the S-matrices are operatorvalued and their algebra is described in terms of R- and mixing (Racah) U-matrices. Then the Kontsevich-Soibelman (KS) invariants are nothing but the standard knot invariants made out of these data within the Reshetikhin-Turaev-Witten approach. The R and Racah matrices acquire a relatively universal form in the semiclassical limit, where the basic reshufflings with the change ofmore » moduli are those of the Stokes line. Natural from this standpoint are matrices provided by the modular transformations of conformal blocks (with the usual identification R = T and U = S), and in the simplest case of the first degenerate field (2, 1), when the conformal blocks satisfy a second-order Shrödinger-like equation, the invariants coincide with the Jones (N = 2) invariants of the associated knots. Another possibility to construct knot invariants is to realize the cluster coordinates associated with reshufflings of the Stokes lines immediately in terms of check-operators acting on solutions of the Knizhnik-Zamolodchikov equations. Then the R-matrices are realized as products of successive mutations in the cluster algebra and are manifestly described in terms of quantum dilogarithms, ultimately leading to the Hikami construction of knot invariants.« less

Computing rank-revealing QR factorizations of dense matrices.

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

Bischof, C. H.; Quintana-Orti, G.; Mathematics and Computer Science

1998-06-01

We develop algorithms and implementations for computing rank-revealing QR (RRQR) factorizations of dense matrices. First, we develop an efficient block algorithm for approximating an RRQR factorization, employing a windowed version of the commonly used Golub pivoting strategy, aided by incremental condition estimation. Second, we develop efficiently implementable variants of guaranteed reliable RRQR algorithms for triangular matrices originally suggested by Chandrasekaran and Ipsen and by Pan and Tang. We suggest algorithmic improvements with respect to condition estimation, termination criteria, and Givens updating. By combining the block algorithm with one of the triangular postprocessing steps, we arrive at an efficient and reliablemore » algorithm for computing an RRQR factorization of a dense matrix. Experimental results on IBM RS/6000 SGI R8000 platforms show that this approach performs up to three times faster that the less reliable QR factorization with column pivoting as it is currently implemented in LAPACK, and comes within 15% of the performance of the LAPACK block algorithm for computing a QR factorization without any column exchanges. Thus, we expect this routine to be useful in may circumstances where numerical rank deficiency cannot be ruled out, but currently has been ignored because of the computational cost of dealing with it.« less

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

VX fate on common matrices: evaporation versus degradation.

PubMed

Columbus, Ishay; Waysbort, Daniel; Marcovitch, Itzhak; Yehezkel, Lea; Mizrahi, Dana M

2012-04-03

A study of the volatilization rate of the nerve agent VX (O-ethyl S-2-(N,N-diisopropylamino)ethyl methylphosphonothiolate) from various urban matrices in a specially designed climatic chamber (model system) is described. The performance of the model system combined with the analytical procedure produced profiles of vapor concentration obtained from samples of VX dispersed as small droplets on the surfaces of the matrices. The results indicated that the bitumen-containing surfaces such as asphalt blocks and bitumen sheets conserve VX and slow-release part of it over a long period of time. No complete mass balance could be obtained for these surfaces. Influence of environmental and experimental parameters as well as the efficacy of decontamination procedure were also measured. From smooth surface tiles a fast release of VX was measured and almost a complete mass balance was obtained, which characterizes the behavior of inert surfaces. Experiments carried out on concrete blocks showed fast decay of the concentration profile along with a very poor reconstruction of the initial quantity of VX, implying that this matrix degraded VX actively due to its multiple basic catalytic sites. To complement this study, solid-state NMR measurements were compared to add data concerning agent-fate within the matrices.

The "SIMCLAS" Model: Simultaneous Analysis of Coupled Binary Data Matrices with Noise Heterogeneity between and within Data Blocks

ERIC Educational Resources Information Center

Wilderjans, Tom F.; Ceulemans, E.; Van Mechelen, I.

2012-01-01

In many research domains different pieces of information are collected regarding the same set of objects. Each piece of information constitutes a data block, and all these (coupled) blocks have the object mode in common. When analyzing such data, an important aim is to obtain an overall picture of the structure underlying the whole set of coupled…

NANOSTRUCTURED METAL OXIDE CATALYSTS VIA BUILDING BLOCK SYNTHESES

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

Craig E. Barnes

2013-03-05

A broadly applicable methodology has been developed to prepare new single site catalysts on silica supports. This methodology requires of three critical components: a rigid building block that will be the main structural and compositional component of the support matrix; a family of linking reagents that will be used to insert active metals into the matrix as well as cross link building blocks into a three dimensional matrix; and a clean coupling reaction that will connect building blocks and linking agents together in a controlled fashion. The final piece of conceptual strategy at the center of this methodology involves dosingmore » the building block with known amounts of linking agents so that the targeted connectivity of a linking center to surrounding building blocks is obtained. Achieving targeted connectivities around catalytically active metals in these building block matrices is a critical element of the strategy by which single site catalysts are obtained. This methodology has been demonstrated with a model system involving only silicon and then with two metal-containing systems (titanium and vanadium). The effect that connectivity has on the reactivity of atomically dispersed titanium sites in silica building block matrices has been investigated in the selective oxidation of phenols to benezoquinones. 2-connected titanium sites are found to be five times as active (i.e. initial turnover frequencies) than 4-connected titanium sites (i.e. framework titanium sites).« less

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.

A Textbook for a First Course in Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Zingg, D. W.; Pulliam, T. H.; Nixon, David (Technical Monitor)

1999-01-01

This paper describes and discusses the textbook, Fundamentals of Computational Fluid Dynamics by Lomax, Pulliam, and Zingg, which is intended for a graduate level first course in computational fluid dynamics. This textbook emphasizes fundamental concepts in developing, analyzing, and understanding numerical methods for the partial differential equations governing the physics of fluid flow. Its underlying philosophy is that the theory of linear algebra and the attendant eigenanalysis of linear systems provides a mathematical framework to describe and unify most numerical methods in common use in the field of fluid dynamics. Two linear model equations, the linear convection and diffusion equations, are used to illustrate concepts throughout. Emphasis is on the semi-discrete approach, in which the governing partial differential equations (PDE's) are reduced to systems of ordinary differential equations (ODE's) through a discretization of the spatial derivatives. The ordinary differential equations are then reduced to ordinary difference equations (O(Delta)E's) using a time-marching method. This methodology, using the progression from PDE through ODE's to O(Delta)E's, together with the use of the eigensystems of tridiagonal matrices and the theory of O(Delta)E's, gives the book its distinctiveness and provides a sound basis for a deep understanding of fundamental concepts in computational fluid dynamics.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers

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

Poole, E.L.

1986-01-01

This research is concerned with the solution on vector computers of linear systems of equations. Ax = b, where A is a large, sparse symmetric positive definite matrix with non-zero elements lying only along a few diagonals of the matrix. The system is solved using the incomplete Cholesky conjugate gradient method (ICCG). Multi-color orderings are used of the unknowns in the linear system to obtain p-color matrices for which a no-fill block ICCG method is implemented on the CYBER 205 with O(N/p) length vector operations in both the decomposition of A and, more importantly, in the forward and back solvesmore » necessary at each iteration of the method. (N is the number of unknowns and p is a small constant). A p-colored matrix is a matrix that can be partitioned into a p x p block matrix where the diagonal blocks are diagonal matrices. The matrix is stored by diagonals and matrix multiplication by diagonals is used to carry out the decomposition of A and the forward and back solves. Additionally, if the vectors across adjacent blocks line up, then some of the overhead associated with vector startups can be eliminated in the matrix vector multiplication necessary at each conjugate gradient iteration. Necessary and sufficient conditions are given to determine which multi-color orderings of the unknowns correspond to p-color matrices, and a process is indicated for choosing multi-color orderings.« less

Implementation of a fully-balanced periodic tridiagonal solver on a parallel distributed memory architecture

NASA Technical Reports Server (NTRS)

Eidson, T. M.; Erlebacher, G.

1994-01-01

While parallel computers offer significant computational performance, it is generally necessary to evaluate several programming strategies. Two programming strategies for a fairly common problem - a periodic tridiagonal solver - are developed and evaluated. Simple model calculations as well as timing results are presented to evaluate the various strategies. The particular tridiagonal solver evaluated is used in many computational fluid dynamic simulation codes. The feature that makes this algorithm unique is that these simulation codes usually require simultaneous solutions for multiple right-hand-sides (RHS) of the system of equations. Each RHS solutions is independent and thus can be computed in parallel. Thus a Gaussian elimination type algorithm can be used in a parallel computation and the more complicated approaches such as cyclic reduction are not required. The two strategies are a transpose strategy and a distributed solver strategy. For the transpose strategy, the data is moved so that a subset of all the RHS problems is solved on each of the several processors. This usually requires significant data movement between processor memories across a network. The second strategy attempts to have the algorithm allow the data across processor boundaries in a chained manner. This usually requires significantly less data movement. An approach to accomplish this second strategy in a near-perfect load-balanced manner is developed. In addition, an algorithm will be shown to directly transform a sequential Gaussian elimination type algorithm into the parallel chained, load-balanced algorithm.

Encoders for block-circulant LDPC codes

NASA Technical Reports Server (NTRS)

Andrews, Kenneth; Dolinar, Sam; Thorpe, Jeremy

2005-01-01

In this paper, we present two encoding methods for block-circulant LDPC codes. The first is an iterative encoding method based on the erasure decoding algorithm, and the computations required are well organized due to the block-circulant structure of the parity check matrix. The second method uses block-circulant generator matrices, and the encoders are very similar to those for recursive convolutional codes. Some encoders of the second type have been implemented in a small Field Programmable Gate Array (FPGA) and operate at 100 Msymbols/second.

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

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

Kim, Kyungjoo; Rajamanickam, Sivasankaran; Stelle, George Widgery

We introduce a task-parallel algorithm for sparse incomplete Cholesky factorization that utilizes a 2D sparse partitioned-block layout of a matrix. Our factorization algorithm follows the idea of algorithms-by-blocks by using the block layout. The algorithm-byblocks approach induces a task graph for the factorization. These tasks are inter-related to each other through their data dependences in the factorization algorithm. To process the tasks on various manycore architectures in a portable manner, we also present a portable tasking API that incorporates different tasking backends and device-specific features using an open-source framework for manycore platforms i.e., Kokkos. A performance evaluation is presented onmore » both Intel Sandybridge and Xeon Phi platforms for matrices from the University of Florida sparse matrix collection to illustrate merits of the proposed task-based factorization. Experimental results demonstrate that our task-parallel implementation delivers about 26.6x speedup (geometric mean) over single-threaded incomplete Choleskyby- blocks and 19.2x speedup over serial Cholesky performance which does not carry tasking overhead using 56 threads on the Intel Xeon Phi processor for sparse matrices arising from various application problems.« less

Selective deposition and self-assembly of triblock copolymers into matrix arrays for membrane protein production.

PubMed

Andreasson-Ochsner, Mirjam; Fu, Zhikang; May, Sylvia; Xiu, Low Ying; Nallani, Madhavan; Sinner, Eva-Kathrin

2012-01-31

To improve the stability of cell membrane mimics, there has been growing interest in the use of block copolymers. Here, we present an easy approach to create an array of planar polymeric matrices capable of hosting membrane proteins. The array of polymeric matrices was formed by the selective deposition of triblock copolymers onto an array of hydrophilic islands situated within a hydrophobic background. The thickness of these matrices corresponds to the length of a single polymer chain. These polymeric matrices were used to host cell-free expressed membrane proteins, and offers a prototype from which a membrane protein array can be created for diagnostics or drug discovery purposes. © 2011 American Chemical Society

Reflection matrices with U q [osp(2) (2|2m)] symmetry

NASA Astrophysics Data System (ADS)

Vieira, R. S.; Lima-Santos, A.

2017-09-01

We propose a classification of the reflection K-matrices (solutions of the boundary Yang-Baxter equation) for the Uq[osp(2)(2\\vert 2m)]=Uq[C(2)(m+1)] vertex-model. We found four families of solutions, namely, the complete solutions, in which no elements of the reflection K-matrix is null, the block-diagonal solutions, the X-shape solutions and the diagonal solutions. We highlight that these diagonal K-matrices also hold for the Uq[osp(2)(2n+2\\vert 2m)]=Uq[D(2)(n+1, m)] vertex-model.

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

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

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

DOE PAGES

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter; ...

2016-06-30

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

Local entanglement entropy of fermions as a marker of quantum phase transition in the one-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Cha, Min-Chul; Chung, Myung-Hoon

2018-05-01

We study quantum phase transition of interacting fermions by measuring the local entanglement entropy in the one-dimensional Hubbard model. The reduced density matrices for blocks of a few sites are constructed from the ground state wave function in infinite systems by adopting the matrix product state representation where time-evolving block decimations are performed to obtain the lowest energy states. The local entanglement entropy, constructed from the reduced density matrices, as a function of the chemical potential shows clear signatures of the Mott transition. The value of the central charge, numerically determined from the universal properties of the local entanglement entropy, confirms that the transition is caused by the suppression of the charge degrees of freedom.

Convergence to Diagonal Form of Block Jacobi-type Processes

NASA Astrophysics Data System (ADS)

Hari, Vjeran

2008-09-01

The main result of recent research on convergence to diagonal form of block Jacobi-type processes is presented. For this purpose, all notions needed to describe the result are introduced. In particular, elementary block transformation matrices, simple and non-simple algorithms, block pivot strategies together with the appropriate equivalence relations are defined. The general block Jacobi-type process considered here can be specialized to take the form of almost any known Jacobi-type method for solving the ordinary or the generalized matrix eigenvalue and singular value problems. The assumptions used in the result are satisfied by many concrete methods.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Poole, E. L.

1986-01-01

In this research, we are concerned with the solution on vector computers of linear systems of equations, Ax = b, where A is a larger, sparse symmetric positive definite matrix. We solve the system using an iterative method, the incomplete Cholesky conjugate gradient method (ICCG). We apply a multi-color strategy to obtain p-color matrices for which a block-oriented ICCG method is implemented on the CYBER 205. (A p-colored matrix is a matrix which can be partitioned into a pXp block matrix where the diagonal blocks are diagonal matrices). This algorithm, which is based on a no-fill strategy, achieves O(N/p) length vector operations in both the decomposition of A and in the forward and back solves necessary at each iteration of the method. We discuss the natural ordering of the unknowns as an ordering that minimizes the number of diagonals in the matrix and define multi-color orderings in terms of disjoint sets of the unknowns. We give necessary and sufficient conditions to determine which multi-color orderings of the unknowns correpond to p-color matrices. A performance model is given which is used both to predict execution time for ICCG methods and also to compare an ICCG method to conjugate gradient without preconditioning or another ICCG method. Results are given from runs on the CYBER 205 at NASA's Langley Research Center for four model problems.

Empirical Bayes method for reducing false discovery rates of correlation matrices with block diagonal structure.

PubMed

Pacini, Clare; Ajioka, James W; Micklem, Gos

2017-04-12

Correlation matrices are important in inferring relationships and networks between regulatory or signalling elements in biological systems. With currently available technology sample sizes for experiments are typically small, meaning that these correlations can be difficult to estimate. At a genome-wide scale estimation of correlation matrices can also be computationally demanding. We develop an empirical Bayes approach to improve covariance estimates for gene expression, where we assume the covariance matrix takes a block diagonal form. Our method shows lower false discovery rates than existing methods on simulated data. Applied to a real data set from Bacillus subtilis we demonstrate it's ability to detecting known regulatory units and interactions between them. We demonstrate that, compared to existing methods, our method is able to find significant covariances and also to control false discovery rates, even when the sample size is small (n=10). The method can be used to find potential regulatory networks, and it may also be used as a pre-processing step for methods that calculate, for example, partial correlations, so enabling the inference of the causal and hierarchical structure of the networks.

The Twist Tensor Nuclear Norm for Video Completion.

PubMed

Hu, Wenrui; Tao, Dacheng; Zhang, Wensheng; Xie, Yuan; Yang, Yehui

2017-12-01

In this paper, we propose a new low-rank tensor model based on the circulant algebra, namely, twist tensor nuclear norm (t-TNN). The twist tensor denotes a three-way tensor representation to laterally store 2-D data slices in order. On one hand, t-TNN convexly relaxes the tensor multirank of the twist tensor in the Fourier domain, which allows an efficient computation using fast Fourier transform. On the other, t-TNN is equal to the nuclear norm of block circulant matricization of the twist tensor in the original domain, which extends the traditional matrix nuclear norm in a block circulant way. We test the t-TNN model on a video completion application that aims to fill missing values and the experiment results validate its effectiveness, especially when dealing with video recorded by a nonstationary panning camera. The block circulant matricization of the twist tensor can be transformed into a circulant block representation with nuclear norm invariance. This representation, after transformation, exploits the horizontal translation relationship between the frames in a video, and endows the t-TNN model with a more powerful ability to reconstruct panning videos than the existing state-of-the-art low-rank models.

The thermal stability of photoacid generators in phenolic matrices

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

Barclay, G.G.; Medeiros, D.R.; Sinta, R.F.

1993-12-31

The thermal stability of various photolabile sulfonate esters in phenolic matrices have been investigated by differential scanning calorimetry and thermogravimetric analysis. It was observed that the thermal stability of these photoacid generators is lowered in the presence of phenolic groups. As a result acid can be thermally generated, thereby reducing the selectivity of photoacid generation. The sulfonate esters investigated in phenolic matrices included nitrobenzyl tosylates, imino sulfonates, benzoin tosylate and 1,2,3-tris(methanesulfonyloxy)benzene. Also the effect of the thermal generation of acid from these photoacid generators on the temperature and rate of deprotection of partially t-butoxycarbonate blocked poly (vinylphenol) was studied bymore » thermogravimetric analysis and FTIR.« less

Parallel block schemes for large scale least squares computations

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

Golub, G.H.; Plemmons, R.J.; Sameh, A.

1986-04-01

Large scale least squares computations arise in a variety of scientific and engineering problems, including geodetic adjustments and surveys, medical image analysis, molecular structures, partial differential equations and substructuring methods in structural engineering. In each of these problems, matrices often arise which possess a block structure which reflects the local connection nature of the underlying physical problem. For example, such super-large nonlinear least squares computations arise in geodesy. Here the coordinates of positions are calculated by iteratively solving overdetermined systems of nonlinear equations by the Gauss-Newton method. The US National Geodetic Survey will complete this year (1986) the readjustment ofmore » the North American Datum, a problem which involves over 540 thousand unknowns and over 6.5 million observations (equations). The observation matrix for these least squares computations has a block angular form with 161 diagnonal blocks, each containing 3 to 4 thousand unknowns. In this paper parallel schemes are suggested for the orthogonal factorization of matrices in block angular form and for the associated backsubstitution phase of the least squares computations. In addition, a parallel scheme for the calculation of certain elements of the covariance matrix for such problems is described. It is shown that these algorithms are ideally suited for multiprocessors with three levels of parallelism such as the Cedar system at the University of Illinois. 20 refs., 7 figs.« less

M-matrices with prescribed elementary divisors

NASA Astrophysics Data System (ADS)

Soto, Ricardo L.; Díaz, Roberto C.; Salas, Mario; Rojo, Oscar

2017-09-01

A real matrix A is said to be an M-matrix if it is of the form A=α I-B, where B is a nonnegative matrix with Perron eigenvalue ρ (B), and α ≥slant ρ (B) . This paper provides sufficient conditions for the existence and construction of an M-matrix A with prescribed elementary divisors, which are the characteristic polynomials of the Jordan blocks of the Jordan canonical form of A. This inverse problem on M-matrices has not been treated until now. We solve the inverse elementary divisors problem for diagonalizable M-matrices and the symmetric generalized doubly stochastic inverse M-matrix problem for lists of real numbers and for lists of complex numbers of the form Λ =\\{λ 1, a+/- bi, \\ldots, a+/- bi\\} . The constructive nature of our results allows for the computation of a solution matrix. The paper also discusses an application of M-matrices to a capacity problem in wireless communications.

An Implicit LU/AF FDTD Method

NASA Technical Reports Server (NTRS)

Beggs, John H.; Briley, W. Roger

2001-01-01

There has been some recent work to develop two and three-dimensional alternating direction implicit (ADI) FDTD schemes. These ADI schemes are based upon the original ADI concept developed by Peaceman and Rachford and Douglas and Gunn, which is a popular solution method in Computational Fluid Dynamics (CFD). These ADI schemes work well and they require solution of a tridiagonal system of equations. A new approach proposed in this paper applies a LU/AF approximate factorization technique from CFD to Maxwell s equations in flux conservative form for one space dimension. The result is a scheme that will retain its unconditional stability in three space dimensions, but does not require the solution of tridiagonal systems. The theory for this new algorithm is outlined in a one-dimensional context for clarity. An extension to two and threedimensional cases is discussed. Results of Fourier analysis are discussed for both stability and dispersion/damping properties of the algorithm. Results are presented for a one-dimensional model problem, and the explicit FDTD algorithm is chosen as a convenient reference for comparison.

Fast modal extraction in NASTRAN via the FEER computer program. [based on automatic matrix reduction method for lower modes of structures with many degrees of freedom

NASA Technical Reports Server (NTRS)

Newman, M. B.; Pipano, A.

1973-01-01

A new eigensolution routine, FEER (Fast Eigensolution Extraction Routine), used in conjunction with NASTRAN at Israel Aircraft Industries is described. The FEER program is based on an automatic matrix reduction scheme whereby the lower modes of structures with many degrees of freedom can be accurately extracted from a tridiagonal eigenvalue problem whose size is of the same order of magnitude as the number of required modes. The process is effected without arbitrary lumping of masses at selected node points or selection of nodes to be retained in the analysis set. The results of computational efficiency studies are presented, showing major arithmetic operation counts and actual computer run times of FEER as compared to other methods of eigenvalue extraction, including those available in the NASTRAN READ module. It is concluded that the tridiagonal reduction method used in FEER would serve as a valuable addition to NASTRAN for highly increased efficiency in obtaining structural vibration modes.

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

PubMed

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

2012-12-01

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

Exact solution of corner-modified banded block-Toeplitz eigensystems

NASA Astrophysics Data System (ADS)

Cobanera, Emilio; Alase, Abhijeet; Ortiz, Gerardo; Viola, Lorenza

2017-05-01

Motivated by the challenge of seeking a rigorous foundation for the bulk-boundary correspondence for free fermions, we introduce an algorithm for determining exactly the spectrum and a generalized-eigenvector basis of a class of banded block quasi-Toeplitz matrices that we call corner-modified. Corner modifications of otherwise arbitrary banded block-Toeplitz matrices capture the effect of boundary conditions and the associated breakdown of translational invariance. Our algorithm leverages the interplay between a non-standard, projector-based method of kernel determination (physically, a bulk-boundary separation) and families of linear representations of the algebra of matrix Laurent polynomials. Thanks to the fact that these representations act on infinite-dimensional carrier spaces in which translation symmetry is restored, it becomes possible to determine the eigensystem of an auxiliary projected block-Laurent matrix. This results in an analytic eigenvector Ansatz, independent of the system size, which we prove is guaranteed to contain the full solution of the original finite-dimensional problem. The actual solution is then obtained by imposing compatibility with a boundary matrix, whose shape is also independent of system size. As an application, we show analytically that eigenvectors of short-ranged fermionic tight-binding models may display power-law corrections to exponential behavior, and demonstrate the phenomenon for the paradigmatic Majorana chain of Kitaev.

Malware analysis using visualized image matrices.

PubMed

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

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

Ghysels, Pieter; Li, Xiaoye S.; Rouet, Francois -Henry

Here, we present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which have low-rank off-diagonal blocks, to approximate the frontal matrices. For HSS matrix construction, a randomized sampling algorithm is used together with interpolative decompositions. The combination of the randomized compression with a fast ULV HSS factoriz ation leads to a solver with lower computational complexity than the standard multifrontal method for many applications, resulting in speedups up to 7 fold for problems in our test suite.more » The implementation targets many-core systems by using task parallelism with dynamic runtime scheduling. Numerical experiments show performance improvements over state-of-the-art sparse direct solvers. The implementation achieves high performance and good scalability on a range of modern shared memory parallel systems, including the Intel Xeon Phi (MIC). The code is part of a software package called STRUMPACK - STRUctured Matrices PACKage, which also has a distributed memory component for dense rank-structured matrices.« less

An Efficient Multicore Implementation of a Novel HSS-Structured Multifrontal Solver Using Randomized Sampling

DOE PAGES

Ghysels, Pieter; Li, Xiaoye S.; Rouet, Francois -Henry; ...

2016-10-27

Here, we present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which have low-rank off-diagonal blocks, to approximate the frontal matrices. For HSS matrix construction, a randomized sampling algorithm is used together with interpolative decompositions. The combination of the randomized compression with a fast ULV HSS factoriz ation leads to a solver with lower computational complexity than the standard multifrontal method for many applications, resulting in speedups up to 7 fold for problems in our test suite.more » The implementation targets many-core systems by using task parallelism with dynamic runtime scheduling. Numerical experiments show performance improvements over state-of-the-art sparse direct solvers. The implementation achieves high performance and good scalability on a range of modern shared memory parallel systems, including the Intel Xeon Phi (MIC). The code is part of a software package called STRUMPACK - STRUctured Matrices PACKage, which also has a distributed memory component for dense rank-structured matrices.« less

Green-noise halftoning with dot diffusion

NASA Astrophysics Data System (ADS)

Lippens, Stefaan; Philips, Wilfried

2007-02-01

Dot diffusion is a halftoning technique that is based on the traditional error diffusion concept, but offers a high degree of parallel processing by its block based approach. Traditional dot diffusion however suffers from periodicity artifacts. To limit the visibility of these artifacts, we propose grid diffusion, which applies different class matrices for different blocks. Furthermore, in this paper we will discuss two approaches in the dot diffusion framework to generate green-noise halftone patterns. The first approach is based on output dependent feedback (hysteresis), analogous to the standard green-noise error diffusion techniques. We observe that the resulting halftones are rather coarse and highly dependent on the used dot diffusion class matrices. In the second approach we don't limit the diffusion to the nearest neighbors. This leads to less coarse halftones, compared to the first approach. The drawback is that it can only cope with rather limited cluster sizes. We can reduce these drawbacks by combining the two approaches.

Reduced order feedback control equations for linear time and frequency domain analysis

NASA Technical Reports Server (NTRS)

Frisch, H. P.

1981-01-01

An algorithm was developed which can be used to obtain the equations. In a more general context, the algorithm computes a real nonsingular similarity transformation matrix which reduces a real nonsymmetric matrix to block diagonal form, each block of which is a real quasi upper triangular matrix. The algorithm works with both defective and derogatory matrices and when and if it fails, the resultant output can be used as a guide for the reformulation of the mathematical equations that lead up to the ill conditioned matrix which could not be block diagonalized.

Power/Performance Trade-offs of Small Batched LU Based Solvers on GPUs

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

Villa, Oreste; Fatica, Massimiliano; Gawande, Nitin A.

In this paper we propose and analyze a set of batched linear solvers for small matrices on Graphic Processing Units (GPUs), evaluating the various alternatives depending on the size of the systems to solve. We discuss three different solutions that operate with different level of parallelization and GPU features. The first, exploiting the CUBLAS library, manages matrices of size up to 32x32 and employs Warp level (one matrix, one Warp) parallelism and shared memory. The second works at Thread-block level parallelism (one matrix, one Thread-block), still exploiting shared memory but managing matrices up to 76x76. The third is Thread levelmore » parallel (one matrix, one thread) and can reach sizes up to 128x128, but it does not exploit shared memory and only relies on the high memory bandwidth of the GPU. The first and second solution only support partial pivoting, the third one easily supports partial and full pivoting, making it attractive to problems that require greater numerical stability. We analyze the trade-offs in terms of performance and power consumption as function of the size of the linear systems that are simultaneously solved. We execute the three implementations on a Tesla M2090 (Fermi) and on a Tesla K20 (Kepler).« less

Strategy for good dispersion of well-defined tetrapods in semiconducting polymer matrices.

PubMed

Lim, Jaehoon; Borg, Lisa zur; Dolezel, Stefan; Schmid, Friederike; Char, Kookheon; Zentel, Rudolf

2014-10-01

The morphology or dispersion control in inorganic/organic hybrid systems is studied, which consist of monodisperse CdSe tetrapods (TPs) with grafted semiconducting block copolymers with excess polymers of the same type. Tetrapod arm-length and amount of polymer loading are varied in order to find the ideal morphology for hybrid solar cells. Additionally, polymers without anchor groups are mixed with the TPs to study the effect of such anchor groups on the hybrid morphology. A numerical model is developed and Monte Carlo simulations to study the basis of compatibility or dispersibility of TPs in polymer matrices are performed. The simulations show that bare TPs tend to form clusters in the matrix of excess polymers. The clustering is significantly reduced after grafting polymer chains to the TPs, which is confirmed experimentally. Transmission electron microscopy reveals that the block copolymer-TP mixtures ("hybrids") show much better film qualities and TP distributions within the films when compared with the homopolymer-TP mixtures ("blends"), representing massive aggregations and cracks in the films. This grafting-to approach for the modification of TPs significantly improves the dispersion of the TPs in matrices of "excess" polymers up to the arm length of 100 nm. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decoherence at constant excitation

NASA Astrophysics Data System (ADS)

Torres, J. M.; Sadurní, E.; Seligman, T. H.

2012-02-01

We present a simple exactly solvable extension of the Jaynes-Cummings model by adding dissipation. This is done such that the total number of excitations is conserved. The Liouville operator in the resulting master equation can be reduced to blocks of 4×4 matrices.

Synthetic Division and Matrix Factorization

ERIC Educational Resources Information Center

Barabe, Samuel; Dubeau, Franc

2007-01-01

Synthetic division is viewed as a change of basis for polynomials written under the Newton form. Then, the transition matrices obtained from a sequence of changes of basis are used to factorize the inverse of a bidiagonal matrix or a block bidiagonal matrix.

Thermal transport in dimerized harmonic lattices: Exact solution, crossover behavior, and extended reservoirs

NASA Astrophysics Data System (ADS)

Chien, Chih-Chun; Kouachi, Said; Velizhanin, Kirill A.; Dubi, Yonatan; Zwolak, Michael

2017-01-01

We present a method for calculating analytically the thermal conductance of a classical harmonic lattice with both alternating masses and nearest-neighbor couplings when placed between individual Langevin reservoirs at different temperatures. The method utilizes recent advances in analytic diagonalization techniques for certain classes of tridiagonal matrices. It recovers the results from a previous method that was applicable for alternating on-site parameters only, and extends the applicability to realistic systems in which masses and couplings alternate simultaneously. With this analytic result in hand, we show that the thermal conductance is highly sensitive to the modulation of the couplings. This is due to the existence of topologically induced edge modes at the lattice-reservoir interface and is also a reflection of the symmetries of the lattice. We make a connection to a recent work that demonstrates thermal transport is analogous to chemical reaction rates in solution given by Kramers' theory [Velizhanin et al., Sci. Rep. 5, 17506 (2015)], 10.1038/srep17506. In particular, we show that the turnover behavior in the presence of edge modes prevents calculations based on single-site reservoirs from coming close to the natural—or intrinsic—conductance of the lattice. Obtaining the correct value of the intrinsic conductance through simulation of even a small lattice where ballistic effects are important requires quite large extended reservoir regions. Our results thus offer a route for both the design and proper simulation of thermal conductance of nanoscale devices.

A Shifted Block Lanczos Algorithm 1: The Block Recurrence

NASA Technical Reports Server (NTRS)

Grimes, Roger G.; Lewis, John G.; Simon, Horst D.

1990-01-01

In this paper we describe a block Lanczos algorithm that is used as the key building block of a software package for the extraction of eigenvalues and eigenvectors of large sparse symmetric generalized eigenproblems. The software package comprises: a version of the block Lanczos algorithm specialized for spectrally transformed eigenproblems; an adaptive strategy for choosing shifts, and efficient codes for factoring large sparse symmetric indefinite matrices. This paper describes the algorithmic details of our block Lanczos recurrence. This uses a novel combination of block generalizations of several features that have only been investigated independently in the past. In particular new forms of partial reorthogonalization, selective reorthogonalization and local reorthogonalization are used, as is a new algorithm for obtaining the M-orthogonal factorization of a matrix. The heuristic shifting strategy, the integration with sparse linear equation solvers and numerical experience with the code are described in a companion paper.

A parallel algorithm for computing the eigenvalues of a symmetric tridiagonal matrix

NASA Technical Reports Server (NTRS)

Swarztrauber, Paul N.

1993-01-01

A parallel algorithm, called polysection, is presented for computing the eigenvalues of a symmetric tridiagonal matrix. The method is based on a quadratic recurrence in which the characteristic polynomial is constructed on a binary tree from polynomials whose degree doubles at each level. Intervals that contain exactly one zero are determined by the zeros of polynomials at the previous level which ensures that different processors compute different zeros. The signs of the polynomials at the interval endpoints are determined a priori and used to guarantee that all zeros are found. The use of finite-precision arithmetic may result in multiple zeros; however, in this case, the intervals coalesce and their number determines exactly the multiplicity of the zero. For an N x N matrix the eigenvalues can be determined in O(log-squared N) time with N-squared processors and O(N) time with N processors. The method is compared with a parallel variant of bisection that requires O(N-squared) time on a single processor, O(N) time with N processors, and O(log N) time with N-squared processors.

Construction of a thermoresponsive magnetic porous polymer membrane enzyme reactor for glutaminase kinetics study.

PubMed

Zhao, Liping; Qiao, Juan; Moon, Meyong Hee; Qi, Li

2018-06-16

Fabrication of polymer membranes with nanopores and a confinement effect toward enzyme immobilization has been an enabling endeavor. In the work reported here, an enzyme reactor based on a thermoresponsive magnetic porous block copolymer membrane was designed and constructed. Reversible addition-fragmentation chain transfer polymerization was used to synthesize the block copolymer, poly(maleic anhydride-styrene-N-isopropylacrylamide), with poly(N-isopropylacrylamide) as the thermoresponsive moiety. The self-assembly property of the block copolymer was used for preparation of magnetic porous thin film matrices with iron oxide nanoparticles. By covalent bonding of glutaminase onto the surface of the membrane matrices and changing the temperature to tune the nanopore size, we observed enhanced enzymolysis efficiency due to the confinement effect. The apparent Michaelis-Menten constant and the maximum rate of the enzyme reactor were determined (K m = 32.3 mM, V max = 33.3 mM min -1 ) by a chiral ligand exchange capillary electrochromatography protocol with L-glutamine as the substrate. Compared with free glutaminase in solution, the proposed enzyme reactor exhibits higher enzymolysis efficiency, greater stability, and greater reusability. Furthermore, the enzyme reactor was applied for a glutaminase kinetics study. The tailored pore sizes and the thermoresponsive property of the block copolymer result in the designed porous membrane based enzyme reactor having great potential for high enzymolysis performance. Graphical abstract ᅟ.

Malware Analysis Using Visualized Image Matrices

PubMed Central

Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

Visualizing Matrix Multiplication

ERIC Educational Resources Information Center

Daugulis, Peteris; Sondore, Anita

2018-01-01

Efficient visualizations of computational algorithms are important tools for students, educators, and researchers. In this article, we point out an innovative visualization technique for matrix multiplication. This method differs from the standard, formal approach by using block matrices to make computations more visual. We find this method a…

Analysis of the Pre-stack Split-Step Migration Operator Using Ritz Values

NASA Astrophysics Data System (ADS)

Kaplan, S. T.; Sacchi, M. D.

2009-05-01

The Born approximation for the acoustic wave-field is often used as a basis for developing algorithms in seismic imaging (migration). The approximation is linear, and, as such, can be written as a matrix-vector multiplication (Am=d). In the seismic imaging problem, d is seismic data (the recorded wave-field), and we aim to find the seismic reflectivity m (a representation of earth structure and properties) so that Am=d is satisfied. This is the often studied inverse problem of seismic migration, where given A and d, we solve for m. This can be done in a least-squares sense, so that the equation of interest is, AHAm = AHd. Hence, the solution m is largely dependent on the properties of AHA. The imaging Jacobian J provides an approximation to AHA, so that J-1AHA is, in a broad sense, better behaved then AHA. We attempt to quantify this last statement by providing an analysis of AHA and J-1AHA using their Ritz values, and for the particular case where A is built using a pre-stack split-step migration algorithm. Typically, one might try to analyze the behaviour of these matrices using their eigenvalue spectra. The difficulty in the analysis of AHA and J-1AHA lie in their size. For example, a subset of the relatively small Marmousi data set makes AHA a complex valued matrix with, roughly, dimensions of 45 million by 45 million (requiring, in single-precision, about 16 Peta-bytes of computer memory). In short, the size of the matrix makes its eigenvalues difficult to compute. Instead, we compute the leading principal minors of similar tridiagonal matrices, Bk=Vk-1AHAVk and Ck = Uk-1 J-1 AHAUk. These can be constructed using, for example, the Lanczos decomposition. Up to some value of k it is feasible to compute the eigenvalues of Bk and Ck which, in turn, are the Ritz values of, respectively, AHA and J-1 AHA, and may allow us to make quantitative statements about their behaviours.

Scaling Optimization of the SIESTA MHD Code

NASA Astrophysics Data System (ADS)

Seal, Sudip; Hirshman, Steven; Perumalla, Kalyan

2013-10-01

SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands at high spatial resolutions for toroidal plasmas. Originally designed to exploit small-scale parallelism, SIESTA has now been scaled to execute efficiently over several thousands of processors P. This scaling improvement was accomplished with minimal intrusion to the execution flow of the original version. First, the efficiency of the iterative solutions was improved by integrating the parallel tridiagonal block solver code BCYCLIC. Krylov-space generation in GMRES was then accelerated using a customized parallel matrix-vector multiplication algorithm. Novel parallel Hessian generation algorithms were integrated and memory access latencies were dramatically reduced through loop nest optimizations and data layout rearrangement. These optimizations sped up equilibria calculations by factors of 30-50. It is possible to compute solutions with granularity N/P near unity on extremely fine radial meshes (N > 1024 points). Grid separation in SIESTA, which manifests itself primarily in the resonant components of the pressure far from rational surfaces, is strongly suppressed by finer meshes. Large problem sizes of up to 300 K simultaneous non-linear coupled equations have been solved on the NERSC supercomputers. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.

Application of Financial Risk-reward Theory to Link and Network Optimization

DTIC Science & Technology

2011-10-01

OFDM systems the matrices V k and U k are Fourier matrices which diagonalize a circulant or block-circulant matrix Hk [18]. In multi-antenna systems...probability α=Pr(η r <=t) Figure 13: Mean link spectral efficiency as a function of target link spectral efficiency ηt and outage probability ζ in a MIMO ...in a MIMO channel. Distribution A: Approved for public release; distribution is unlimited. 41 (75) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 6 8

Computer Control and Activation of Six-Degree-of-Freedom Simulator

DTIC Science & Technology

1983-01-01

Evaluation of Matrices 54 Calculation of Linear Coefficients 54 Off-Line Calculations for Aircraft 59 Off-Line Calculations for Combat Vehicle 61 Table...468 in. 59 Physical concept tail-boom control system 203 Vlll 60 Tail-boom control system block diagram 204 61 Block diagram for position...configuration. Now, since Z must be diagonal, it follows that the principal elements of Z are given by 13 where and a) = ^11 ^12’ 2 2 ^21 ^22 ’ 61

USEEIO v1.1-Matrices

EPA Science Inventory

This dataset provides the basic building blocks for the USEEIO v1.1 model and life cycle results per $1 (2013 USD) demand for all goods and services in the model in the producer's price (see BEA 2015). The methodology underlying USEEIO is described in Yang, Ingwersen et al., 2017...

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

PubMed

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

A FORTRAN program for the analysis of linear continuous and sample-data systems

NASA Technical Reports Server (NTRS)

Edwards, J. W.

1976-01-01

A FORTRAN digital computer program which performs the general analysis of linearized control systems is described. State variable techniques are used to analyze continuous, discrete, and sampled data systems. Analysis options include the calculation of system eigenvalues, transfer functions, root loci, root contours, frequency responses, power spectra, and transient responses for open- and closed-loop systems. A flexible data input format allows the user to define systems in a variety of representations. Data may be entered by inputing explicit data matrices or matrices constructed in user written subroutines, by specifying transfer function block diagrams, or by using a combination of these methods.

Efficient quantum circuits for dense circulant and circulant like operators

PubMed Central

Zhou, S. S.

2017-01-01

Circulant matrices are an important family of operators, which have a wide range of applications in science and engineering-related fields. They are, in general, non-sparse and non-unitary. In this paper, we present efficient quantum circuits to implement circulant operators using fewer resources and with lower complexity than existing methods. Moreover, our quantum circuits can be readily extended to the implementation of Toeplitz, Hankel and block circulant matrices. Efficient quantum algorithms to implement the inverses and products of circulant operators are also provided, and an example application in solving the equation of motion for cyclic systems is discussed. PMID:28572988

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

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

Samuel Dyer and His Contributions to Chinese Typography.

ERIC Educational Resources Information Center

Ismail, Ibrahim bin

1984-01-01

This history of a London Missionary Society member's contributions to typography development in China highlights selection of 3,000 Chinese characters needed for purpose of printing Christian books, production of temporary font from wooden blocks, and use of European methods of punches and matrices to produce permanent metal font. (Twenty-seven…

Parallel conjugate gradient algorithms for manipulator dynamic simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheld, Robert E.

1989-01-01

Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).

Engineering of M13 Bacteriophage for Development of Tissue Engineering Materials.

PubMed

Jin, Hyo-Eon; Lee, Seung-Wuk

2018-01-01

M13 bacteriophages have several qualities that make them attractive candidates as building blocks for tissue regenerating scaffold materials. Through genetic engineering, a high density of functional peptides and proteins can be simultaneously displayed on the M13 bacteriophage's outer coat proteins. The resulting phage can self-assemble into nanofibrous network structures and can guide the tissue morphogenesis through proliferation, differentiation and apoptosis. In this manuscript, we will describe methods to develop major coat-engineered M13 phages as a basic building block and aligned tissue-like matrices to develop regenerative nanomaterials.

Soil heating and evaporation under extreme conditions: Forest fires and slash pile burns

NASA Astrophysics Data System (ADS)

Massman, W. J.

2011-12-01

Heating any soil during a sufficiently intense wild fire or prescribed burn can alter soil irreversibly, resulting in many significant and well known, long term biological, chemical, and hydrological effects. To better understand how fire impacts soil, especially considering the increasing probability of wildfires that is being driven by climate change and the increasing use of prescribe burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improving understanding of heat and mass transport during such extreme conditions should also provide insights into the associated transport mechanisms under more normal conditions as well. Here I describe the development of a new model designed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 Wm-2 for several minutes to several hours. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events created with an extremely intense radiant heater. The laboratory tests employed well described soils with well known physical properties. The model, on the other hand, is somewhat unusual in that it employs formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve (relation between soil moisture and soil moisture potential). It also employs a new formulation for the surface evaporation rate as a component of the upper boundary condition, as well as the Newton-Raphson method and the generalized Thomas algorithm for inverting block tri-diagonal matrices to solve for soil temperature and soil moisture potential. Model results show rapid evaporation rates with significant vapor transfer not only to the free atmosphere above the soil, but to lower depths of the soil, where the vapor re-condenses ahead of the heating front. Consequently the trajectory of the solution (soil volumetric water content versus soil temperature) is very unusual and highly nonlinear, which may explain why more traditional methods (i.e., those based on finite difference or finite element approaches) tend to show more numerical instabilities than the Newton-Raphson method when used to model these extreme conditions. But, despite the intuitive and qualitative appeal of the model's numerical solution, it underestimates the rate of soil moisture loss observed during the laboratory trials, although the soil temperatures are reasonably well simulated.

Pseudomorphic InGaAs Materials

DTIC Science & Technology

1990-07-31

tive mass Schrodinger equation can be cast using a finite element technique (Galerkin residual method) into a symmetric tridiagonal matrix formulation...lnr’Gal-.’As composition. All of the structures were fabricated by molecular beam epitaxy (MBE). The effects of different growth conditions were evaluated... different growth conditions were evaluated with a combination of characterization techniques. Key results to emerge from this work relate to the

The crypto-Hermitian smeared-coordinate representation of wave functions

NASA Astrophysics Data System (ADS)

Znojil, Miloslav

2011-08-01

In discrete-coordinate quantum models the kinematical observable of position need not necessarily be chosen local (i.e., diagonal). Its smearing is selected in the nearest-neighbor form of a real asymmetric (i.e., crypto-Hermitian) tridiagonal matrix Qˆ. Via Gauss-Hermite illustrative example we show how such an option restricts the class of admissible dynamical observables (sampled here just by the Hamiltonian).

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.

Investigation of Elliptical Cooling Channels for a Naval Electromagnetic Railgun

DTIC Science & Technology

2005-05-09

Numerical Recipes in C : The Art of Scientific Computing, Second Edition. Cambridge: Cambridge University Press, 1992. Ramanujan , S. Ramanujan’s...by Midshipman 1/ c Elizabeth R. Kealey, Class of 2005 United States Naval Academy Annapolis, MD ___________________________________ (signature...system 55 10 Equation 46: Fourier number 55 Equation 47: General heat equation with coefficients a, b, c , and d 55 Equation 48: Tridiagonal matrix

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

DTIC Science & Technology

2012-03-22

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

Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.

PubMed

Fessler, J A; Booth, S D

1999-01-01

Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.

BIPAD: A web server for modeling bipartite sequence elements

PubMed Central

Bi, Chengpeng; Rogan, Peter K

2006-01-01

Background Many dimeric protein complexes bind cooperatively to families of bipartite nucleic acid sequence elements, which consist of pairs of conserved half-site sequences separated by intervening distances that vary among individual sites. Results We introduce the Bipad Server [1], a web interface to predict sequence elements embedded within unaligned sequences. Either a bipartite model, consisting of a pair of one-block position weight matrices (PWM's) with a gap distribution, or a single PWM matrix for contiguous single block motifs may be produced. The Bipad program performs multiple local alignment by entropy minimization and cyclic refinement using a stochastic greedy search strategy. The best models are refined by maximizing incremental information contents among a set of potential models with varying half site and gap lengths. Conclusion The web service generates information positional weight matrices, identifies binding site motifs, graphically represents the set of discovered elements as a sequence logo, and depicts the gap distribution as a histogram. Server performance was evaluated by generating a collection of bipartite models for distinct DNA binding proteins. PMID:16503993

Error Correction using Quantum Quasi-Cyclic Low-Density Parity-Check(LDPC) Codes

NASA Astrophysics Data System (ADS)

Jing, Lin; Brun, Todd; Quantum Research Team

Quasi-cyclic LDPC codes can approach the Shannon capacity and have efficient decoders. Manabu Hagiwara et al., 2007 presented a method to calculate parity check matrices with high girth. Two distinct, orthogonal matrices Hc and Hd are used. Using submatrices obtained from Hc and Hd by deleting rows, we can alter the code rate. The submatrix of Hc is used to correct Pauli X errors, and the submatrix of Hd to correct Pauli Z errors. We simulated this system for depolarizing noise on USC's High Performance Computing Cluster, and obtained the block error rate (BER) as a function of the error weight and code rate. From the rates of uncorrectable errors under different error weights we can extrapolate the BER to any small error probability. Our results show that this code family can perform reasonably well even at high code rates, thus considerably reducing the overhead compared to concatenated and surface codes. This makes these codes promising as storage blocks in fault-tolerant quantum computation. Error Correction using Quantum Quasi-Cyclic Low-Density Parity-Check(LDPC) Codes.

Effective Mass of a Single π0 Interacting With Itself

NASA Astrophysics Data System (ADS)

Eldridge, J. M.; Orginos, K.

2014-09-01

The effective mass of a single π0 π on when interacting with itself has been calculated. The calculation was done using C++ and It++, a C++ library extension which attempts to emulate MATLAB. This calculation was done by generating a matrix G from a database, and two meson state matrices M0, and M1. G, M0, and M1 are each 1584 × 1584 , however, careful algebra, knowing the properties of these matrices, enables only the top left 792 × 792 block of each to be created, saving computation time and reducing numerical error. The π0 self-interacting-effective-mass has been calculated to be 0.0755(190).

Hypoxic stellate cells of pancreatic cancer stroma regulate extracellular matrix fiber organization and cancer cell motility.

PubMed

Sada, Masafumi; Ohuchida, Kenoki; Horioka, Kohei; Okumura, Takashi; Moriyama, Taiki; Miyasaka, Yoshihiro; Ohtsuka, Takao; Mizumoto, Kazuhiro; Oda, Yoshinao; Nakamura, Masafumi

2016-03-28

Desmoplasia and hypoxia in pancreatic cancer mutually affect each other and create a tumor-supportive microenvironment. Here, we show that microenvironment remodeling by hypoxic pancreatic stellate cells (PSCs) promotes cancer cell motility through alteration of extracellular matrix (ECM) fiber architecture. Three-dimensional (3-D) matrices derived from PSCs under hypoxia exhibited highly organized parallel-patterned matrix fibers compared with 3-D matrices derived from PSCs under normoxia, and promoted cancer cell motility by inducing directional migration of cancer cells due to the parallel fiber architecture. Microarray analysis revealed that procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 (PLOD2) in PSCs was the gene that potentially regulates ECM fiber architecture under hypoxia. Stromal PLOD2 expression in surgical specimens of pancreatic cancer was confirmed by immunohistochemistry. RNA interference-mediated knockdown of PLOD2 in PSCs blocked parallel fiber architecture of 3-D matrices, leading to decreased directional migration of cancer cells within the matrices. In conclusion, these findings indicate that hypoxia-induced PLOD2 expression in PSCs creates a permissive microenvironment for migration of cancer cells through architectural regulation of stromal ECM in pancreatic cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Biclustering sparse binary genomic data.

PubMed

van Uitert, Miranda; Meuleman, Wouter; Wessels, Lodewyk

2008-12-01

Genomic datasets often consist of large, binary, sparse data matrices. In such a dataset, one is often interested in finding contiguous blocks that (mostly) contain ones. This is a biclustering problem, and while many algorithms have been proposed to deal with gene expression data, only two algorithms have been proposed that specifically deal with binary matrices. None of the gene expression biclustering algorithms can handle the large number of zeros in sparse binary matrices. The two proposed binary algorithms failed to produce meaningful results. In this article, we present a new algorithm that is able to extract biclusters from sparse, binary datasets. A powerful feature is that biclusters with different numbers of rows and columns can be detected, varying from many rows to few columns and few rows to many columns. It allows the user to guide the search towards biclusters of specific dimensions. When applying our algorithm to an input matrix derived from TRANSFAC, we find transcription factors with distinctly dissimilar binding motifs, but a clear set of common targets that are significantly enriched for GO categories.

An efficient solver for large structured eigenvalue problems in relativistic quantum chemistry

NASA Astrophysics Data System (ADS)

Shiozaki, Toru

2017-01-01

We report an efficient program for computing the eigenvalues and symmetry-adapted eigenvectors of very large quaternionic (or Hermitian skew-Hamiltonian) matrices, using which structure-preserving diagonalisation of matrices of dimension N > 10, 000 is now routine on a single computer node. Such matrices appear frequently in relativistic quantum chemistry owing to the time-reversal symmetry. The implementation is based on a blocked version of the Paige-Van Loan algorithm, which allows us to use the Level 3 BLAS subroutines for most of the computations. Taking advantage of the symmetry, the program is faster by up to a factor of 2 than state-of-the-art implementations of complex Hermitian diagonalisation; diagonalising a 12, 800 × 12, 800 matrix took 42.8 (9.5) and 85.6 (12.6) minutes with 1 CPU core (16 CPU cores) using our symmetry-adapted solver and Intel Math Kernel Library's ZHEEV that is not structure-preserving, respectively. The source code is publicly available under the FreeBSD licence.

Effects of partitioning and scheduling sparse matrix factorization on communication and load balance

NASA Technical Reports Server (NTRS)

Venugopal, Sesh; Naik, Vijay K.

1991-01-01

A block based, automatic partitioning and scheduling methodology is presented for sparse matrix factorization on distributed memory systems. Using experimental results, this technique is analyzed for communication and load imbalance overhead. To study the performance effects, these overheads were compared with those obtained from a straightforward 'wrap mapped' column assignment scheme. All experimental results were obtained using test sparse matrices from the Harwell-Boeing data set. The results show that there is a communication and load balance tradeoff. The block based method results in lower communication cost whereas the wrap mapped scheme gives better load balance.

Computational Modeling of the Dielectric Barrier Discharge (DBD) Device for Aeronautical Applications

DTIC Science & Technology

2006-06-01

electron energy equation are solved semi-implicitly in a sequential manner. Each of the governing equations is solved by casting them onto a tridiagonal ...actuator for different device configurations and operating parameters. This will provide the Air Force with a low cost, quick turn around...Atmosphere (ATM) (20:8). Initially, the applied potential difference on the electrodes must be great enough to initiate gas breakdown. While

Self-assembly behavior of poly(fluorenyl styrene)-block-poly(2-vinyl pyridine) and their blends with single wall carbon nanotubes (SWCNT)

NASA Astrophysics Data System (ADS)

Mezzenga, Raffaele; Li, Chaoxu; Hsu, Jung-Ching; Chen, Wen-Chang; Sugiyama, Kenji; Hirao, Akira

2010-03-01

We describe a supramolecular strategy to disperse carbon nanotubes in block copolymer matrices. To achieve the desired functions and morphologies, comb-type architectures in which one and two fluorene units attached on the styrene ring of polystyrene-block-poly(2-vinyl pyridine) were studied. Depending on the pendant fluorene units, the block ratio, the casting solvent and thermal annealing history, multiple morphologies were found. The phase diagram, compared to PS-b-P2VP, was interpreted in terms of the conformational asymmetry arising from grafting of fluorene units of variable lengths. Hydrogen bonds between COOH-SWCNT and P2VP favor miscibility of SWCNT within P2VP domains and the blending of these two components is reflected both on the final morphologies and on the electron conductivity of the blends.

Decentralized state estimation for a large-scale spatially interconnected system.

PubMed

Liu, Huabo; Yu, Haisheng

2018-03-01

A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Unusual square roots in the ghost-free theory of massive gravity

NASA Astrophysics Data System (ADS)

Golovnev, Alexey; Smirnov, Fedor

2017-06-01

A crucial building block of the ghost free massive gravity is the square root function of a matrix. This is a problematic entity from the viewpoint of existence and uniqueness properties. We accurately describe the freedom of choosing a square root of a (non-degenerate) matrix. It has discrete and (in special cases) continuous parts. When continuous freedom is present, the usual perturbation theory in terms of matrices can be critically ill defined for some choices of the square root. We consider the new formulation of massive and bimetric gravity which deals directly with eigenvalues (in disguise of elementary symmetric polynomials) instead of matrices. It allows for a meaningful discussion of perturbation theory in such cases, even though certain non-analytic features arise.

A Performance Comparison of the Parallel Preconditioners for Iterative Methods for Large Sparse Linear Systems Arising from Partial Differential Equations on Structured Grids

NASA Astrophysics Data System (ADS)

Ma, Sangback

In this paper we compare various parallel preconditioners such as Point-SSOR (Symmetric Successive OverRelaxation), ILU(0) (Incomplete LU) in the Wavefront ordering, ILU(0) in the Multi-color ordering, Multi-Color Block SOR (Successive OverRelaxation), SPAI (SParse Approximate Inverse) and pARMS (Parallel Algebraic Recursive Multilevel Solver) for solving large sparse linear systems arising from two-dimensional PDE (Partial Differential Equation)s on structured grids. Point-SSOR is well-known, and ILU(0) is one of the most popular preconditioner, but it is inherently serial. ILU(0) in the Wavefront ordering maximizes the parallelism in the natural order, but the lengths of the wave-fronts are often nonuniform. ILU(0) in the Multi-color ordering is a simple way of achieving a parallelism of the order N, where N is the order of the matrix, but its convergence rate often deteriorates as compared to that of natural ordering. We have chosen the Multi-Color Block SOR preconditioner combined with direct sparse matrix solver, since for the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with the Multi-Color ordering. By using block version we expect to minimize the interprocessor communications. SPAI computes the sparse approximate inverse directly by least squares method. Finally, ARMS is a preconditioner recursively exploiting the concept of independent sets and pARMS is the parallel version of ARMS. Experiments were conducted for the Finite Difference and Finite Element discretizations of five two-dimensional PDEs with large meshsizes up to a million on an IBM p595 machine with distributed memory. Our matrices are real positive, i. e., their real parts of the eigenvalues are positive. We have used GMRES(m) as our outer iterative method, so that the convergence of GMRES(m) for our test matrices are mathematically guaranteed. Interprocessor communications were done using MPI (Message Passing Interface) primitives. The results show that in general ILU(0) in the Multi-Color ordering ahd ILU(0) in the Wavefront ordering outperform the other methods but for symmetric and nearly symmetric 5-point matrices Multi-Color Block SOR gives the best performance, except for a few cases with a small number of processors.

On Distributed Strategies in Defense of a High Value Unit (HVU) Against a Swarm Attack

DTIC Science & Technology

2012-09-01

function [ lam ,U] = tqr(a,b,U) % [ lam u] = tqr(a,b) or [ lam U] = tqr(a,b,U... lam u] = tqr(a,b): % % The column lam contains the eigenvalues of the Hermitian tridiagonal % matrix T = mxt(a,b) computed by one version of the...computed. The computed eigenvalues are real and are sorted to be % nonincreasing. % % [ lam U] = tqr(a,b,U): % % This replaces the input U

Implementation of a Fully-Balanced Periodic Tridiagonal Solver on a Parallel Distributed Memory Architecture

DTIC Science & Technology

1994-05-01

PARALLEL DISTRIBUTED MEMORY ARCHITECTURE LTJh T. M. Eidson 0 - 8 l 9 5 " G. Erlebacher _ _ _. _ DTIe QUALITY INSPECTED a Contract NAS I - 19480 May 1994...DISTRIBUTED MEMORY ARCHITECTURE T.M. Eidson * High Technology Corporation Hampton, VA 23665 G. Erlebachert Institute for Computer Applications in Science and...developed and evaluated. Simple model calculations as well as timing results are pres.nted to evaluate the various strategies. The particular

Parallel language constructs for tensor product computations on loosely coupled architectures

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Van Rosendale, John

1989-01-01

A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. The authors focus on tensor product array computations, a simple but important class of numerical algorithms. They consider first the problem of programming one-dimensional kernel routines, such as parallel tridiagonal solvers, and then look at how such parallel kernels can be combined to form parallel tensor product algorithms.

Some Factors Underlying Mathematical Performance: The Role of Visuospatial Working Memory and Non-Verbal Intelligence

ERIC Educational Resources Information Center

Kyttala, Minna; Lehto, Juhani E.

2008-01-01

Passive and active visuospatial working memory (VSWM) were investigated in relation to maths performance. The mental rotation task was employed as a measure of active VSWM whereas passive VSWM was investigated using a modified Corsi Blocks task and a matrix pattern task. The Raven Progressive Matrices Test measured fluid intelligence. A total of…

Some fast elliptic solvers on parallel architectures and their complexities

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Youcef

1989-01-01

The discretization of separable elliptic partial differential equations leads to linear systems with special block triangular matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconsistant coefficients. A method was recently proposed to parallelize and vectorize BCR. Here, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches, including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational complexity lower than that of parallel BCR.

Extracellular microvesicles and invadopodia mediate non-overlapping modes of tumor cell invasion

PubMed Central

Sedgwick, Alanna E.; Clancy, James W.; Olivia Balmert, M.; D’Souza-Schorey, Crislyn

2015-01-01

Tumor cell invasion requires the molecular and physical adaptation of both the cell and its microenvironment. Here we show that tumor cells are able to switch between the use of microvesicles and invadopodia to facilitate invasion through the extracellular matrix. Invadopodia formation accompanies the mesenchymal mode of migration on firm matrices and is facilitated by Rac1 activation. On the other hand, during invasion through compliant and deformable environments, tumor cells adopt an amoeboid phenotype and release microvesicles. Notably, firm matrices do not support microvesicle release, whereas compliant matrices are not conducive to invadopodia biogenesis. Furthermore, Rac1 activation is required for invadopodia function, while its inactivation promotes RhoA activation and actomyosin contractility required for microvesicle shedding. Suppression of RhoA signaling blocks microvesicle formation but enhances the formation of invadopodia. Finally, we describe Rho-mediated pathways involved in microvesicle biogenesis through the regulation of myosin light chain phosphatase. Our findings suggest that the ability of tumor cells to switch between the aforementioned qualitatively distinct modes of invasion may allow for dissemination across different microenvironments. PMID:26458510

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

Parallelized implicit propagators for the finite-difference Schrödinger equation

NASA Astrophysics Data System (ADS)

Parker, Jonathan; Taylor, K. T.

1995-08-01

We describe the application of block Gauss-Seidel and block Jacobi iterative methods to the design of implicit propagators for finite-difference models of the time-dependent Schrödinger equation. The block-wise iterative methods discussed here are mixed direct-iterative methods for solving simultaneous equations, in the sense that direct methods (e.g. LU decomposition) are used to invert certain block sub-matrices, and iterative methods are used to complete the solution. We describe parallel variants of the basic algorithm that are well suited to the medium- to coarse-grained parallelism of work-station clusters, and MIMD supercomputers, and we show that under a wide range of conditions, fine-grained parallelism of the computation can be achieved. Numerical tests are conducted on a typical one-electron atom Hamiltonian. The methods converge robustly to machine precision (15 significant figures), in some cases in as few as 6 or 7 iterations. The rate of convergence is nearly independent of the finite-difference grid-point separations.

Electromagnetic Scattering from a Structured Slab Comprised of Periodically Placed Resistive Cards

DTIC Science & Technology

1989-05-01

many different configurations of resistance may be computed at little additional cost. The three types of elements in the tridiagonal resistance...that of the B-52 bomber Reduction of the RCS is a hierarchical process in which each level of contribution must be taken care of by a different ...between the 3 currents of different unit cells; the currents on the entire structure must be treated as unknowns in a moment method solution. On the other

Coordinated Research Program in Pulsed Power Physics.

DTIC Science & Technology

1981-12-01

Ref. C11, this problem may be elimi- nated by factoring the tridiagonal , 2nd order, finite difference equation, Eq. (1), into two ist order finite ...13)Ti,o where 1h 2 /2 h2 = 2 - g + / -h g (1- - g) (14) 1+ h This solution to the finite difference equations consists of expo- nentially growing...December 1, 1981fl j,/,,- //,CJ’ .* ., .) - 13. NUMBEROF PAGES - A.)6 2 /’ij250 14. MONITORING AGENCY NAME & ADDRESS(iI different from Controlling

Low-rank factorization of electron integral tensors and its application in electronic structure theory

DOE PAGES

Peng, Bo; Kowalski, Karol

2017-01-25

In this paper, we apply reverse Cuthill-McKee (RCM) algorithm to transform two-electron integral tensors to their block diagonal forms. By further applying Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates low-rank factorizations of high-dimensional tensor contractions in post-Hartree-Fock calculations. Finally, we discuss the second-order Møller-Plesset (MP2) method and the linear coupled-cluster model with doubles (L-CCD) as examples to demonstrate the efficiency of this technique in representing the two-electron integrals in a compact form.

Low-rank factorization of electron integral tensors and its application in electronic structure theory

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

Peng, Bo; Kowalski, Karol

In this paper, we apply reverse Cuthill-McKee (RCM) algorithm to transform two-electron integral tensors to their block diagonal forms. By further applying Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates low-rank factorizations of high-dimensional tensor contractions in post-Hartree-Fock calculations. Finally, we discuss the second-order Møller-Plesset (MP2) method and the linear coupled-cluster model with doubles (L-CCD) as examples to demonstrate the efficiency of this technique in representing the two-electron integrals in a compact form.

A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance Structure Models to Block-Toeplitz Matrices Representing Single-Subject Multivariate Time-Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

1998-01-01

Pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation methods for estimating dynamic factor model parameters within a covariance structure framework were compared through a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates, but only ADF gives standard errors and chi-square…

Integrated Circuit For Simulation Of Neural Network

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

1988-01-01

Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

An efficient strongly coupled immersed boundary method for deforming bodies

NASA Astrophysics Data System (ADS)

Goza, Andres; Colonius, Tim

2016-11-01

Immersed boundary methods treat the fluid and immersed solid with separate domains. As a result, a nonlinear interface constraint must be satisfied when these methods are applied to flow-structure interaction problems. This typically results in a large nonlinear system of equations that is difficult to solve efficiently. Often, this system is solved with a block Gauss-Seidel procedure, which is easy to implement but can require many iterations to converge for small solid-to-fluid mass ratios. Alternatively, a Newton-Raphson procedure can be used to solve the nonlinear system. This typically leads to convergence in a small number of iterations for arbitrary mass ratios, but involves the use of large Jacobian matrices. We present an immersed boundary formulation that, like the Newton-Raphson approach, uses a linearization of the system to perform iterations. It therefore inherits the same favorable convergence behavior. However, we avoid large Jacobian matrices by using a block LU factorization of the linearized system. We derive our method for general deforming surfaces and perform verification on 2D test problems of flow past beams. These test problems involve large amplitude flapping and a wide range of mass ratios. This work was partially supported by the Jet Propulsion Laboratory and Air Force Office of Scientific Research.

Graph Theory Roots of Spatial Operators for Kinematics and Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Spatial operators have been used to analyze the dynamics of robotic multibody systems and to develop novel computational dynamics algorithms. Mass matrix factorization, inversion, diagonalization, and linearization are among several new insights obtained using such operators. While initially developed for serial rigid body manipulators, the spatial operators and the related mathematical analysis have been shown to extend very broadly including to tree and closed topology systems, to systems with flexible joints, links, etc. This work uses concepts from graph theory to explore the mathematical foundations of spatial operators. The goal is to study and characterize the properties of the spatial operators at an abstract level so that they can be applied to a broader range of dynamics problems. The rich mathematical properties of the kinematics and dynamics of robotic multibody systems has been an area of strong research interest for several decades. These properties are important to understand the inherent physical behavior of systems, for stability and control analysis, for the development of computational algorithms, and for model development of faithful models. Recurring patterns in spatial operators leads one to ask the more abstract question about the properties and characteristics of spatial operators that make them so broadly applicable. The idea is to step back from the specific application systems, and understand more deeply the generic requirements and properties of spatial operators, so that the insights and techniques are readily available across different kinematics and dynamics problems. In this work, techniques from graph theory were used to explore the abstract basis for the spatial operators. The close relationship between the mathematical properties of adjacency matrices for graphs and those of spatial operators and their kernels were established. The connections hold across very basic requirements on the system topology, the nature of the component bodies, the indexing schemes, etc. The relationship of the underlying structure is intimately connected with efficient, recursive computational algorithms. The results provide the foundational groundwork for a much broader look at the key problems in kinematics and dynamics. The properties of general graphs and trees of nodes and edge were examined, as well as the properties of adjacency matrices that are used to describe graph connectivity. The nilpotency property of such matrices for directed trees was reviewed, and the adjacency matrices were generalized to the notion of block weighted adjacency matrices that support block matrix elements. This leads us to the development of the notion of Spatial Kernel Operator SKO kernels. These kernels provide the basis for the development of SKO resolvent operators.

Proposed Standard For Variable Format Picture Processing And A Codec Approach To Match Diverse Imaging Devices

NASA Astrophysics Data System (ADS)

Wendler, Th.; Meyer-Ebrecht, D.

1982-01-01

Picture archiving and communication systems, especially those for medical applications, will offer the potential to integrate the various image sources of different nature. A major problem, however, is the incompatibility of the different matrix sizes and data formats. This may be overcome by a novel hierarchical coding process, which could lead to a unified picture format standard. A picture coding scheme is described, which decomposites a given (2n)2 picture matrix into a basic (2m)2 coarse information matrix (representing lower spatial frequencies) and a set of n-m detail matrices, containing information of increasing spatial resolution. Thus, the picture is described by an ordered set of data blocks rather than by a full resolution matrix of pixels. The blocks of data are transferred and stored using data formats, which have to be standardized throughout the system. Picture sources, which produce pictures of different resolution, will provide the coarse-matrix datablock and additionally only those detail matrices that correspond to their required resolution. Correspondingly, only those detail-matrix blocks need to be retrieved from the picture base, that are actually required for softcopy or hardcopy output. Thus, picture sources and retrieval terminals of diverse nature and retrieval processes for diverse purposes are easily made compatible. Furthermore this approach will yield an economic use of storage space and transmission capacity: In contrast to fixed formats, redundand data blocks are always skipped. The user will get a coarse representation even of a high-resolution picture almost instantaneously with gradually added details, and may abort transmission at any desired detail level. The coding scheme applies the S-transform, which is a simple add/substract algorithm basically derived from the Hadamard Transform. Thus, an additional data compression can easily be achieved especially for high-resolution pictures by applying appropriate non-linear and/or adaptive quantizing.

Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.

PubMed

Behrisch, Michael; Bach, Benjamin; Hund, Michael; Delz, Michael; Von Ruden, Laura; Fekete, Jean-Daniel; Schreck, Tobias

2017-01-01

In this work we address the problem of retrieving potentially interesting matrix views to support the exploration of networks. We introduce Matrix Diagnostics (or Magnostics), following in spirit related approaches for rating and ranking other visualization techniques, such as Scagnostics for scatter plots. Our approach ranks matrix views according to the appearance of specific visual patterns, such as blocks and lines, indicating the existence of topological motifs in the data, such as clusters, bi-graphs, or central nodes. Magnostics can be used to analyze, query, or search for visually similar matrices in large collections, or to assess the quality of matrix reordering algorithms. While many feature descriptors for image analyzes exist, there is no evidence how they perform for detecting patterns in matrices. In order to make an informed choice of feature descriptors for matrix diagnostics, we evaluate 30 feature descriptors-27 existing ones and three new descriptors that we designed specifically for MAGNOSTICS-with respect to four criteria: pattern response, pattern variability, pattern sensibility, and pattern discrimination. We conclude with an informed set of six descriptors as most appropriate for Magnostics and demonstrate their application in two scenarios; exploring a large collection of matrices and analyzing temporal networks.

Block matrix based LU decomposition to analyze kinetic damping in active plasma resonance spectroscopy

NASA Astrophysics Data System (ADS)

Roehl, Jan Hendrik; Oberrath, Jens

2016-09-01

``Active plasma resonance spectroscopy'' (APRS) is a widely used diagnostic method to measure plasma parameter like electron density. Measurements with APRS probes in plasmas of a few Pa typically show a broadening of the spectrum due to kinetic effects. To analyze the broadening a general kinetic model in electrostatic approximation based on functional analytic methods has been presented [ 1 ] . One of the main results is, that the system response function Y(ω) is given in terms of the matrix elements of the resolvent of the dynamic operator evaluated for values on the imaginary axis. To determine the response function of a specific probe the resolvent has to be approximated by a huge matrix which is given by a banded block structure. Due to this structure a block based LU decomposition can be implemented. It leads to a solution of Y(ω) which is given only by products of matrices of the inner block size. This LU decomposition allows to analyze the influence of kinetic effects on the broadening and saves memory and calculation time. Gratitude is expressed to the internal funding of Leuphana University.

Time-dependent generalized Gibbs ensembles in open quantum systems

NASA Astrophysics Data System (ADS)

Lange, Florian; Lenarčič, Zala; Rosch, Achim

2018-04-01

Generalized Gibbs ensembles have been used as powerful tools to describe the steady state of integrable many-particle quantum systems after a sudden change of the Hamiltonian. Here, we demonstrate numerically that they can be used for a much broader class of problems. We consider integrable systems in the presence of weak perturbations which break both integrability and drive the system to a state far from equilibrium. Under these conditions, we show that the steady state and the time evolution on long timescales can be accurately described by a (truncated) generalized Gibbs ensemble with time-dependent Lagrange parameters, determined from simple rate equations. We compare the numerically exact time evolutions of density matrices for small systems with a theory based on block-diagonal density matrices (diagonal ensemble) and a time-dependent generalized Gibbs ensemble containing only a small number of approximately conserved quantities, using the one-dimensional Heisenberg model with perturbations described by Lindblad operators as an example.

Locality preserving non-negative basis learning with graph embedding.

PubMed

Ghanbari, Yasser; Herrington, John; Gur, Ruben C; Schultz, Robert T; Verma, Ragini

2013-01-01

The high dimensionality of connectivity networks necessitates the development of methods identifying the connectivity building blocks that not only characterize the patterns of brain pathology but also reveal representative population patterns. In this paper, we present a non-negative component analysis framework for learning localized and sparse sub-network patterns of connectivity matrices by decomposing them into two sets of discriminative and reconstructive bases. In order to obtain components that are designed towards extracting population differences, we exploit the geometry of the population by using a graphtheoretical scheme that imposes locality-preserving properties as well as maintaining the underlying distance between distant nodes in the original and the projected space. The effectiveness of the proposed framework is demonstrated by applying it to two clinical studies using connectivity matrices derived from DTI to study a population of subjects with ASD, as well as a developmental study of structural brain connectivity that extracts gender differences.

Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation

PubMed Central

Jeon, Jessie S.; Bersini, Simone; Gilardi, Mara; Dubini, Gabriele; Charest, Joseph L.; Moretti, Matteo; Kamm, Roger D.

2015-01-01

A key aspect of cancer metastases is the tendency for specific cancer cells to home to defined subsets of secondary organs. Despite these known tendencies, the underlying mechanisms remain poorly understood. Here we develop a microfluidic 3D in vitro model to analyze organ-specific human breast cancer cell extravasation into bone- and muscle-mimicking microenvironments through a microvascular network concentrically wrapped with mural cells. Extravasation rates and microvasculature permeabilities were significantly different in the bone-mimicking microenvironment compared with unconditioned or myoblast containing matrices. Blocking breast cancer cell A3 adenosine receptors resulted in higher extravasation rates of cancer cells into the myoblast-containing matrices compared with untreated cells, suggesting a role for adenosine in reducing extravasation. These results demonstrate the efficacy of our model as a drug screening platform and a promising tool to investigate specific molecular pathways involved in cancer biology, with potential applications to personalized medicine. PMID:25524628

Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation.

PubMed

Jeon, Jessie S; Bersini, Simone; Gilardi, Mara; Dubini, Gabriele; Charest, Joseph L; Moretti, Matteo; Kamm, Roger D

2015-01-06

A key aspect of cancer metastases is the tendency for specific cancer cells to home to defined subsets of secondary organs. Despite these known tendencies, the underlying mechanisms remain poorly understood. Here we develop a microfluidic 3D in vitro model to analyze organ-specific human breast cancer cell extravasation into bone- and muscle-mimicking microenvironments through a microvascular network concentrically wrapped with mural cells. Extravasation rates and microvasculature permeabilities were significantly different in the bone-mimicking microenvironment compared with unconditioned or myoblast containing matrices. Blocking breast cancer cell A3 adenosine receptors resulted in higher extravasation rates of cancer cells into the myoblast-containing matrices compared with untreated cells, suggesting a role for adenosine in reducing extravasation. These results demonstrate the efficacy of our model as a drug screening platform and a promising tool to investigate specific molecular pathways involved in cancer biology, with potential applications to personalized medicine.

Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

NASA Astrophysics Data System (ADS)

Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

2017-10-01

We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

Numerical calculation of the neoclassical electron distribution function in an axisymmetric torus

NASA Astrophysics Data System (ADS)

Lyons, B. C.; Jardin, S. C.; Ramos, J. J.

2011-10-01

We solve for a stationary, axisymmetric electron distribution function (fe) in a torus using a drift-kinetic equation (DKE) with complete Landau collision operator. All terms are kept to gyroradius and collisionality orders relevant to high- temperature tokamaks (i.e., the neoclassical banana regime for electrons). A solubility condition on the DKE determines the non-Maxwellian pieces of fe (called fNMe) to all relevant orders. We work in a 4D phase space (ψ , θ , v , λ) , where ψ defines a flux surface, θ is the poloidal angle, v is the total velocity, and λ is the pitch angle parameter. We expand fNMe in finite elements in both v and λ. The Rosenbluth potentials, Φ and Ψ, which define the collision operator, are expanded in Legendre series in cos χ , where χ is the pitch angle, Fourier series in cos θ , and finite elements in v. At each ψ, we solve a block tridiagonal system for fNMe, Φ, and Ψ simultaneously, resulting in a neoclassical fe for the entire torus. Our goal is to demonstrate that such a formulation can be accurately and efficiently solved numerically. Results will be compared to other codes (e.g., NCLASS, NEO) and could be used as a kinetic closure for an MHD code (e.g., M3D-C1). Supported by the DOE SCGF and DOE Contract # DE-AC02-09CH11466. Based on analytic work by Ramos, PoP 17, 082502 (2010).

Development of the PARVMEC Code for Rapid Analysis of 3D MHD Equilibrium

NASA Astrophysics Data System (ADS)

Seal, Sudip; Hirshman, Steven; Cianciosa, Mark; Wingen, Andreas; Unterberg, Ezekiel; Wilcox, Robert; ORNL Collaboration

2015-11-01

The VMEC three-dimensional (3D) MHD equilibrium has been used extensively for designing stellarator experiments and analyzing experimental data in such strongly 3D systems. Recent applications of VMEC include 2D systems such as tokamaks (in particular, the D3D experiment), where application of very small (delB/B ~ 10-3) 3D resonant magnetic field perturbations render the underlying assumption of axisymmetry invalid. In order to facilitate the rapid analysis of such equilibria (for example, for reconstruction purposes), we have undertaken the task of parallelizing the VMEC code (PARVMEC) to produce a scalable and temporally rapidly convergent equilibrium code for use on parallel distributed memory platforms. The parallelization task naturally splits into three distinct parts 1) radial surfaces in the fixed-boundary part of the calculation; 2) two 2D angular meshes needed to compute the Green's function integrals over the plasma boundary for the free-boundary part of the code; and 3) block tridiagonal matrix needed to compute the full (3D) pre-conditioner near the final equilibrium state. Preliminary results show that scalability is achieved for tasks 1 and 3, with task 2 still nearing completion. The impact of this work on the rapid reconstruction of D3D plasmas using PARVMEC in the V3FIT code will be discussed. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.

Fast method to compute scattering by a buried object under a randomly rough surface: PILE combined with FB-SA.

PubMed

Bourlier, Christophe; Kubické, Gildas; Déchamps, Nicolas

2008-04-01

A fast, exact numerical method based on the method of moments (MM) is developed to calculate the scattering from an object below a randomly rough surface. Déchamps et al. [J. Opt. Soc. Am. A23, 359 (2006)] have recently developed the PILE (propagation-inside-layer expansion) method for a stack of two one-dimensional rough interfaces separating homogeneous media. From the inversion of the impedance matrix by block (in which two impedance matrices of each interface and two coupling matrices are involved), this method allows one to calculate separately and exactly the multiple-scattering contributions inside the layer in which the inverses of the impedance matrices of each interface are involved. Our purpose here is to apply this method for an object below a rough surface. In addition, to invert a matrix of large size, the forward-backward spectral acceleration (FB-SA) approach of complexity O(N) (N is the number of unknowns on the interface) proposed by Chou and Johnson [Radio Sci.33, 1277 (1998)] is applied. The new method, PILE combined with FB-SA, is tested on perfectly conducting circular and elliptic cylinders located below a dielectric rough interface obeying a Gaussian process with Gaussian and exponential height autocorrelation functions.

Continuous tone printing in silicone from CNC milled matrices

NASA Astrophysics Data System (ADS)

Hoskins, S.; McCallion, P.

2014-02-01

Current research at the Centre for Fine Print Research (CFPR) at the University of the West of England, Bristol, is exploring the potential of creating coloured pictorial imagery from a continuous tone relief surface. To create the printing matrices the research team have been using CNC milled images where the height of the relief image is dictated by creating a tone curve and then milling this curve into a series of relief blocks from which the image is cast in a silicone ink. A translucent image is cast from each of the colour matrices and each colour is assembled - one on top of another - resulting is a colour continuous tone print, where colour tone is created by physical depth of colour. This process is a contemporary method of continuous tone colour printing based upon the Nineteenth Century black and white printing process of Woodburytype as developed by Walter Bentley Woodbury in 1865. Woodburytype is the only true continuous tone printing process invented, and although its delicate and subtle surfaces surpassed all other printing methods at the time. The process died out in the late nineteenth century as more expedient and cost effective methods of printing prevailed. New research at CFPR builds upon previous research that combines 19th Century Photomechanical techniques with digital technology to reappraise the potential of these processes.

Application of p-Multigrid to Discontinuous Galerkin Formulations of the Poisson Equation

NASA Technical Reports Server (NTRS)

Helenbrook, B. T.; Atkins, H. L.

2006-01-01

We investigate p-multigrid as a solution method for several different discontinuous Galerkin (DG) formulations of the Poisson equation. Different combinations of relaxation schemes and basis sets have been combined with the DG formulations to find the best performing combination. The damping factors of the schemes have been determined using Fourier analysis for both one and two-dimensional problems. One important finding is that when using DG formulations, the standard approach of forming the coarse p matrices separately for each level of multigrid is often unstable. To ensure stability the coarse p matrices must be constructed from the fine grid matrices using algebraic multigrid techniques. Of the relaxation schemes, we find that the combination of Jacobi relaxation with the spectral element basis is fairly effective. The results using this combination are p sensitive in both one and two dimensions, but reasonable convergence rates can still be achieved for moderate values of p and isotropic meshes. A competitive alternative is a block Gauss-Seidel relaxation. This actually out performs a more expensive line relaxation when the mesh is isotropic. When the mesh becomes highly anisotropic, the implicit line method and the Gauss-Seidel implicit line method are the only effective schemes. Adding the Gauss-Seidel terms to the implicit line method gives a significant improvement over the line relaxation method.

Effect of poly(ethylene oxide) homopolymer and two different poly(ethylene oxide-b-poly(propylene oxide)-b-poly(ethylene oxide) triblock copolymers on morphological, optical, and mechanical properties of nanostructured unsaturated polyester.

PubMed

Builes, Daniel H; Hernández-Ortiz, Juan P; Corcuera, Ma Angeles; Mondragon, Iñaki; Tercjak, Agnieszka

2014-01-22

Novel nanostructured unsaturated polyester resin-based thermosets, modified with poly(ethylene oxide) (PEO), poly(propylene oxide) (PPO), and two poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) block copolymers (BCP), were developed and analyzed. The effects of molecular weights, blocks ratio, and curing temperatures on the final morphological, optical, and mechanical properties were reported. The block influence on the BCP miscibility was studied through uncured and cured mixtures of unsaturated polyester (UP) resins with PEO and PPO homopolymers having molecular weights similar to molecular weights of the blocks of BCP. The final morphology of the nanostructured thermosetting systems, containing BCP or homopolymers, was investigated, and multiple mechanisms of nanostructuration were listed and explained. By considering the miscibility of each block before and after curing, it was determined that the formation of the nanostructured matrices followed a self-assembly mechanism or a polymerization-induced phase separation mechanism. The miscibility between PEO or PPO blocks with one of two phases of UP matrix was highlighted due to its importance in the final thermoset properties. Relationships between the final morphology and thermoset optical and mechanical properties were examined. The mechanisms and physics behind the morphologies lead toward the design of highly transparent, nanostructured, and toughened thermosetting UP systems.

Graph Theoretic Foundations of Multibody Dynamics Part I: Structural Properties

PubMed Central

Jain, Abhinandan

2011-01-01

This is the first part of two papers that use concepts from graph theory to obtain a deeper understanding of the mathematical foundations of multibody dynamics. The key contribution is the development of a unifying framework that shows that key analytical results and computational algorithms in multibody dynamics are a direct consequence of structural properties and require minimal assumptions about the specific nature of the underlying multibody system. This first part focuses on identifying the abstract graph theoretic structural properties of spatial operator techniques in multibody dynamics. The second part paper exploits these structural properties to develop a broad spectrum of analytical results and computational algorithms. Towards this, we begin with the notion of graph adjacency matrices and generalize it to define block-weighted adjacency (BWA) matrices and their 1-resolvents. Previously developed spatial operators are shown to be special cases of such BWA matrices and their 1-resolvents. These properties are shown to hold broadly for serial and tree topology multibody systems. Specializations of the BWA and 1-resolvent matrices are referred to as spatial kernel operators (SKO) and spatial propagation operators (SPO). These operators and their special properties provide the foundation for the analytical and algorithmic techniques developed in the companion paper. We also use the graph theory concepts to study the topology induced sparsity structure of these operators and the system mass matrix. Similarity transformations of these operators are also studied. While the detailed development is done for the case of rigid-link multibody systems, the extension of these techniques to a broader class of systems (e.g. deformable links) are illustrated. PMID:22102790

Interfacial adhesion of carbon fibers

NASA Technical Reports Server (NTRS)

Bascom, Willard D.

1987-01-01

Relative adhesion strengths between AS4, AS1, and XAS carbon fibers and thermoplastic polymers were determined using the embedded single filament test. Polymers studied included polycarbonate, polyphenylene oxide, polyetherimide, polysulfone, polyphenylene oxide blends with polystyrene, and polycarbonate blends with a polycarbonate polysiloxane block copolymer. Fiber surface treatments and sizings improved adhesion somewhat, but adhesion remained well below levels obtained with epoxy matrices. An explanation for the differences between the Hercules and Grafil fibers was sought using X ray photon spectroscopy, wetting, scanning electron microscopy and thermal desorption analysis.

Profiling of Sugar Nucleotides.

PubMed

Rejzek, Martin; Hill, Lionel; Hems, Edward S; Kuhaudomlarp, Sakonwan; Wagstaff, Ben A; Field, Robert A

2017-01-01

Sugar nucleotides are essential building blocks for the glycobiology of all living organisms. Detailed information on the types of sugar nucleotides present in a particular cell and how they change as a function of metabolic, developmental, or disease status is vital. The extraction, identification, and quantification of sugar nucleotides in a given sample present formidable challenges. In this chapter, currently used techniques for sugar nucleotide extraction from cells, separation from complex biological matrices, and detection by optical and mass spectrometry methods are discussed. © 2017 Elsevier Inc. All rights reserved.

Nonequilibrium thermo-chemical calculations using a diagonal implicit scheme

NASA Technical Reports Server (NTRS)

Imlay, Scott T.; Roberts, Donald W.; Soetrisno, Moeljo; Eberhardt, Scott

1991-01-01

A recently developed computer program for hypersonic vehicle flow analysis is described. The program uses a diagonal implicit algorithm to solve the equations of viscous flow for a gas in thermochemical nonequilibrium. The diagonal scheme eliminates the expense of inverting large block matrices that arise when species conservation equations are introduced. The program uses multiple zones of grids patched together and includes radiation wall and rarefied gas boundary conditions. Solutions are presented for hypersonic flows of air and hydrogen air mixtures.

Symmetry breaking by bifundamentals

NASA Astrophysics Data System (ADS)

Schellekens, A. N.

2018-03-01

We derive all possible symmetry breaking patterns for all possible Higgs fields that can occur in intersecting brane models: bifundamentals and rank-2 tensors. This is a field-theoretic problem that was already partially solved in 1973 by Ling-Fong Li [1]. In that paper the solution was given for rank-2 tensors of orthogonal and unitary group, and U (N )×U (M ) and O (N )×O (M ) bifundamentals. We extend this first of all to symplectic groups. When formulated correctly, this turns out to be straightforward generalization of the previous results from real and complex numbers to quaternions. The extension to mixed bifundamentals is more challenging and interesting. The scalar potential has up to six real parameters. Its minima or saddle points are described by block-diagonal matrices built out of K blocks of size p ×q . Here p =q =1 for the solutions of Ling-Fong Li, and the number of possibilities for p ×q is equal to the number of real parameters in the potential, minus 1. The maximum block size is p ×q =2 ×4 . Different blocks cannot be combined, and the true minimum occurs for one choice of basic block, and for either K =1 or K maximal, depending on the parameter values.

Real-Time Cytotoxicity Assay for Rapid and Sensitive Detection of Ricin from Complex Matrices

PubMed Central

Pauly, Diana; Worbs, Sylvia; Kirchner, Sebastian; Shatohina, Olena; Dorner, Martin B.; Dorner, Brigitte G.

2012-01-01

Background In the context of a potential bioterrorist attack sensitive and fast detection of functionally active toxins such as ricin from complex matrices is necessary to be able to start timely countermeasures. One of the functional detection methods currently available for ricin is the endpoint cytotoxicity assay, which suffers from a number of technical deficits. Methodology/Findings This work describes a novel online cytotoxicity assay for the detection of active ricin and Ricinus communis agglutinin, that is based on a real-time cell electronic sensing system and impedance measurement. Characteristic growth parameters of Vero cells were monitored online and used as standardized viability control. Upon incubation with toxin the cell status and the cytotoxic effect were visualized using a characteristic cell index–time profile. For ricin, tested in concentrations of 0.06 ng/mL or above, a concentration-dependent decrease of cell index correlating with cytotoxicity was recorded between 3.5 h and 60 h. For ricin, sensitive detection was determined after 24 h, with an IC50 of 0.4 ng/mL (for agglutinin, an IC50 of 30 ng/mL was observed). Using functionally blocking antibodies, the specificity for ricin and agglutinin was shown. For detection from complex matrices, ricin was spiked into several food matrices, and an IC50 ranging from 5.6 to 200 ng/mL was observed. Additionally, the assay proved to be useful in detecting active ricin in environmental sample materials, as shown for organic fertilizer containing R. communis material. Conclusions/Significance The cell-electrode impedance measurement provides a sensitive online detection method for biologically active cytotoxins such as ricin. As the cell status is monitored online, the assay can be standardized more efficiently than previous approaches based on endpoint measurement. More importantly, the real-time cytotoxicity assay provides a fast and easy tool to detect active ricin in complex sample matrices. PMID:22532852

Four-parameter potential box with inverse square singular boundaries

NASA Astrophysics Data System (ADS)

Alhaidari, A. D.; Taiwo, T. J.

2018-03-01

Using the Tridiagonal Representation Approach (TRA), we obtain solutions (energy spectrum and corresponding wavefunctions) for a four-parameter potential box with inverse square singularity at the boundaries. It could be utilized in physical applications to replace the widely used one-parameter infinite square potential well (ISPW). The four parameters of the potential provide an added flexibility over the one-parameter ISPW to control the physical features of the system. The two potential parameters that give the singularity strength at the boundaries are naturally constrained to avoid the inherent quantum anomalies associated with the inverse square potential.

Noniterative three-dimensional grid generation using parabolic partial differential equations

NASA Technical Reports Server (NTRS)

Edwards, T. A.

1985-01-01

A new algorithm for generating three-dimensional grids has been developed and implemented which numerically solves a parabolic partial differential equation (PDE). The solution procedure marches outward in two coordinate directions, and requires inversion of a scalar tridiagonal system in the third. Source terms have been introduced to control the spacing and angle of grid lines near the grid boundaries, and to control the outer boundary point distribution. The method has been found to generate grids about 100 times faster than comparable grids generated via solution of elliptic PDEs, and produces smooth grids for finite-difference flow calculations.

A case against a divide and conquer approach to the nonsymmetric eigenvalue problem

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

Jessup, E.R.

1991-12-01

Divide and conquer techniques based on rank-one updating have proven fast, accurate, and efficient in parallel for the real symmetric tridiagonal and unitary eigenvalue problems and for the bidiagonal singular value problem. Although the divide and conquer mechanism can also be adapted to the real nonsymmetric eigenproblem in a straightforward way, most of the desirable characteristics of the other algorithms are lost. In this paper, we examine the problems of accuracy and efficiency that can stand in the way of a nonsymmetric divide and conquer eigensolver based on low-rank updating. 31 refs., 2 figs.

Trajectory Generation by Piecewise Spline Interpolation

DTIC Science & Technology

1976-04-01

Lx) -a 0 + atx + aAx + x (21)0 1 2 3 and the coefficients are obtained from Equation (20) as ao m fl (22)i al " fi, (23) S3(fi + I f ) 2fj + fj+ 1 (24...reference frame to the vehicle fixed frame is pTO’ 0TO’ OTO’ *TO where a if (gZv0 - A >- 0 aCI (64) - azif (gzv0- AzvO < 0 These rotations may be...velocity frame axes directions (velocity frame from the output frame) aO, al , a 2 , a 3 Coefficients of the piecewise cubic polynomials [B ] Tridiagonal

Data traffic reduction schemes for Cholesky factorization on asynchronous multiprocessor systems

NASA Technical Reports Server (NTRS)

Naik, Vijay K.; Patrick, Merrell L.

1989-01-01

Communication requirements of Cholesky factorization of dense and sparse symmetric, positive definite matrices are analyzed. The communication requirement is characterized by the data traffic generated on multiprocessor systems with local and shared memory. Lower bound proofs are given to show that when the load is uniformly distributed the data traffic associated with factoring an n x n dense matrix using n to the alpha power (alpha less than or equal 2) processors is omega(n to the 2 + alpha/2 power). For n x n sparse matrices representing a square root of n x square root of n regular grid graph the data traffic is shown to be omega(n to the 1 + alpha/2 power), alpha less than or equal 1. Partitioning schemes that are variations of block assignment scheme are described and it is shown that the data traffic generated by these schemes are asymptotically optimal. The schemes allow efficient use of up to O(n to the 2nd power) processors in the dense case and up to O(n) processors in the sparse case before the total data traffic reaches the maximum value of O(n to the 3rd power) and O(n to the 3/2 power), respectively. It is shown that the block based partitioning schemes allow a better utilization of the data accessed from shared memory and thus reduce the data traffic than those based on column-wise wrap around assignment schemes.

Projective loop quantum gravity. I. State space

NASA Astrophysics Data System (ADS)

Lanéry, Suzanne; Thiemann, Thomas

2016-12-01

Instead of formulating the state space of a quantum field theory over one big Hilbert space, it has been proposed by Kijowski to describe quantum states as projective families of density matrices over a collection of smaller, simpler Hilbert spaces. Beside the physical motivations for this approach, it could help designing a quantum state space holding the states we need. In a latter work by Okolów, the description of a theory of Abelian connections within this framework was developed, an important insight being to use building blocks labeled by combinations of edges and surfaces. The present work generalizes this construction to an arbitrary gauge group G (in particular, G is neither assumed to be Abelian nor compact). This involves refining the definition of the label set, as well as deriving explicit formulas to relate the Hilbert spaces attached to different labels. If the gauge group happens to be compact, we also have at our disposal the well-established Ashtekar-Lewandowski Hilbert space, which is defined as an inductive limit using building blocks labeled by edges only. We then show that the quantum state space presented here can be thought as a natural extension of the space of density matrices over this Hilbert space. In addition, it is manifest from the classical counterparts of both formalisms that the projective approach allows for a more balanced treatment of the holonomy and flux variables, so it might pave the way for the development of more satisfactory coherent states.

Spectral analysis of GEOS-3 altimeter data and frequency domain collocation. [to estimate gravity anomalies

NASA Technical Reports Server (NTRS)

Eren, K.

1980-01-01

The mathematical background in spectral analysis as applied to geodetic applications is summarized. The resolution (cut-off frequency) of the GEOS 3 altimeter data is examined by determining the shortest wavelength (corresponding to the cut-off frequency) recoverable. The data from some 18 profiles are used. The total power (variance) in the sea surface topography with respect to the reference ellipsoid as well as with respect to the GEM-9 surface is computed. A fast inversion algorithm for matrices of simple and block Toeplitz matrices and its application to least squares collocation is explained. This algorithm yields a considerable gain in computer time and storage in comparison with conventional least squares collocation. Frequency domain least squares collocation techniques are also introduced and applied to estimating gravity anomalies from GEOS 3 altimeter data. These techniques substantially reduce the computer time and requirements in storage associated with the conventional least squares collocation. Numerical examples given demonstrate the efficiency and speed of these techniques.

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

Closure of the operator product expansion in the non-unitary bootstrap

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

Esterlis, Ilya; Fitzpatrick, A. Liam; Ramirez, David M.

We use the numerical conformal bootstrap in two dimensions to search for finite, closed sub-algebras of the operator product expansion (OPE), without assuming unitarity. We find the minimal models as special cases, as well as additional lines of solutions that can be understood in the Coulomb gas formalism. All the solutions we find that contain the vacuum in the operator algebra are cases where the external operators of the bootstrap equation are degenerate operators, and we argue that this follows analytically from the expressions in arXiv:1202.4698 for the crossing matrices of Virasoro conformal blocks. Our numerical analysis is a specialmore » case of the “Gliozzi” bootstrap method, and provides a simpler setting in which to study technical challenges with the method. In the supplementary material, we provide a Mathematica notebook that automates the calculation of the crossing matrices and OPE coefficients for degenerate operators using the formulae of Dotsenko and Fateev.« less

Closure of the operator product expansion in the non-unitary bootstrap

DOE PAGES

Esterlis, Ilya; Fitzpatrick, A. Liam; Ramirez, David M.

2016-11-07

We use the numerical conformal bootstrap in two dimensions to search for finite, closed sub-algebras of the operator product expansion (OPE), without assuming unitarity. We find the minimal models as special cases, as well as additional lines of solutions that can be understood in the Coulomb gas formalism. All the solutions we find that contain the vacuum in the operator algebra are cases where the external operators of the bootstrap equation are degenerate operators, and we argue that this follows analytically from the expressions in arXiv:1202.4698 for the crossing matrices of Virasoro conformal blocks. Our numerical analysis is a specialmore » case of the “Gliozzi” bootstrap method, and provides a simpler setting in which to study technical challenges with the method. In the supplementary material, we provide a Mathematica notebook that automates the calculation of the crossing matrices and OPE coefficients for degenerate operators using the formulae of Dotsenko and Fateev.« less

Use of Massive Parallel Computing Libraries in the Context of Global Gravity Field Determination from Satellite Data

NASA Astrophysics Data System (ADS)

Brockmann, J. M.; Schuh, W.-D.

2011-07-01

The estimation of the global Earth's gravity field parametrized as a finite spherical harmonic series is computationally demanding. The computational effort depends on the one hand on the maximal resolution of the spherical harmonic expansion (i.e. the number of parameters to be estimated) and on the other hand on the number of observations (which are several millions for e.g. observations from the GOCE satellite missions). To circumvent these restrictions, a massive parallel software based on high-performance computing (HPC) libraries as ScaLAPACK, PBLAS and BLACS was designed in the context of GOCE HPF WP6000 and the GOCO consortium. A prerequisite for the use of these libraries is that all matrices are block-cyclic distributed on a processor grid comprised by a large number of (distributed memory) computers. Using this set of standard HPC libraries has the benefit that once the matrices are distributed across the computer cluster, a huge set of efficient and highly scalable linear algebra operations can be used.

Electronomicroscopic evaluation of the microlesional aspects in the pulp dentinal complex after repeated whitening therapy

NASA Astrophysics Data System (ADS)

Bodea, Rodica; Jianu, Rodica; Marchese, Cristian; Vasile, Liliana

2012-06-01

The aim of this study was to examine cellular and matriceal dynamics within pulp tissue of the teeth with repeated bleaching. Material and method - The study was made on 25 patients aged between 15 and 45, to whom bleaching method of the premolars with indication of extraction in orthodontic purposes was applied. None of the subjects smoked and throughout the investigation no antibiotics had been used. We initiated an intensive oral hygiene program, and we removed the supragingival and subgingival deposits. Oral hygiene and the gingival health were evaluated before every session of bleaching. During each visit the dentition was cleaned professionally and if needed the subjects were reinstucted in proper oral hygiene. After 3 and 5 successive bleachings of the teeth, we removed the dental pulps and we extracted the premolars. The pulpal biopsies were fixed in buffed formaldehyde 10% for 48 hours, then paraffinized, sectioned at 3-5 μ and stained with topographic, H&E and trichrome stained. For the electonomicroscopic study we used the Lehner technique to process the biopsies (n=3) after the reinclusion of the pieces from the paraffine blocks in Epon, postfixated in buffered glutaraldehyde, micro sectioned at 0,5 μ, contrastated with Pb citrate (stained) and examination in transmission electronic microscopy with Philips microscope. Results - At cellular and matriceal level we observed a marked collagen fibrillogenesis in the presence of active fibroblasts, with well developed cellular organites and fibroclastic aspects which suggest matriceal active repair. The microvascular network presents an activated endothelium with turgescent endothelial cells, with intracitoplasmatic resorbtion vacuols, well developed Golgi Complex. Conclusion - We interpreed the cell - matriceal lesions in the context of the acute inflammatory process in the first lesional phase and chronic scleroatrophic process after successive bleaching.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Watson, Andrew B.

1994-01-01

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Large-scale 3-D EM modelling with a Block Low-Rank multifrontal direct solver

NASA Astrophysics Data System (ADS)

Shantsev, Daniil V.; Jaysaval, Piyoosh; de la Kethulle de Ryhove, Sébastien; Amestoy, Patrick R.; Buttari, Alfredo; L'Excellent, Jean-Yves; Mary, Theo

2017-06-01

We put forward the idea of using a Block Low-Rank (BLR) multifrontal direct solver to efficiently solve the linear systems of equations arising from a finite-difference discretization of the frequency-domain Maxwell equations for 3-D electromagnetic (EM) problems. The solver uses a low-rank representation for the off-diagonal blocks of the intermediate dense matrices arising in the multifrontal method to reduce the computational load. A numerical threshold, the so-called BLR threshold, controlling the accuracy of low-rank representations was optimized by balancing errors in the computed EM fields against savings in floating point operations (flops). Simulations were carried out over large-scale 3-D resistivity models representing typical scenarios for marine controlled-source EM surveys, and in particular the SEG SEAM model which contains an irregular salt body. The flop count, size of factor matrices and elapsed run time for matrix factorization are reduced dramatically by using BLR representations and can go down to, respectively, 10, 30 and 40 per cent of their full-rank values for our largest system with N = 20.6 million unknowns. The reductions are almost independent of the number of MPI tasks and threads at least up to 90 × 10 = 900 cores. The BLR savings increase for larger systems, which reduces the factorization flop complexity from O(N2) for the full-rank solver to O(Nm) with m = 1.4-1.6. The BLR savings are significantly larger for deep-water environments that exclude the highly resistive air layer from the computational domain. A study in a scenario where simulations are required at multiple source locations shows that the BLR solver can become competitive in comparison to iterative solvers as an engine for 3-D controlled-source electromagnetic Gauss-Newton inversion that requires forward modelling for a few thousand right-hand sides.

Tumor cell invasion of collagen matrices requires coordinate lipid agonist-induced G-protein and membrane-type matrix metalloproteinase-1-dependent signaling.

PubMed

Fisher, Kevin E; Pop, Andreia; Koh, Wonshill; Anthis, Nicholas J; Saunders, W Brian; Davis, George E

2006-12-08

Lysophosphatidic acid (LPA) and sphingosine 1-phosphate (S1P) are bioactive lipid signaling molecules implicated in tumor dissemination. Membrane-type matrix metalloproteinase 1 (MT1-MMP) is a membrane-tethered collagenase thought to be involved in tumor invasion via extracellular matrix degradation. In this study, we investigated the molecular requirements for LPA- and S1P-regulated tumor cell migration in two dimensions (2D) and invasion of three-dimensional (3D) collagen matrices and, in particular, evaluated the role of MT1-MMP in this process. LPA stimulated while S1P inhibited migration of most tumor lines in Boyden chamber assays. Conversely, HT1080 fibrosarcoma cells migrated in response to both lipids. HT1080 cells also markedly invaded 3D collagen matrices (approximatly 700 microm over 48 hours) in response to either lipid. siRNA targeting of LPA1 and Rac1, or S1P1, Rac1, and Cdc42 specifically inhibited LPA- or S1P-induced HT1080 invasion, respectively. Analysis of LPA-induced HT1080 motility on 2D substrates vs. 3D matrices revealed that synthetic MMP inhibitors markedly reduced the distance (approximately 125 microm vs. approximately 45 microm) and velocity of invasion (approximately 0.09 microm/min vs. approximately 0.03 microm/min) only when cells navigated 3D matrices signifying a role for MMPs exclusively in invasion. Additionally, tissue inhibitors of metalloproteinases (TIMPs)-2, -3, and -4, but not TIMP-1, blocked lipid agonist-induced invasion indicating a role for membrane-type (MT)-MMPs. Furthermore, MT1-MMP expression in several tumor lines directly correlated with LPA-induced invasion. HEK293s, which neither express MT1-MMP nor invade in the presence of LPA, were transfected with MT1-MMP cDNA, and subsequently invaded in response to LPA. When HT1080 cells were seeded on top of or within collagen matrices, siRNA targeting of MT1-MMP, but not other MMPs, inhibited lipid agonist-induced invasion establishing a requisite role for MT1-MMP in this process. LPA is a fundamental regulator of MT1-MMP-dependent tumor cell invasion of 3D collagen matrices. In contrast, S1P appears to act as an inhibitory stimulus in most cases, while stimulating only select tumor lines. MT1-MMP is required only when tumor cells navigate 3D barriers and not when cells migrate on 2D substrata. We demonstrate that tumor cells require coordinate regulation of LPA/S1P receptors and Rho GTPases to migrate, and additionally, require MT1-MMP in order to invade collagen matrices during neoplastic progression.

A Fast Estimation Algorithm for Two-Dimensional Gravity Data (GEOFAST),

DTIC Science & Technology

1979-11-15

to a wide class of problems (Refs. 9 and 17). The major inhibitor to the widespread appli- ( cation of optimal gravity data processing is the severe...extends directly to two dimensions. Define the nln 2xn1 n2 diagonal window matrix W as the Kronecker product of two one-dimensional windows W = W1 0 W2 (B...Inversion of Separable Matrices Consider the linear system y = T x (B.3-1) where T is block Toeplitz of dimension nln 2xnIn 2 . Its fre- quency domain

Nickel-impregnated silica nanoparticle synthesis and their evaluation for biocatalyst immobilization.

PubMed

Prakasham, Reddy Shetty; Devi, G Sarala; Rao, Chaganti Subba; Sivakumar, V S S; Sathish, T; Sarma, P N

2010-04-01

In the present investigation, impact of nickel-impregnated silica paramagnetic particles (NSP) as biocatalyst immobilization matrices was investigated. These nanoparticles were synthesized by sol-gel route using a nonionic surfactant block co polymer [poly (ethylene glycol)-block-poly-(propylene glycol)-block-poly (ethylene glycol)]. Diastase enzyme was immobilized on these particles (enzyme-impregnated NSP) as model enzyme and characterized using Fourier-transform infrared spectroscopy and X-ray crystallography. Analysis of enzyme-binding nature with these nanoparticles at different physiological conditions revealed that binding pattern and activity profile varied with the pH of the reaction mixture. The immobilized enzyme was further characterized for its biocatalytic activity with respect to kinetic properties such as Km and Vmax and compared with free enzyme. Paramagnetic nanoparticle-immobilized enzyme showed more affinity for substrate compared to free one. The nature of silica and nickel varied from amorphous to crystalline nature and vice versa upon immobilization of enzyme. To the best of our knowledge, this is the first report of its kind for change of nature from one form to other under normal temperatures upon diastase interaction with NSP.

Synthesis and controlled self-assembly of UV-responsive gold nanoparticles in block copolymer templates.

PubMed

Song, Dong-Po; Wang, Xinyu; Lin, Ying; Watkins, James J

2014-11-06

We demonstrate the facile synthesis of gold nanoparticles (GNPs) functionalized by UV-responsive block copolymer ligands, poly(styrene)-b-poly(o-nitrobenzene acrylate)-SH (PS-b-PNBA-SH), followed by their targeted distribution within a lamellae-forming poly(styrene)-b-poly(2-vinylpyridine) (PS-b-P2VP) block copolymer. The multilayer, micelle-like structure of the GNPs consists of a gold core, an inner PNBA layer, and an outer PS layer. The UV-sensitive PNBA segment can be deprotected into a layer containing poly(acrylic acid) (PAA) when exposed to UV light at 365 nm, which enables the simple and precise tuning of GNP surface properties from hydrophobic to amphiphilic. The GNPs bearing ligands of different chemical compositions were successfully and selectively incorporated into the PS-b-P2VP block copolymer, and UV light showed a profound influence on the spatial distributions of GNPs. Prior to UV exposure, GNPs partition along the interfaces of PS and P2VP domains, while the UV-treated GNPs are incorporated into P2VP domains as a result of hydrogen bond interactions between PAA on the gold surface and P2VP domains. This provides an easy way of controlling the arrangement of nanoparticles in polymer matrices by tailoring the nanoparticle surface using UV light.

Block-diagonalization as a tool for the robust diabatization of high-dimensional potential energy surfaces

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

Venghaus, Florian; Eisfeld, Wolfgang, E-mail: wolfgang.eisfeld@uni-bielefeld.de

2016-03-21

Robust diabatization techniques are key for the development of high-dimensional coupled potential energy surfaces (PESs) to be used in multi-state quantum dynamics simulations. In the present study we demonstrate that, besides the actual diabatization technique, common problems with the underlying electronic structure calculations can be the reason why a diabatization fails. After giving a short review of the theoretical background of diabatization, we propose a method based on the block-diagonalization to analyse the electronic structure data. This analysis tool can be used in three different ways: First, it allows to detect issues with the ab initio reference data and ismore » used to optimize the setup of the electronic structure calculations. Second, the data from the block-diagonalization are utilized for the development of optimal parametrized diabatic model matrices by identifying the most significant couplings. Third, the block-diagonalization data are used to fit the parameters of the diabatic model, which yields an optimal initial guess for the non-linear fitting required by standard or more advanced energy based diabatization methods. The new approach is demonstrated by the diabatization of 9 electronic states of the propargyl radical, yielding fully coupled full-dimensional (12D) PESs in closed form.« less

Microzonation of seismic risk in a low-rise Latin American city based on the macroseismic evaluation of the vulnerability of residential buildings: Colima city, México

NASA Astrophysics Data System (ADS)

Zobin, V. M.; Cruz-Bravo, A. A.; Ventura-Ramírez, F.

2010-06-01

A macroseismic methodology of seismic risk microzonation in a low-rise city based on the vulnerability of residential buildings is proposed and applied to Colima city, Mexico. The seismic risk microzonation for Colima consists of two elements: the mapping of residential blocks according to their vulnerability level and the calculation of an expert-opinion based damage probability matrix (DPM) for a given level of earthquake intensity and a given type of residential block. A specified exposure time to the seismic risk for this zonation is equal to the interval between two destructive earthquakes. The damage probability matrices were calculated for three types of urban buildings and five types of residential blocks in Colima. It was shown that only 9% of 1409 residential blocks are able to resist to the Modify Mercalli (MM) intensity VII and VIII earthquakes without significant damage. The proposed DPM-2007 is in good accordance with the experimental damage curves based on the macroseismic evaluation of 3332 residential buildings in Colima that was carried out after the 21 January 2003 intensity MM VII earthquake. This methodology and the calculated PDM-2007 curves may be applied also to seismic risk microzonation for many low-rise cities in Latin America, Asia, and Africa.

Preconditioned Mixed Spectral Element Methods for Elasticity and Stokes Problems

NASA Technical Reports Server (NTRS)

Pavarino, Luca F.

1996-01-01

Preconditioned iterative methods for the indefinite systems obtained by discretizing the linear elasticity and Stokes problems with mixed spectral elements in three dimensions are introduced and analyzed. The resulting stiffness matrices have the structure of saddle point problems with a penalty term, which is associated with the Poisson ratio for elasticity problems or with stabilization techniques for Stokes problems. The main results of this paper show that the convergence rate of the resulting algorithms is independent of the penalty parameter, the number of spectral elements Nu and mildly dependent on the spectral degree eta via the inf-sup constant. The preconditioners proposed for the whole indefinite system are block-diagonal and block-triangular. Numerical experiments presented in the final section show that these algorithms are a practical and efficient strategy for the iterative solution of the indefinite problems arising from mixed spectral element discretizations of elliptic systems.

Investigation of adaptive filtering and MDL mitigation based on space-time block-coding for spatial division multiplexed coherent receivers

NASA Astrophysics Data System (ADS)

Weng, Yi; He, Xuan; Yao, Wang; Pacheco, Michelle C.; Wang, Junyi; Pan, Zhongqi

2017-07-01

In this paper, we explored the performance of space-time block-coding (STBC) assisted multiple-input multiple-output (MIMO) scheme for modal dispersion and mode-dependent loss (MDL) mitigation in spatial-division multiplexed optical communication systems, whereas the weight matrices of frequency-domain equalization (FDE) were updated heuristically using decision-directed recursive least squares (RLS) algorithm for convergence and channel estimation. The proposed STBC-RLS algorithm can achieve 43.6% enhancement on convergence rate over conventional least mean squares (LMS) for quadrature phase-shift keying (QPSK) signals with merely 16.2% increase in hardware complexity. The overall optical signal to noise ratio (OSNR) tolerance can be improved via STBC by approximately 3.1, 4.9, 7.8 dB for QPSK, 16-quadrature amplitude modulation (QAM) and 64-QAM with respective bit-error-rates (BER) and minimum-mean-square-error (MMSE).

Multivariable frequency domain identification via 2-norm minimization

NASA Technical Reports Server (NTRS)

Bayard, David S.

1992-01-01

The author develops a computational approach to multivariable frequency domain identification, based on 2-norm minimization. In particular, a Gauss-Newton (GN) iteration is developed to minimize the 2-norm of the error between frequency domain data and a matrix fraction transfer function estimate. To improve the global performance of the optimization algorithm, the GN iteration is initialized using the solution to a particular sequentially reweighted least squares problem, denoted as the SK iteration. The least squares problems which arise from both the SK and GN iterations are shown to involve sparse matrices with identical block structure. A sparse matrix QR factorization method is developed to exploit the special block structure, and to efficiently compute the least squares solution. A numerical example involving the identification of a multiple-input multiple-output (MIMO) plant having 286 unknown parameters is given to illustrate the effectiveness of the algorithm.

Treatment of toxic metal aqueous solutions: encapsulation in a phosphate-calcium aluminate matrix.

PubMed

Fernández, J M; Navarro-Blasco, I; Duran, A; Sirera, R; Alvarez, J I

2014-07-01

Polyphosphate-modified calcium aluminate cement matrices were prepared by using aqueous solutions polluted with toxic metals as mixing water to obtain waste-containing solid blocks with improved management and disposal. Synthetically contaminated waters containing either Pb or Cu or Zn were incorporated into phosphoaluminate cement mortars and the effects of the metal's presence on setting time and mechanical performance were assessed. Sorption and leaching tests were also executed and both retention and release patterns were investigated. For all three metals, high uptake capacities as well as percentages of retention larger than 99.9% were measured. Both Pb and Cu were seen to be largely compatible with this cementitious matrix, rendering the obtained blocks suitable for landfilling or for building purposes. However, Zn spoilt the compressive strength values because of its reaction with hydrogen phosphate anions, hindering the development of the binding matrix. Copyright © 2014 Elsevier Ltd. All rights reserved.

Low-rank factorization of electron integral tensors and its application in electronic structure theory

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

Peng, Bo; Kowalski, Karol

In this letter, we introduce the reverse Cuthill-McKee (RCM) algorithm, which is often used for the bandwidth reduction of sparse tensors, to transform the two-electron integral tensors to their block diagonal forms. By further applying the pivoted Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates the low-rank factorization of the high-dimensional tensor contractions that are usually encountered in post-Hartree-Fock calculations. In this letter, we discuss the second-order Møller-Plesset (MP2) method and linear coupled- cluster model with doublesmore » (L-CCD) as two simple examples to demonstrate the efficiency of the RCM-CD technique in representing two-electron integrals in a compact form.« less

Stain susceptibility of composite and ceramic CAD/CAM blocks versus direct resin composites with different resinous matrices.

PubMed

Alharbi, Amal; Ardu, Stefano; Bortolotto, Tissiana; Krejci, Ivo

2017-04-01

To evaluate the stain susceptibility of CAD/CAM blocks and direct composite after long term exposure to various staining agents. 40 disk-shaped samples were fabricated from each of nine materials; six CAD/CAM (Vitablocs Mark II, Paradigm MZ100, Experimental Vita Hybrid Ceramic, Vita Enamic, Experimental Kerr and Lava Ultimate) and three direct composites (Filtek Supreme, Venus Diamond and Filtek Silorane). Samples were randomly divided into five groups (n = 8) according to different staining solutions (distilled water, tea, red wine, coffee and artificial saliva). Initial L*a*b* values were assessed using a calibrated digital spectrophotometer. Specimens were immersed in staining solutions and stored in an incubator at 37 °C for 120 days. L*a*b* values were assessed again and color change (∆E) was calculated as difference between recorded L*a*b* values. ANOVA, and Duncan test were used to identify differences between groups (α = 0.05). Significant differences in ∆E values were detected between materials (p = 0.000). Among all staining solutions, the highest ∆E value was observed with red wine. The new CAD/CAM blocks (Vita Enamic, Vita Hybrid Ceramic and Lava Ultimate) showed the highest resistance to staining compared to the MZ100 composite resin blocks. Filtek Silorane, a direct composite, showed high stain resistance values compared to CAD/CAM materials and other direct composites. Ceramic and composite CAD/CAM blocks had lower staining susceptibility than methacrylate based direct composite. Staining susceptibility of the new resin based CAD/CAM materials Vita Enamic and Lava Ultimate was comparable to feldspathic ceramic blocks (Vitablocs Mark II). Filtek Silorane showed promising results that were comparable to some CAD/CAM blocks.

Summer Proceedings 2016: The Center for Computing Research at Sandia National Laboratories

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

Carleton, James Brian; Parks, Michael L.

Solving sparse linear systems from the discretization of elliptic partial differential equations (PDEs) is an important building block in many engineering applications. Sparse direct solvers can solve general linear systems, but are usually slower and use much more memory than effective iterative solvers. To overcome these two disadvantages, a hierarchical solver (LoRaSp) based on H2-matrices was introduced in [22]. Here, we have developed a parallel version of the algorithm in LoRaSp to solve large sparse matrices on distributed memory machines. On a single processor, the factorization time of our parallel solver scales almost linearly with the problem size for three-dimensionalmore » problems, as opposed to the quadratic scalability of many existing sparse direct solvers. Moreover, our solver leads to almost constant numbers of iterations, when used as a preconditioner for Poisson problems. On more than one processor, our algorithm has significant speedups compared to sequential runs. With this parallel algorithm, we are able to solve large problems much faster than many existing packages as demonstrated by the numerical experiments.« less

A structure preserving Lanczos algorithm for computing the optical absorption spectrum

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

Shao, Meiyue; Jornada, Felipe H. da; Lin, Lin

2016-11-16

We present a new structure preserving Lanczos algorithm for approximating the optical absorption spectrum in the context of solving full Bethe-Salpeter equation without Tamm-Dancoff approximation. The new algorithm is based on a structure preserving Lanczos procedure, which exploits the special block structure of Bethe-Salpeter Hamiltonian matrices. A recently developed technique of generalized averaged Gauss quadrature is incorporated to accelerate the convergence. We also establish the connection between our structure preserving Lanczos procedure with several existing Lanczos procedures developed in different contexts. Numerical examples are presented to demonstrate the effectiveness of our Lanczos algorithm.

Couple of the Variational Iteration Method and Fractional-Order Legendre Functions Method for Fractional Differential Equations

PubMed Central

Song, Junqiang; Leng, Hongze; Lu, Fengshun

2014-01-01

We present a new numerical method to get the approximate solutions of fractional differential equations. A new operational matrix of integration for fractional-order Legendre functions (FLFs) is first derived. Then a modified variational iteration formula which can avoid “noise terms” is constructed. Finally a numerical method based on variational iteration method (VIM) and FLFs is developed for fractional differential equations (FDEs). Block-pulse functions (BPFs) are used to calculate the FLFs coefficient matrices of the nonlinear terms. Five examples are discussed to demonstrate the validity and applicability of the technique. PMID:24511303

Maximum Entropy/Optimal Projection Design Synthesis for Decentralized Control of Large Space Structures

DTIC Science & Technology

1988-05-01

M 21 M2 I SI M1l[11 II1211 - - - M= II 2+111 I11-211 NONNEGATIVE CONE ORDERING Figure 25. The Matrix Majorant Is a Bound for the Hatrix Block Norm...the with respect to the cone of nonnegative -definite matrices. inequality (1.5) by the r x r nonnegative matrix equation Indeed, the majorant bound...t) eA-) e ea ’ A rT(" 3 ds, t> O , ju E [0 , 1] 0 J(G, )= tr (0,(6)R,) which is monotonically increasing in the nonnegative -definite G , cone with

Toughening of PMR composites by gradient semi-interpenetrating networks

NASA Technical Reports Server (NTRS)

Johnston, N. J.; Srinivasan, K.; Peter, R. H.

1992-01-01

The toughening of the PMR-15 and LARC RP-46 high temperature thermosetting polyimides is presently attempted through the construction of a semiinterpenetrating network at ply interfaces through the use of the Matrimid 5218 thermoplastic polyimide powder, whose 315-320 glass transition temperature is compatible with the PMR matrices. The 60 vol pct fiber composites thus prepared for the two resins, with and without toughening, were comprehensively characterized in flexure, tension, intralaminar and short beam shear, compression and quasi-isotropic short-block compression, as well as modes I and II interlaminar fracture toughness and compression after impact.

Markov Chain Analysis of Musical Dice Games

NASA Astrophysics Data System (ADS)

Volchenkov, D.; Dawin, J. R.

2012-07-01

A system for using dice to compose music randomly is known as the musical dice game. The discrete time MIDI models of 804 pieces of classical music written by 29 composers have been encoded into the transition matrices and studied by Markov chains. Contrary to human languages, entropy dominates over redundancy, in the musical dice games based on the compositions of classical music. The maximum complexity is achieved on the blocks consisting of just a few notes (8 notes, for the musical dice games generated over Bach's compositions). First passage times to notes can be used to resolve tonality and feature a composer.

Musical Markov Chains

NASA Astrophysics Data System (ADS)

Volchenkov, Dima; Dawin, Jean René

A system for using dice to compose music randomly is known as the musical dice game. The discrete time MIDI models of 804 pieces of classical music written by 29 composers have been encoded into the transition matrices and studied by Markov chains. Contrary to human languages, entropy dominates over redundancy, in the musical dice games based on the compositions of classical music. The maximum complexity is achieved on the blocks consisting of just a few notes (8 notes, for the musical dice games generated over Bach's compositions). First passage times to notes can be used to resolve tonality and feature a composer.

An algorithm for automatic reduction of complex signal flow graphs

NASA Technical Reports Server (NTRS)

Young, K. R.; Hoberock, L. L.; Thompson, J. G.

1976-01-01

A computer algorithm is developed that provides efficient means to compute transmittances directly from a signal flow graph or a block diagram. Signal flow graphs are cast as directed graphs described by adjacency matrices. Nonsearch computation, designed for compilers without symbolic capability, is used to identify all arcs that are members of simple cycles for use with Mason's gain formula. The routine does not require the visual acumen of an interpreter to reduce the topology of the graph, and it is particularly useful for analyzing control systems described for computer analyses by means of interactive graphics.

A diagonal implicit scheme for computing flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Eberhardt, Scott; Imlay, Scott

1990-01-01

A new algorithm for solving steady, finite-rate chemistry, flow problems is presented. The new scheme eliminates the expense of inverting large block matrices that arise when species conservation equations are introduced. The source Jacobian matrix is replaced by a diagonal matrix which is tailored to account for the fastest reactions in the chemical system. A point-implicit procedure is discussed and then the algorithm is included into the LU-SGS scheme. Solutions are presented for hypervelocity reentry and Hydrogen-Oxygen combustion. For the LU-SGS scheme a CFL number in excess of 10,000 has been achieved.

On substructuring algorithms and solution techniques for the numerical approximation of partial differential equations

NASA Technical Reports Server (NTRS)

Gunzburger, M. D.; Nicolaides, R. A.

1986-01-01

Substructuring methods are in common use in mechanics problems where typically the associated linear systems of algebraic equations are positive definite. Here these methods are extended to problems which lead to nonpositive definite, nonsymmetric matrices. The extension is based on an algorithm which carries out the block Gauss elimination procedure without the need for interchanges even when a pivot matrix is singular. Examples are provided wherein the method is used in connection with finite element solutions of the stationary Stokes equations and the Helmholtz equation, and dual methods for second-order elliptic equations.

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

NASA Technical Reports Server (NTRS)

Zubair, Mohammad; Nielsen, Eric; Luitjens, Justin; Hammond, Dana

2016-01-01

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments.

PubMed

Ajawatanawong, Pravech; Atkinson, Gemma C; Watson-Haigh, Nathan S; Mackenzie, Bryony; Baldauf, Sandra L

2012-07-01

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Parallel algorithms for boundary value problems

NASA Technical Reports Server (NTRS)

Lin, Avi

1990-01-01

A general approach to solve boundary value problems numerically in a parallel environment is discussed. The basic algorithm consists of two steps: the local step where all the P available processors work in parallel, and the global step where one processor solves a tridiagonal linear system of the order P. The main advantages of this approach are two fold. First, this suggested approach is very flexible, especially in the local step and thus the algorithm can be used with any number of processors and with any of the SIMD or MIMD machines. Secondly, the communication complexity is very small and thus can be used as easily with shared memory machines. Several examples for using this strategy are discussed.

Parallel language constructs for tensor product computations on loosely coupled architectures

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Vanrosendale, John

1989-01-01

Distributed memory architectures offer high levels of performance and flexibility, but have proven awkard to program. Current languages for nonshared memory architectures provide a relatively low level programming environment, and are poorly suited to modular programming, and to the construction of libraries. A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. Tensor product array computations are focused on along with a simple but important class of numerical algorithms. The problem of programming 1-D kernal routines is focused on first, such as parallel tridiagonal solvers, and then how such parallel kernels can be combined to form parallel tensor product algorithms is examined.

Systems of Inhomogeneous Linear Equations

NASA Astrophysics Data System (ADS)

Scherer, Philipp O. J.

Many problems in physics and especially computational physics involve systems of linear equations which arise e.g. from linearization of a general nonlinear problem or from discretization of differential equations. If the dimension of the system is not too large standard methods like Gaussian elimination or QR decomposition are sufficient. Systems with a tridiagonal matrix are important for cubic spline interpolation and numerical second derivatives. They can be solved very efficiently with a specialized Gaussian elimination method. Practical applications often involve very large dimensions and require iterative methods. Convergence of Jacobi and Gauss-Seidel methods is slow and can be improved by relaxation or over-relaxation. An alternative for large systems is the method of conjugate gradients.

Efficient numerical simulation of an electrothermal de-icer pad

NASA Technical Reports Server (NTRS)

Roelke, R. J.; Keith, T. G., Jr.; De Witt, K. J.; Wright, W. B.

1987-01-01

In this paper, a new approach to calculate the transient thermal behavior of an iced electrothermal de-icer pad was developed. The method of splines was used to obtain the temperature distribution within the layered pad. Splines were used in order to create a tridiagonal system of equations that could be directly solved by Gauss elimination. The Stefan problem was solved using the enthalpy method along with a recent implicit technique. Only one to three iterations were needed to locate the melt front during any time step. Computational times were shown to be greatly reduced over those of an existing one dimensional procedure without any reduction in accuracy; the curent technique was more than 10 times faster.

Gegenbauer-solvable quantum chain model

NASA Astrophysics Data System (ADS)

Znojil, Miloslav

2010-11-01

An N-level quantum model is proposed in which the energies are represented by an N-plet of zeros of a suitable classical orthogonal polynomial. The family of Gegenbauer polynomials G(n,a,x) is selected for illustrative purposes. The main obstacle lies in the non-Hermiticity (aka crypto-Hermiticity) of Hamiltonians H≠H†. We managed to (i) start from elementary secular equation G(N,a,En)=0, (ii) keep our H, in the nearest-neighbor-interaction spirit, tridiagonal, (iii) render it Hermitian in an ad hoc, nonunique Hilbert space endowed with metric Θ≠I, (iv) construct eligible metrics in closed forms ordered by increasing nondiagonality, and (v) interpret the model as a smeared N-site lattice.

Liquid chromatography tandem-mass spectrometry (LC-MS/MS) and dried blood spot sampling applied to pharmacokinetics studies in animals: Correlation of classic and block design.

PubMed

Baldo, Matías N; Angeli, Emmanuel; Gareis, Natalia C; Hunzicker, Gabriel A; Murguía, Marcelo C; Ortega, Hugo H; Hein, Gustavo J

2018-04-01

A relative bioavailability study (RBA) of two phenytoin (PHT) formulations was conducted in rabbits, in order to compare the results obtained from different matrices (plasma and blood from dried blood spot (DBS) sampling) and different experimental designs (classic and block). The method was developed by liquid chromatography tandem-mass spectrometry (LC-MS/MS) in plasma and blood samples. The different sample preparation techniques, plasma protein precipitation and DBS, were validated according to international requirements. The analytical method was validated with ranges 0.20-50.80 and 0.12-20.32 µg ml -1 , r > 0.999 for plasma and blood, respectively. Accuracy and precision were within acceptance criteria for bioanalytical assay validation (< 15 for bias and CV% and < 20 for limit of quantification (LOQ)). PHT showed long-term stability, both for plasma and blood, and under refrigerated and room temperature conditions. Haematocrit values were measured during the validation process and RBA study. Finally, the pharmacokinetic parameters (C max , T max and AUC 0-t ) obtained from the RBA study were tested. Results were highly comparable for matrices and experimental designs. A matrix correlation higher than 0.975 and a ratio of (PHT blood) = 1.158 (PHT plasma) were obtained. The results obtained herein show that the use of classic experimental design and DBS sampling for animal pharmacokinetic studies should be encouraged as they could help to prevent the use of a large number of animals and also animal euthanasia. Finally, the combination of DBS sampling with LC-MS/MS technology showed to be an excellent tool not only for therapeutic drug monitoring but also for RBA studies.

Deformation and Metasomatic Evolution at the Subduction Plate Interface As Viewed from Study of HP/UHP Metamorphic Rocks

NASA Astrophysics Data System (ADS)

Bebout, G. E.; Penniston-Dorland, S.

2014-12-01

We provide a view of lithologic makeup, deformation, and fluid-rock interaction along the deep forearc to subarc plate interface, based on insights gained from study of HP/UHP metamorphic rocks. Exposures of plate-boundary shear zones on which we base our perspective represent 30-80 km depths and are on Catalina Island and at Monviso, Syros, and New Caledonia. Each contains highly deformed zones with schistose matrix, commonly with a large ultramafic component, containing bodies of less deformed mafic, sedimentary, and ultramafic rocks. These "blocks" have varying geometries, are up to km-scale, and can preserve disparate P-T histories reflecting dynamics of incorporation and entrainment. Sheared matrices contain high-variance, hydrous mineral assemblages in some cases resembling metasomatic zones ("rinds") at block-matrix contacts, and rinds and matrices have homogenized isotopic compositions reflecting extensive fluid-rock interaction. Shearing and related physical juxtaposition of disparate metasomatic rocks can result in mixed or 'hybrid' chemical compositions. The chlorite-, talc-, and amphibole-rich schists developed by these processes can stabilize H2O to great depth and influence its cycling. Fluids (hydrous fluids, silicate melts) released within slabs necessarily interact with highly deformed, lithologically hybridized zones at the plate interface as they ascend to potentially enter mantle wedges. Fluids bearing chemical/isotopic signatures of hybrid rocks appear capable of producing arc magma compositions interpreted as reflecting multiple, chemically distinct fluids sources. Geophysical signatures of these rheologically weak zones are equivocal but many recognize the presence of zones of low seismic velocity at/near the top of slabs and attribute them to hydrated rocks. Whether rocks from this interface buoyantly ascend into mantle wedges, indicated in some theoretical models, remains largely untested by field and geophysical observations.

Field Analysis of Polychlorinated Biphenyls (PCBs) in Soil Using Solid-Phase Microextraction (SPME) and a Portable Gas Chromatography-Mass Spectrometry System.

PubMed

Zhang, Mengliang; Kruse, Natalie A; Bowman, Jennifer R; Jackson, Glen P

2016-05-01

An expedited field analysis method was developed for the determination of polychlorinated biphenyls (PCBs) in soil matrices using a portable gas chromatography-mass spectrometry (GC-MS) instrument. Soil samples of approximately 0.5 g were measured with a portable scale and PCBs were extracted by headspace solid-phase microextraction (SPME) with a 100 µm polydimethylsiloxane (PDMS) fiber. Two milliliters of 0.2 M potassium permanganate and 0.5 mL of 6 M sulfuric acid solution were added to the soil matrices to facilitate the extraction of PCBs. The extraction was performed for 30 min at 100 ℃ in a portable heating block that was powered by a portable generator. The portable GC-MS instrument took less than 6 min per analysis and ran off an internal battery and helium cylinder. Six commercial PCB mixtures, Aroclor 1016, 1221, 1232, 1242, 1248, 1254, and 1260, could be classified based on the GC chromatograms and mass spectra. The detection limit of this method for Aroclor 1260 in soil matrices is approximately 10 ppm, which is sufficient for guiding remediation efforts in contaminated sites. This method was applicable to the on-site analysis of PCBs with a total analysis time of 37 min per sample. However, the total analysis time could be improved to less than 7 min per sample by conducting the rate-limiting extraction step for different samples in parallel. © The Author(s) 2016.

Stability and stabilisation of a class of networked dynamic systems

NASA Astrophysics Data System (ADS)

Liu, H. B.; Wang, D. Q.

2018-04-01

We investigate the stability and stabilisation of a linear time invariant networked heterogeneous system with arbitrarily connected subsystems. A new linear matrix inequality based sufficient and necessary condition for the stability is derived, based on which the stabilisation is provided. The obtained conditions efficiently utilise the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, a sufficient condition only dependent on each individual subsystem is also presented for the stabilisation of the networked systems with a large scale. Numerical simulations show that these conditions are computationally valid in the analysis and synthesis of a large-scale networked system.

Time delay estimation using new spectral and adaptive filtering methods with applications to underwater target detection

NASA Astrophysics Data System (ADS)

Hasan, Mohammed A.

1997-11-01

In this dissertation, we present several novel approaches for detection and identification of targets of arbitrary shapes from the acoustic backscattered data and using the incident waveform. This problem is formulated as time- delay estimation and sinusoidal frequency estimation problems which both have applications in many other important areas in signal processing. Solving time-delay estimation problem allows the identification of the specular components in the backscattered signal from elastic and non-elastic targets. Thus, accurate estimation of these time delays would help in determining the existence of certain clues for detecting targets. Several new methods for solving these two problems in the time, frequency and wavelet domains are developed. In the time domain, a new block fast transversal filter (BFTF) is proposed for a fast implementation of the least squares (LS) method. This BFTF algorithm is derived by using data-related constrained block-LS cost function to guarantee global optimality. The new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data and thus it is computationally very efficient compared with other LS- based schemes. Additionally, the tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. The effectiveness of this algorithm is tested on several underwater acoustic backscattered data for elastic targets and non-elastic (cement chunk) objects. In the frequency domain, the time-delay estimation problem is converted to a sinusoidal frequency estimation problem by using the discrete Fourier transform. Then, the lagged sample covariance matrices of the resulting signal are computed and studied in terms of their eigen- structure. These matrices are shown to be robust and effective in extracting bases for the signal and noise subspaces. New MUSIC and matrix pencil-based methods are derived these subspaces. The effectiveness of the method is demonstrated on the problem of detection of multiple specular components in the acoustic backscattered data. Finally, a method for the estimation of time delays using wavelet decomposition is derived. The sub-band adaptive filtering uses discrete wavelet transform for multi- resolution or sub-band decomposition. Joint time delay estimation for identifying multi-specular components and subsequent adaptive filtering processes are performed on the signal in each sub-band. This would provide multiple 'look' of the signal at different resolution scale which results in more accurate estimates for delays associated with the specular components. Simulation results on the simulated and real shallow water data are provided which show the promise of this new scheme for target detection in a heavy cluttered environment.

Keratinocyte-driven contraction of reconstructed human skin.

PubMed

Chakrabarty, K H; Heaton, M; Dalley, A J; Dawson, R A; Freedlander, E; Khaw, P T; Mac Neil, S

2001-01-01

We have previously reported that reconstructed human skin, using deepidermized acellular sterilized dermis and allogeneic keratinocytes and fibroblasts, significantly contracts in vitro. Contracture of split skin grafts in burns injuries remains a serious problem and this in vitro model provides an opportunity to study keratinocyte/mesenchymal cell interactions and cell interactions with extracted normal human dermis. The aim of this study was to investigate the nature of this in vitro contraction and explore several approaches to prevent or reduce contraction. Three different methodologies for sterilization of the dermal matrix were examined: glycerol, ethylene oxide and a combination of glycerol and ethylene oxide. While the nature of the sterilization technique influenced the extent of contraction and thinner dermal matrices contracted proportionately more than thicker matrices, in all cases contraction was driven by the keratinocytes with relatively little influence from the fibroblasts. The contraction of the underlying dermis did not represent any change in tissue mass but rather a reorganization of the dermis which was rapidly reversed (within minutes) when the epidermal layer was removed. Pharmacological approaches to block contraction showed forskolin and mannose-6-phosphate to be ineffective and ascorbic acid-2-phosphate to exacerbate contraction. However, Galardin, a matrix metalloproteinase inhibitor and keratinocyte conditioned media, both inhibited contraction.

Multiple-image encryption based on double random phase encoding and compressive sensing by using a measurement array preprocessed with orthogonal-basis matrices

NASA Astrophysics Data System (ADS)

Zhang, Luozhi; Zhou, Yuanyuan; Huo, Dongming; Li, Jinxi; Zhou, Xin

2018-09-01

A method is presented for multiple-image encryption by using the combination of orthogonal encoding and compressive sensing based on double random phase encoding. As an original thought in optical encryption, it is demonstrated theoretically and carried out by using the orthogonal-basis matrices to build a modified measurement array, being projected onto the images. In this method, all the images can be compressed in parallel into a stochastic signal and be diffused to be a stationary white noise. Meanwhile, each single-image can be separately reestablished by adopting a proper decryption key combination through the block-reconstruction rather than the entire-rebuilt, for its costs of data and decryption time are greatly decreased, which may be promising both in multi-user multiplexing and huge-image encryption/decryption. Besides, the security of this method is characterized by using the bit-length of key, and the parallelism is investigated as well. The simulations and discussions are also made on the effects of decryption as well as the correlation coefficient by using a series of sampling rates, occlusion attacks, keys with various error rates, etc.

Rab-coupling protein coordinates recycling of alpha5beta1 integrin and EGFR1 to promote cell migration in 3D microenvironments.

PubMed

Caswell, Patrick T; Chan, May; Lindsay, Andrew J; McCaffrey, Mary W; Boettiger, David; Norman, Jim C

2008-10-06

Here we show that blocking the adhesive function of alphavbeta3 integrin with soluble RGD ligands, such as osteopontin or cilengitide, promoted association of Rab-coupling protein (RCP) with alpha5beta1 integrin and drove RCP-dependent recycling of alpha5beta1 to the plasma membrane and its mobilization to dynamic ruffling protrusions at the cell front. These RCP-driven changes in alpha5beta1 trafficking led to acquisition of rapid/random movement on two-dimensional substrates and to a marked increase in fibronectin-dependent migration of tumor cells into three-dimensional matrices. Recycling of alpha5beta1 integrin did not affect its regulation or ability to form adhesive bonds with substrate fibronectin. Instead, alpha5beta1 controlled the association of EGFR1 with RCP to promote the coordinate recycling of these two receptors. This modified signaling downstream of EGFR1 to increase its autophosphorylation and activation of the proinvasive kinase PKB/Akt. We conclude that RCP provides a scaffold that promotes the physical association and coordinate trafficking of alpha5beta1 and EGFR1 and that this drives migration of tumor cells into three-dimensional matrices.

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

Znojil, Miloslav

An N-level quantum model is proposed in which the energies are represented by an N-plet of zeros of a suitable classical orthogonal polynomial. The family of Gegenbauer polynomials G(n,a,x) is selected for illustrative purposes. The main obstacle lies in the non-Hermiticity (aka crypto-Hermiticity) of Hamiltonians H{ne}H{sup {dagger}.} We managed to (i) start from elementary secular equation G(N,a,E{sub n})=0, (ii) keep our H, in the nearest-neighbor-interaction spirit, tridiagonal, (iii) render it Hermitian in an ad hoc, nonunique Hilbert space endowed with metric {Theta}{ne}I, (iv) construct eligible metrics in closed forms ordered by increasing nondiagonality, and (v) interpret the model as amore » smeared N-site lattice.« less

Introducing a new family of short-range potentials and their numerical solutions using the asymptotic iteration method

NASA Astrophysics Data System (ADS)

Assi, I. A.; Sous, A. J.

2018-05-01

The goal of this work is to derive a new class of short-range potentials that could have a wide range of physical applications, specially in molecular physics. The tridiagonal representation approach has been developed beyond its limitations to produce new potentials by requiring the representation of the Schrödinger wave operator to be multidiagonal and symmetric. This produces a family of Hulthén potentials that has a specific structure, as mentioned in the introduction. As an example, we have solved the nonrelativistic wave equation for the new four-parameter short-range screening potential numerically using the asymptotic iteration method, where we tabulated the eigenvalues for both s -wave and arbitrary l -wave cases in tables.

Modular and Orthogonal Synthesis of Hybrid Polymers and Networks

PubMed Central

Liu, Shuang; Dicker, Kevin T.; Jia, Xinqiao

2015-01-01

Biomaterials scientists strive to develop polymeric materials with distinct chemical make-up, complex molecular architectures, robust mechanical properties and defined biological functions by drawing inspirations from biological systems. Salient features of biological designs include (1) repetitive presentation of basic motifs; and (2) efficient integration of diverse building blocks. Thus, an appealing approach to biomaterials synthesis is to combine synthetic and natural building blocks in a modular fashion employing novel chemical methods. Over the past decade, orthogonal chemistries have become powerful enabling tools for the modular synthesis of advanced biomaterials. These reactions require building blocks with complementary functionalities, occur under mild conditions in the presence of biological molecules and living cells and proceed with high yield and exceptional selectivity. These chemistries have facilitated the construction of complex polymers and networks in a step-growth fashion, allowing facile modulation of materials properties by simple variations of the building blocks. In this review, we first summarize features of several types of orthogonal chemistries. We then discuss recent progress in the synthesis of step growth linear polymers, dendrimers and networks that find application in drug delivery, 3D cell culture and tissue engineering. Overall, orthogonal reactions and modulular synthesis have not only minimized the steps needed for the desired chemical transformations but also maximized the diversity and functionality of the final products. The modular nature of the design, combined with the potential synergistic effect of the hybrid system, will likely result in novel hydrogel matrices with robust structures and defined functions. PMID:25572255

Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems.

PubMed

Ravishankar, Saiprasad; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-12-01

The sparsity of signals in a transform domain or dictionary has been exploited in applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis dictionaries has shown promise compared to analytical dictionary models. However, dictionary learning problems are typically non-convex and NP-hard, and the usual alternating minimization approaches for these problems are often computationally expensive, with the computations dominated by the NP-hard synthesis sparse coding step. This paper exploits the ideas that drive algorithms such as K-SVD, and investigates in detail efficient methods for aggregate sparsity penalized dictionary learning by first approximating the data with a sum of sparse rank-one matrices (outer products) and then using a block coordinate descent approach to estimate the unknowns. The resulting block coordinate descent algorithms involve efficient closed-form solutions. Furthermore, we consider the problem of dictionary-blind image reconstruction, and propose novel and efficient algorithms for adaptive image reconstruction using block coordinate descent and sum of outer products methodologies. We provide a convergence study of the algorithms for dictionary learning and dictionary-blind image reconstruction. Our numerical experiments show the promising performance and speedups provided by the proposed methods over previous schemes in sparse data representation and compressed sensing-based image reconstruction.

Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems

PubMed Central

Ravishankar, Saiprasad; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

The sparsity of signals in a transform domain or dictionary has been exploited in applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis dictionaries has shown promise compared to analytical dictionary models. However, dictionary learning problems are typically non-convex and NP-hard, and the usual alternating minimization approaches for these problems are often computationally expensive, with the computations dominated by the NP-hard synthesis sparse coding step. This paper exploits the ideas that drive algorithms such as K-SVD, and investigates in detail efficient methods for aggregate sparsity penalized dictionary learning by first approximating the data with a sum of sparse rank-one matrices (outer products) and then using a block coordinate descent approach to estimate the unknowns. The resulting block coordinate descent algorithms involve efficient closed-form solutions. Furthermore, we consider the problem of dictionary-blind image reconstruction, and propose novel and efficient algorithms for adaptive image reconstruction using block coordinate descent and sum of outer products methodologies. We provide a convergence study of the algorithms for dictionary learning and dictionary-blind image reconstruction. Our numerical experiments show the promising performance and speedups provided by the proposed methods over previous schemes in sparse data representation and compressed sensing-based image reconstruction. PMID:29376111

Fast iterative solution of the Bethe-Salpeter eigenvalue problem using low-rank and QTT tensor approximation

NASA Astrophysics Data System (ADS)

Benner, Peter; Dolgov, Sergey; Khoromskaia, Venera; Khoromskij, Boris N.

2017-04-01

In this paper, we propose and study two approaches to approximate the solution of the Bethe-Salpeter equation (BSE) by using structured iterative eigenvalue solvers. Both approaches are based on the reduced basis method and low-rank factorizations of the generating matrices. We also propose to represent the static screen interaction part in the BSE matrix by a small active sub-block, with a size balancing the storage for rank-structured representations of other matrix blocks. We demonstrate by various numerical tests that the combination of the diagonal plus low-rank plus reduced-block approximation exhibits higher precision with low numerical cost, providing as well a distinct two-sided error estimate for the smallest eigenvalues of the Bethe-Salpeter operator. The complexity is reduced to O (Nb2) in the size of the atomic orbitals basis set, Nb, instead of the practically intractable O (Nb6) scaling for the direct diagonalization. In the second approach, we apply the quantized-TT (QTT) tensor representation to both, the long eigenvectors and the column vectors in the rank-structured BSE matrix blocks, and combine this with the ALS-type iteration in block QTT format. The QTT-rank of the matrix entities possesses almost the same magnitude as the number of occupied orbitals in the molecular systems, No

An overview of NSPCG: A nonsymmetric preconditioned conjugate gradient package

NASA Astrophysics Data System (ADS)

Oppe, Thomas C.; Joubert, Wayne D.; Kincaid, David R.

1989-05-01

The most recent research-oriented software package developed as part of the ITPACK Project is called "NSPCG" since it contains many nonsymmetric preconditioned conjugate gradient procedures. It is designed to solve large sparse systems of linear algebraic equations by a variety of different iterative methods. One of the main purposes for the development of the package is to provide a common modular structure for research on iterative methods for nonsymmetric matrices. Another purpose for the development of the package is to investigate the suitability of several iterative methods for vector computers. Since the vectorizability of an iterative method depends greatly on the matrix structure, NSPCG allows great flexibility in the operator representation. The coefficient matrix can be passed in one of several different matrix data storage schemes. These sparse data formats allow matrices with a wide range of structures from highly structured ones such as those with all nonzeros along a relatively small number of diagonals to completely unstructured sparse matrices. Alternatively, the package allows the user to call the accelerators directly with user-supplied routines for performing certain matrix operations. In this case, one can use the data format from an application program and not be required to copy the matrix into one of the package formats. This is particularly advantageous when memory space is limited. Some of the basic preconditioners that are available are point methods such as Jacobi, Incomplete LU Decomposition and Symmetric Successive Overrelaxation as well as block and multicolor preconditioners. The user can select from a large collection of accelerators such as Conjugate Gradient (CG), Chebyshev (SI, for semi-iterative), Generalized Minimal Residual (GMRES), Biconjugate Gradient Squared (BCGS) and many others. The package is modular so that almost any accelerator can be used with almost any preconditioner.

Lecture Notes on Multigrid Methods

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

Vassilevski, P S

The Lecture Notes are primarily based on a sequence of lectures given by the author while been a Fulbright scholar at 'St. Kliment Ohridski' University of Sofia, Sofia, Bulgaria during the winter semester of 2009-2010 academic year. The notes are somewhat expanded version of the actual one semester class he taught there. The material covered is slightly modified and adapted version of similar topics covered in the author's monograph 'Multilevel Block-Factorization Preconditioners' published in 2008 by Springer. The author tried to keep the notes as self-contained as possible. That is why the lecture notes begin with some basic introductory matrix-vectormore » linear algebra, numerical PDEs (finite element) facts emphasizing the relations between functions in finite dimensional spaces and their coefficient vectors and respective norms. Then, some additional facts on the implementation of finite elements based on relation tables using the popular compressed sparse row (CSR) format are given. Also, typical condition number estimates of stiffness and mass matrices, the global matrix assembly from local element matrices are given as well. Finally, some basic introductory facts about stationary iterative methods, such as Gauss-Seidel and its symmetrized version are presented. The introductory material ends up with the smoothing property of the classical iterative methods and the main definition of two-grid iterative methods. From here on, the second part of the notes begins which deals with the various aspects of the principal TG and the numerous versions of the MG cycles. At the end, in part III, we briefly introduce algebraic versions of MG referred to as AMG, focusing on classes of AMG specialized for finite element matrices.« less

Encapsulated and Monolithic Resonant Structures for Laser Applications

DTIC Science & Technology

2014-11-18

large, and is better handled in matrices of the form ,y z y r x d j dz   K u u ε s where ,yK ,zu ,yu ,rε and xs are defined in (2.9) [41]. 18...unknowns: ,xu ,yu , xs and .ys The resulting equations can be written in block matrix form. 19 1 1 1 1 , x x x r y r x r x y y y r y r y r x d dz...ALD cycle. The Al2O3 deposition recipe yields a deposition rate of 0.122 nm per cycle. A 350 nm deposition is used to nearly fill the etched trenches

A C++11 implementation of arbitrary-rank tensors for high-performance computing

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.

2014-06-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

A C++11 implementation of arbitrary-rank tensors for high-performance computing

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.

2014-11-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

An accelerated lambda iteration method for multilevel radiative transfer. I - Non-overlapping lines with background continuum

NASA Technical Reports Server (NTRS)

Rybicki, G. B.; Hummer, D. G.

1991-01-01

A method is presented for solving multilevel transfer problems when nonoverlapping lines and background continuum are present and active continuum transfer is absent. An approximate lambda operator is employed to derive linear, 'preconditioned', statistical-equilibrium equations. A method is described for finding the diagonal elements of the 'true' numerical lambda operator, and therefore for obtaining the coefficients of the equations. Iterations of the preconditioned equations, in conjunction with the transfer equation's formal solution, are used to solve linear equations. Some multilevel problems are considered, including an eleven-level neutral helium atom. Diagonal and tridiagonal approximate lambda operators are utilized in the problems to examine the convergence properties of the method, and it is found to be effective for the line transfer problems.

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

Pratap, Surender; Sarkar, Niladri, E-mail: niladri@pilani.bits-pilani.ac.in

Self-Consistent Quantum Method using Schrodinger-Poisson equations have been used for determining the Channel electron density of Nano-Scale MOSFETs for 6nm and 9nm thick channels. The 6nm thick MOSFET show the peak of the electron density at the middle where as the 9nm thick MOSFET shows the accumulation of the electrons at the oxide/semiconductor interface. The electron density in the channel is obtained from the diagonal elements of the density matrix; [ρ]=[1/(1+exp(β(H − μ)))] A Tridiagonal Hamiltonian Matrix [H] is constructed for the oxide/channel/oxide 1D structure for the dual gate MOSFET. This structure is discretized and Finite-Difference method is used formore » constructing the matrix equation. The comparison of these results which are obtained by Quantum methods are done with Semi-Classical methods.« less

Sequential time interleaved random equivalent sampling for repetitive signal.

PubMed

Zhao, Yijiu; Liu, Jingjing

2016-12-01

Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.

Gels from soft hairy nanoparticles in polymeric matrices

NASA Astrophysics Data System (ADS)

Vlassopoulos, Dimitris

2013-03-01

Hairy particles represent a huge class of soft colloids with tunable interactions and properties. Advances in synthetic chemistry have enabled obtaining well-characterized such systems for specific needs. In this talk we present two model hairy soft particles with diameters of the order of tens of nanometers, star polymers and polymerically grafted spherical particles. In particular, we discuss design strategies for dispersing them in polymeric matrices and eventually creating and breaking gels. Control parameters are the matrix molar mass, the grafting density (or functionality) and the size of the grafts (or arms). The linear viscoelastic properties and slow time evolution of the gels are examined in view of the existing knowledge from colloidal gels consisting of micron-sized particles, and compared. In the case of stars we start from a concentrated glassy suspension in molecular solvent and add homopolymer at increasing concentration, and as a result of the induced osmotic pressure the stars shrink and a depletion gel is formed. For the grafted colloidal particles, they are added at low concentration to a polymer matrix, and it has been shown that under certain conditions the anisotropy of interactions gives rise to network formation. We then focus on the nonlinear rheological response and in particular the effect of shear flow in inducing a solid to liquid transition. Our studies show that the yielding process is gradual and shares many common features with that of flocculated colloidal suspensions, irrespectively of the shape of the building block of the gel. Whereas shear can melt such a gel, it cannot break it into its constituent blocks and hence fully disperse the hairy nanoparticles. On the other hand, the hairy particles are intrinsically hybrid. We show how this important feature is reflected on the heating of the gels. In that case, the mismatch of thermal expansion coefficients of core and shell appears to play a role on the particle response as it imposes and internal strain on the particle, which in turn changes the shell conformation and under some conditions can lead to thermal melting of the gel. These alternative avenues for manipulating the gel-to-liquid transition have potential implications in directing the properties of hairy nanoparticles and their assemblies in viscoelastic matrices. Parts of this work reflect collaboration with D. Truzzolillo (FORTH), J. F. Moll and S. K.Kumar (Columbia). R. H. Colby (Penn State), M. Gauthier (Waterloo) and B. C. Benicewicz (Univ. South Carolina).

An Analysis of the Max-Min Texture Measure.

DTIC Science & Technology

1982-01-01

PANC 33 D2 Confusion Matrices for Scene A, IR 34 D3 Confusion Matrices for Scene B, PANC 35 D4 Confusion Matrices for Scene B, IR 36 D5 Confusion...Matrices for Scene C, PANC 37 D6 Confusion Matrices for Scene C, IR 38 D7 Confusion Matrices for Scene E, PANC 39 D8 Confusion Matrices for Scene E, IR 40...D9 Confusion Matrices for Scene H, PANC 41 DIO Confusion Matrices for Scene H, JR 42 3 .D 10CnuinMtie o cn ,IR4 AN ANALYSIS OF THE MAX-MIN TEXTURE

CoCoMac 2.0 and the future of tract-tracing databases

PubMed Central

Bakker, Rembrandt; Wachtler, Thomas; Diesmann, Markus

2012-01-01

The CoCoMac database contains the results of several hundred published axonal tract-tracing studies in the macaque monkey brain. The combined results are used for constructing the macaque macro-connectome. Here we discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two online resources that provide full access to raw tracing data in rodents, a connectome viewer for advanced 3D graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity matrices, and a software package that covers the complete pipeline from connectivity data to large-scale brain simulations. The second edition of CoCoMac features many enhancements over the original. For example, a search wizard is provided for full access to all tables and their nested dependencies. Connectivity matrices can be computed on demand in a user-selected nomenclature. A new data entry system is available as a preview, and is to become a generic solution for community-driven data entry in manually collated databases. We conclude with the question whether neuronal tracing will remain the gold standard to uncover the wiring of brains, thereby highlighting developments in human connectome construction, tracer substances, polarized light imaging, and serial block-face scanning electron microscopy. PMID:23293600

CoCoMac 2.0 and the future of tract-tracing databases.

PubMed

Bakker, Rembrandt; Wachtler, Thomas; Diesmann, Markus

2012-01-01

The CoCoMac database contains the results of several hundred published axonal tract-tracing studies in the macaque monkey brain. The combined results are used for constructing the macaque macro-connectome. Here we discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two online resources that provide full access to raw tracing data in rodents, a connectome viewer for advanced 3D graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity matrices, and a software package that covers the complete pipeline from connectivity data to large-scale brain simulations. The second edition of CoCoMac features many enhancements over the original. For example, a search wizard is provided for full access to all tables and their nested dependencies. Connectivity matrices can be computed on demand in a user-selected nomenclature. A new data entry system is available as a preview, and is to become a generic solution for community-driven data entry in manually collated databases. We conclude with the question whether neuronal tracing will remain the gold standard to uncover the wiring of brains, thereby highlighting developments in human connectome construction, tracer substances, polarized light imaging, and serial block-face scanning electron microscopy.

A Semi-Vectorization Algorithm to Synthesis of Gravitational Anomaly Quantities on the Earth

NASA Astrophysics Data System (ADS)

Abdollahzadeh, M.; Eshagh, M.; Najafi Alamdari, M.

2009-04-01

The Earth's gravitational potential can be expressed by the well-known spherical harmonic expansion. The computational time of summing up this expansion is an important practical issue which can be reduced by an efficient numerical algorithm. This paper proposes such a method for block-wise synthesizing the anomaly quantities on the Earth surface using vectorization. Fully-vectorization means transformation of the summations to the simple matrix and vector products. It is not a practical for the matrices with large dimensions. Here a semi-vectorization algorithm is proposed to avoid working with large vectors and matrices. It speeds up the computations by using one loop for the summation either on degrees or on orders. The former is a good option to synthesize the anomaly quantities on the Earth surface considering a digital elevation model (DEM). This approach is more efficient than the two-step method which computes the quantities on the reference ellipsoid and continues them upward to the Earth surface. The algorithm has been coded in MATLAB which synthesizes a global grid of 5′Ã- 5′ (corresponding 9 million points) of gravity anomaly or geoid height using a geopotential model to degree 360 in 10000 seconds by an ordinary computer with 2G RAM.

Thermoresponsive microgels containing trehalose as soft matrices for 3D cell culture.

PubMed

Burek, Małgorzata; Waśkiewicz, Sylwia; Lalik, Anna; Student, Sebastian; Bieg, Tadeusz; Wandzik, Ilona

2017-01-31

A series of thermoresponsive glycomicrogels with trehalose in the cross-links or with trehalose in the cross-links and as pending moieties was synthesized. These materials were obtained by surfactant-free precipitation copolymerization of N-isopropylacrylamide and various amounts of trehalose monomers. The resultant particles showed a spherical shape and a submicrometer hydrodynamic size with a narrow size distribution. At 25 °C, glycomicrogels in solutions with physiological ionic strength formed stable colloids, which further gelled upon heating to physiological temperature forming a macroscopic hydrogel with an interconnected porous structure. These extremely soft matrices with dynamic storage modulus in the range of 9-70 Pa were examined in 3D culture systems for HeLa cell culture in comparison to traditional 2D mode. They showed relatively low syneresis over time, especially when glycomicrogels with a high content of hydrophilic trehalose were used as building blocks. An incorporated pending trehalose composed of two α,α'-1,1'-linked d-glucose moieties was used with the intention of providing multivalent interactions with glucose transporters (GLUTs) expressed on the cell surface. A better cell viability was observed when a soft hydrogel with the highest content of trehalose and the lowest syneresis was used as a matrix compared to a 2D control assay.

Periodic GMP Matrices

NASA Astrophysics Data System (ADS)

Eichinger, Benjamin

2016-07-01

We recall criteria on the spectrum of Jacobi matrices such that the corresponding isospectral torus consists of periodic operators. Motivated by those known results for Jacobi matrices, we define a new class of operators called GMP matrices. They form a certain Generalization of matrices related to the strong Moment Problem. This class allows us to give a parametrization of almost periodic finite gap Jacobi matrices by periodic GMP matrices. Moreover, due to their structural similarity we can carry over numerous results from the direct and inverse spectral theory of periodic Jacobi matrices to the class of periodic GMP matrices. In particular, we prove an analogue of the remarkable ''magic formula'' for this new class.

Fast, exact k-space sample density compensation for trajectories composed of rotationally symmetric segments, and the SNR-optimized image reconstruction from non-Cartesian samples.

PubMed

Mitsouras, Dimitris; Mulkern, Robert V; Rybicki, Frank J

2008-08-01

A recently developed method for exact density compensation of non uniformly arranged samples relies on the analytically known cross-correlations of Fourier basis functions corresponding to the traced k-space trajectory. This method produces a linear system whose solution represents compensated samples that normalize the contribution of each independent element of information that can be expressed by the underlying trajectory. Unfortunately, linear system-based density compensation approaches quickly become computationally demanding with increasing number of samples (i.e., image resolution). Here, it is shown that when a trajectory is composed of rotationally symmetric interleaves, such as spiral and PROPELLER trajectories, this cross-correlations method leads to a highly simplified system of equations. Specifically, it is shown that the system matrix is circulant block-Toeplitz so that the linear system is easily block-diagonalized. The method is described and demonstrated for 32-way interleaved spiral trajectories designed for 256 image matrices; samples are compensated non iteratively in a few seconds by solving the small independent block-diagonalized linear systems in parallel. Because the method is exact and considers all the interactions between all acquired samples, up to a 10% reduction in reconstruction error concurrently with an up to 30% increase in signal to noise ratio are achieved compared to standard density compensation methods. (c) 2008 Wiley-Liss, Inc.

Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research.

PubMed

Waller, Niels G

2016-01-01

For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.

Application of stochastic automata networks for creation of continuous time Markov chain models of voltage gating of gap junction channels.

PubMed

Snipas, Mindaugas; Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Paulauskas, Nerijus; Bukauskas, Feliksas F

2015-01-01

The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ~20 times.

Factor structure of the Hooper Visual Organization Test: a cross-cultural replication and extension.

PubMed

Merten, Thomas

2005-01-01

To investigate construct validity of the Hooper Visual Organization Test (VOT), a principal-axis analysis was performed on the neuropsychological test results of 200 German-speaking neurological patients who received a comprehensive battery, encompassing tests of visuospatial functions, memory, attention, executive functions, naming ability, and vocabulary. A four-factor solution was obtained with substantial loadings of the VOT only on the first factor, interpreted as a global dimension of non-verbal cognitive functions. This factor loaded significantly on numerous measures of visuospatial processing and attention (with particularly high loadings on WAIS-R Block Design, Trails A and B, and Raven's Standard Progressive Matrices). The remaining three factors were interpreted as memory, verbal abilities (vocabulary), and a separate factor of naming abilities.

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

Tungsten wire/FeCrAlY matrix turbine blade fabrication study

NASA Technical Reports Server (NTRS)

Melnyk, P.; Fleck, J. N.

1979-01-01

The objective was to establish a viable FRS monotape technology base to fabricate a complex, advanced turbine blade. All elements of monotape fabrication were addressed. A new process for incorporation of the matrix, including bi-alloy matrices, was developed. Bonding, cleaning, cutting, sizing, and forming parameters were established. These monotapes were then used to fabricate a 48 ply solid JT9D-7F 1st stage turbine blade. Core technology was then developed and first a 12 ply and then a 7 ply shell hollow airfoil was fabricated. As the fabrication technology advanced, additional airfoils incorporated further elements of sophistication, by introducing in sequence bonded root blocks, cross-plying, bi-metallic matrix, tip cap, trailing edge slots, and impingement inserts.

Block Gauss elimination followed by a classical iterative method for the solution of linear systems

NASA Astrophysics Data System (ADS)

Alanelli, Maria; Hadjidimos, Apostolos

2004-02-01

In the last two decades many papers have appeared in which the application of an iterative method for the solution of a linear system is preceded by a step of the Gauss elimination process in the hope that this will increase the rates of convergence of the iterative method. This combination of methods has been proven successful especially when the matrix A of the system is an M-matrix. The purpose of this paper is to extend the idea of one to more Gauss elimination steps, consider other classes of matrices A, e.g., p-cyclic consistently ordered, and generalize and improve the asymptotic convergence rates of some of the methods known so far.

Symmetric convolution of asymmetric multidimensional sequences using discrete trigonometric transforms.

PubMed

Foltz, T M; Welsh, B M

1999-01-01

This paper uses the fact that the discrete Fourier transform diagonalizes a circulant matrix to provide an alternate derivation of the symmetric convolution-multiplication property for discrete trigonometric transforms. Derived in this manner, the symmetric convolution-multiplication property extends easily to multiple dimensions using the notion of block circulant matrices and generalizes to multidimensional asymmetric sequences. The symmetric convolution of multidimensional asymmetric sequences can then be accomplished by taking the product of the trigonometric transforms of the sequences and then applying an inverse trigonometric transform to the result. An example is given of how this theory can be used for applying a two-dimensional (2-D) finite impulse response (FIR) filter with nonlinear phase which models atmospheric turbulence.

Optical properties of graphene superlattices.

PubMed

Le, H Anh; Ho, S Ta; Nguyen, D Chien; Do, V Nam

2014-10-08

In this work, the optical responses of graphene superlattices, i.e. graphene subjected to a periodic scalar potential, are theoretically reported. The optical properties were studied by investigating the optical conductivity, which was calculated using the Kubo formalism. It was found that the optical conductivity becomes dependent on the photon polarization and is suppressed in the photon energy range of (0, Ub), where Ub is the potential barrier height. In the higher photon energy range, i.e. Ω > Ub, the optical conductivity is, however, almost identical to that of pristine graphene. Such behaviors of the optical conductivity are explained microscopically through the analysis of the elements of optical matrices and effectively through a simple model, which is based on the Pauli blocking mechanism.

Elucidation of the Structure Formation of Polymer-Conjugated Proteins in Solution and Block Copolymer Templates

NASA Astrophysics Data System (ADS)

Ferebee, Rachel L.

The broader technical objective of this work is to contribute to the development of enzyme-functionalized nanoporous membranes that can function as autonomous and target selective dynamic separators. The scientific objective of the research performed within this thesis is to elucidate the parameters that control the mixing of proteins in organic host materials and in block copolymers templates in particular. A "biomimetic" membrane system that uses enzymes to selectively neutralize targets and trigger a change in permeability of nanopores lined with a pH-responsive polymer has been fabricated and characterized. Mechanical and functional stability, as well as scalability, have been demonstrated for this system. Additional research has focused on the role of polymeric ligands on the solubility characteristics of the model protein, Bovine Serum Albumin (BSA). For this purpose BSA was conjugated with poly(ethylene glycol) (PEG) ligands of varied degree of polymerization and grafting density. Combined static and dynamic light scattering was used (in conjunction with MALDI-TOF) to determine the second virial coefficient in PBS solutions. At a given mass fraction PEG or average number of grafts, the solubility of BSA-PEG conjugates is found to increase with the degree of polymerization of conjugated PEG. This result informs the synthesis of protein-conjugate systems that are optimized for the fabrication of block copolymer blend materials with maximum protein loading. Blends of BSA-PEG conjugates and block copolymer (BCP) matrices were fabricated to evaluate the dispersion morphology and solubility limits in a model system. Electron microscopy was used to evaluate the changes in lamellar spacing with increased filling fraction of BSA-PEG conjugates.

The trellis complexity of convolutional codes

NASA Technical Reports Server (NTRS)

Mceliece, R. J.; Lin, W.

1995-01-01

It has long been known that convolutional codes have a natural, regular trellis structure that facilitates the implementation of Viterbi's algorithm. It has gradually become apparent that linear block codes also have a natural, though not in general a regular, 'minimal' trellis structure, which allows them to be decoded with a Viterbi-like algorithm. In both cases, the complexity of the Viterbi decoding algorithm can be accurately estimated by the number of trellis edges per encoded bit. It would, therefore, appear that we are in a good position to make a fair comparison of the Viterbi decoding complexity of block and convolutional codes. Unfortunately, however, this comparison is somewhat muddled by the fact that some convolutional codes, the punctured convolutional codes, are known to have trellis representations that are significantly less complex than the conventional trellis. In other words, the conventional trellis representation for a convolutional code may not be the minimal trellis representation. Thus, ironically, at present we seem to know more about the minimal trellis representation for block than for convolutional codes. In this article, we provide a remedy, by developing a theory of minimal trellises for convolutional codes. (A similar theory has recently been given by Sidorenko and Zyablov). This allows us to make a direct performance-complexity comparison for block and convolutional codes. A by-product of our work is an algorithm for choosing, from among all generator matrices for a given convolutional code, what we call a trellis-minimal generator matrix, from which the minimal trellis for the code can be directly constructed. Another by-product is that, in the new theory, punctured convolutional codes no longer appear as a special class, but simply as high-rate convolutional codes whose trellis complexity is unexpectedly small.

Label-Free Fluorescent DNA Dendrimers for microRNA Detection Based On Nonlinear Hybridization Chain Reaction-Mediated Multiple G-Quadruplex with Low Background Signal.

PubMed

Xue, Qingwang; Liu, Chunxue; Li, Xia; Dai, Li; Wang, Huaisheng

2018-04-18

Various fluorescent sensing systems for miRNA detection have been developed, but they mostly contain enzymatic amplification reactions and label procedures. The strict reaction conditions of tool enzymes and the high cost of labeling limit their potential applications, especially in complex biological matrices. Here, we have addressed the difficult problems and report a strategy for label-free fluorescent DNA dendrimers based on enzyme-free nonlinear hybridization chain reaction (HCR)-mediated multiple G-quadruplex for simple, sensitive, and selective detection of miRNAs with low-background signal. In the strategy, a split G-quadruplex (3:1) sequence is ingeniously designed at both ends of two double-stranded DNAs, which is exploited as building blocks for nonlinear HCR assembly, thereby acquiring a low background signal. A hairpin switch probe (HSP) was employed as recognition and transduction element. Upon sensing the target miRNA, the nonlinear HCR assembly of two blocks (blocks-A and blocks-B) was initiated with the help of two single-stranded DNA assistants, resulting in chain-branching growth of DNA dendrimers with multiple G-quadruplex incorporation. With the zinc(II)-protoporphyrin IX (ZnPPIX) selectively intercalated into the multiple G-quadruplexes, fluorescent DNA dendrimers were obtained, leading to an exponential fluorescence intensity increase. Benefiting from excellent performances of nonlinear HCR and low background signal, this strategy possesses the characteristics of a simplified reaction operation process, as well as high sensitivity. Moreover, the proposed fluorescent sensing strategy also shows preferable selectivity, and can be implemented without modified DNA blocks. Importantly, the strategy has also been tested for miRNA quantification with high confidence in breast cancer cells. Thus, this proposed strategy for label-free fluorescent DNA dendrimers based on a nonlinear HCR-mediated multiple G-quadruplex will be turned into an alternative approach for simple, sensitive, and selective miRNA quantification.

CMV matrices in random matrix theory and integrable systems: a survey

NASA Astrophysics Data System (ADS)

Nenciu, Irina

2006-07-01

We present a survey of recent results concerning a remarkable class of unitary matrices, the CMV matrices. We are particularly interested in the role they play in the theory of random matrices and integrable systems. Throughout the paper we also emphasize the analogies and connections to Jacobi matrices.

Basal Cell Carcinoma With Matrical Differentiation: Clinicopathologic, Immunohistochemical, and Molecular Biological Study of 22 Cases.

PubMed

Kyrpychova, Liubov; Carr, Richard A; Martinek, Petr; Vanecek, Tomas; Perret, Raul; Chottová-Dvořáková, Magdalena; Zamecnik, Michal; Hadravsky, Ladislav; Michal, Michal; Kazakov, Dmitry V

2017-06-01

Basal cell carcinoma (BCC) with matrical differentiation is a fairly rare neoplasm, with about 30 cases documented mainly as isolated case reports. We studied a series of this neoplasm, including cases with an atypical matrical component, a hitherto unreported feature. Lesions coded as BCC with matrical differentiation were reviewed; 22 cases were included. Immunohistochemical studies were performed using antibodies against BerEp4, β-catenin, and epithelial membrane antigen (EMA). Molecular genetic studies using Ion AmpliSeq Cancer Hotspot Panel v2 by massively parallel sequencing on Ion Torrent PGM were performed in 2 cases with an atypical matrical component (1 was previously subjected to microdissection to sample the matrical and BCC areas separately). There were 13 male and 9 female patients, ranging in age from 41 to 89 years. Microscopically, all lesions manifested at least 2 components, a BCC area (follicular germinative differentiation) and areas with matrical differentiation. A BCC component dominated in 14 cases, whereas a matrical component dominated in 4 cases. Matrical differentiation was recognized as matrical/supramatrical cells (n=21), shadow cells (n=21), bright red trichohyaline granules (n=18), and blue-gray corneocytes (n=18). In 2 cases, matrical areas manifested cytologic atypia, and a third case exhibited an infiltrative growth pattern, with the tumor metastasizing to a lymph node. BerEP4 labeled the follicular germinative cells, whereas it was markedly reduced or negative in matrical areas. The reverse pattern was seen with β-catenin. EMA was negative in BCC areas but stained a proportion of matrical/supramatrical cells. Genetic studies revealed mutations of the following genes: CTNNB1, KIT, CDKN2A, TP53, SMAD4, ERBB4, and PTCH1, with some differences between the matrical and BCC components. It is concluded that matrical differentiation in BCC in most cases occurs as multiple foci. Rare neoplasms manifest atypia in the matrical areas. Immunohistochemical analysis for BerEP4, EMA, and β-catenin can be helpful in limited biopsy specimens. From a molecular biological prospective, BCC and matrical components appear to share some of the gene mutations but have differences in others, but this observation must be validated in a large series.

A Brief Historical Introduction to Matrices and Their Applications

ERIC Educational Resources Information Center

Debnath, L.

2014-01-01

This paper deals with the ancient origin of matrices, and the system of linear equations. Included are algebraic properties of matrices, determinants, linear transformations, and Cramer's Rule for solving the system of algebraic equations. Special attention is given to some special matrices, including matrices in graph theory and electrical…

Laminin active peptide/agarose matrices as multifunctional biomaterials for tissue engineering.

PubMed

Yamada, Yuji; Hozumi, Kentaro; Aso, Akihiro; Hotta, Atsushi; Toma, Kazunori; Katagiri, Fumihiko; Kikkawa, Yamato; Nomizu, Motoyoshi

2012-06-01

Cell adhesive peptides derived from extracellular matrix components are potential candidates to afford bio-adhesiveness to cell culture scaffolds for tissue engineering. Previously, we covalently conjugated bioactive laminin peptides to polysaccharides, such as chitosan and alginate, and demonstrated their advantages as biomaterials. Here, we prepared functional polysaccharide matrices by mixing laminin active peptides and agarose gel. Several laminin peptide/agarose matrices showed cell attachment activity. In particular, peptide AG73 (RKRLQVQLSIRT)/agarose matrices promoted strong cell attachment and the cell behavior depended on the stiffness of agarose matrices. Fibroblasts formed spheroid structures on the soft AG73/agarose matrices while the cells formed a monolayer with elongated morphologies on the stiff matrices. On the stiff AG73/agarose matrices, neuronal cells extended neuritic processes and endothelial cells formed capillary-like networks. In addition, salivary gland cells formed acini-like structures on the soft matrices. These results suggest that the peptide/agarose matrices are useful for both two- and three-dimensional cell culture systems as a multifunctional biomaterial for tissue engineering. Copyright © 2012 Elsevier Ltd. All rights reserved.

Precisely Size-Tunable Monodisperse Hairy Plasmonic Nanoparticles via Amphiphilic Star-Like Block Copolymers.

PubMed

Chen, Yihuang; Yoon, Young Jun; Pang, Xinchang; He, Yanjie; Jung, Jaehan; Feng, Chaowei; Zhang, Guangzhao; Lin, Zhiqun

2016-12-01

In situ precision synthesis of monodisperse hairy plasmonic nanoparticles with tailored dimensions and compositions by capitalizing on amphiphilic star-like diblock copolymers as nanoreactors are reported. Such hairy plasmonic nanoparticles comprise uniform noble metal nanoparticles intimately and perpetually capped by hydrophobic polymer chains (i.e., "hairs") with even length. Interestingly, amphiphilic star-like diblock copolymer nanoreactors retain the spherical shape under reaction conditions, and the diameter of the resulting plasmonic nanoparticles and the thickness of polymer chains situated on the surface of the nanoparticle can be readily and precisely tailored. These hairy nanoparticles can be regarded as hard/soft core/shell nanoparticles. Notably, the polymer "hairs" are directly and permanently tethered to the noble metal nanoparticle surface, thereby preventing the aggregation of nanoparticles and rendering their dissolution in nonpolar solvents and the homogeneous distribution in polymer matrices with long-term stability. This amphiphilic star-like block copolymer nanoreactor-based strategy is viable and robust and conceptually enables the design and synthesis of a rich variety of hairy functional nanoparticles with new horizons for fundamental research on self-assembly and technological applications in plasmonics, catalysis, energy conversion and storage, bioimaging, and biosensors. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of polyphenylquinoxaline graphite composites

NASA Technical Reports Server (NTRS)

Hoggatt, J. T.; Hergenrother, P. M.; Shdo, J. G.

1973-01-01

The potential of polyphenylquinoxaline (PPQ)/graphite composites to serve as structural material at 316 C (600 F)has been demonstrated using a block copolymer, BlCo(13), PPQ derivative. Initially, thirteen polyphenylquinoxalines were evaluated. From this work, four candidate polymers were selected for preliminary evaluation as matrices for HMS graphite fiber reinforced composites. The preliminary composite evaluation enabled selection of one of the four polymers for advanced composite preparation and testing. Using an experimentally established cure schedule for each of the four polymers, preliminary laminates of 50% resin volume content, prepared without postcure, were tested for flexure strength and modulus, interlaminar shear strength (short beam), and tensile strength and modulus at ambient temperature. A block copolymer (Bl Co 13) derived from one mole p-bis (phenylglyoxalyl) benzene, one fourth mole 3,3'-diaminobenzidine and three-fourths mole 3,3', 4,4'-tetraminobenzophenone was selected for extensive study. Tensile, flexural, and interlaminar shear values were obtained after aging and testing postcured BlCo(13) laminates at 316 C (600 F). The potential of PPQ/graphite laminates to serve as short term structural materials at temperatures up to 371 C (700 F) was demonstrated through weight loss experiments.

A Novel Approach for Constructing One-Way Hash Function Based on a Message Block Controlled 8D Hyperchaotic Map

NASA Astrophysics Data System (ADS)

Lin, Zhuosheng; Yu, Simin; Lü, Jinhu

2017-06-01

In this paper, a novel approach for constructing one-way hash function based on 8D hyperchaotic map is presented. First, two nominal matrices both with constant and variable parameters are adopted for designing 8D discrete-time hyperchaotic systems, respectively. Then each input plaintext message block is transformed into 8 × 8 matrix following the order of left to right and top to bottom, which is used as a control matrix for the switch of the nominal matrix elements both with the constant parameters and with the variable parameters. Through this switching control, a new nominal matrix mixed with the constant and variable parameters is obtained for the 8D hyperchaotic map. Finally, the hash function is constructed with the multiple low 8-bit hyperchaotic system iterative outputs after being rounded down, and its secure analysis results are also given, validating the feasibility and reliability of the proposed approach. Compared with the existing schemes, the main feature of the proposed method is that it has a large number of key parameters with avalanche effect, resulting in the difficulty for estimating or predicting key parameters via various attacks.

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

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

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms thatmore » iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.« less

Multifunctional Self-Adhesive Fibrous Layered Matrix (FiLM) for Tissue Glues and Therapeutic Carriers.

PubMed

Yoon, Ye-Eun; Im, Byung Gee; Kim, Jung-Suk; Jang, Jae-Hyung

2017-01-09

Tissue adhesives, which inherently serve as wound sealants or as hemostatic agents, can be further augmented to acquire crucial functions as scaffolds, thereby accelerating wound healing or elevating the efficacy of tissue regeneration. Herein, multifunctional adherent fibrous matrices, acting as self-adhesive scaffolds capable of cell/gene delivery, were devised by coaxially electrospinning poly(caprolactone) (PCL) and poly(vinylpyrrolidone) (PVP). Wrapping the building block PCL fibers with the adherent PVP layers formed film-like fibrous matrices that could rapidly adhere to wet biological surfaces, referred to as fibrous layered matrix (FiLM) adhesives. The inclusion of ionic salts (i.e., dopamine hydrochloride) in the sheath layers generated spontaneously multilayered fibrous adhesives, whose partial layers could be manually peeled off, termed derivative FiLM (d-FiLM). In the context of scaffolds/tissue adhesives, both FiLM and d-FiLM demonstrated almost identical characteristics (i.e., sticky, mechanical, and performances as cell/gene carriers). Importantly, the single FiLM-process can yield multiple sets of d-FiLM by investing the same processing time, materials, and labor required to form a single conventional adhesive fibrous mat, thereby highlighting the economic aspects of the process. The FiLM/d-FiLM offer highly impacting contributions to many biomedical applications, especially in fields that require urgent aids (e.g., endoscopic surgeries, implantation in wet environments, severe wounds).

Elastomeric photo-actuators and their investigation by confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Czaniková, Klaudia; Ilčíková, Markéta; Krupa, Igor; Mičušík, Matej; Kasák, Peter; Pavlova, Ewa; Mosnáček, Jaroslav; Chorvát, Dušan, Jr.; Omastová, Mária

2013-10-01

The photo-actuation behavior of nanocomposites based on ethylene-vinylacetate copolymer (EVA) and styrene-isoprene-styrene (SIS) block copolymer filled with well-dispersed and modified multiwalled carbon nanotubes (MWCNTs) is discussed in this paper. The nanocomposites were prepared by casting from solution. To improve the dispersion of the MWCNTs in EVA, the MWCNT surface was modified with a non-covalent surfactant, cholesteryl 1-pyrenecarboxylate (PyChol). To prepare SIS nanocomposites, the MWCNT surface was covalently modified with polystyrene chains. The good dispersion of the filler was confirmed by transmission electron microscopy (TEM). Special, custom-made punch/die molds were used to create a Braille element (BE)-like shape, which under shear forces induces a uniaxial orientation of the MWCNTs within the matrix. The uniaxial orientation of MWCNTs is an essential precondition to ensure the photo-actuating behavior of MWCNTs in polymeric matrices. The orientation of the MWCNTs within the matrices was examined by scanning electron microscopy (SEM). Nanocomposite BEs were illuminated from the bottom by a red light-emitting diode (LED), and the photo-actuation was investigated by confocal laser scanning microscopy (CLSM). When the BEs were exposed to light, a temporary increase in the height of the element was detected. This process was observed to be reversible: after switching off the light, the BEs returned to their original shape and height.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

NASA Astrophysics Data System (ADS)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

DOE PAGES

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

2017-10-30

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms thatmore » iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.« less

Smart materials systems through mesoscale patterning

NASA Astrophysics Data System (ADS)

Aksay, Ilhan A.; Groves, John T.; Gruner, Sol M.; Lee, P. C. Y.; Prud'homme, Robert K.; Shih, Wei-Heng; Torquato, Salvatore; Whitesides, George M.

1996-02-01

We report work on the fabrication of smart materials with two unique strategies: (1) self- assembly and (2) laser stereolithography. Both methods are akin to the processes used by biological systems. The first one is ideal for pattern development and the fabrication of miniaturized units in the submicron range and the second one in the 10 micrometer to 1 mm size range. By using these miniaturized units as building blocks, one can also produce smart material systems that can be used at larger length scales such as smart structural components. We have chosen to focus on two novel piezoceramic systems: (1) high-displacement piezoelectric actuators, and (2) piezoceramic hydrophone composites possessing negative Poisson ratio matrices. High-displacement actuators are essential in such applications as linear motors, pumps, switches, loud speakers, variable-focus mirrors, and laser deflectors. Arrays of such units can potentially be used for active vibration control of helicopter rotors as well as the fabrication of adaptive rotors. In the case of piezoceramic hydrophone composites, we utilize matrices having a negative Poisson's ratio in order to produce highly sensitive, miniaturized sensors. We envision such devices having promising new application areas such as the implantation of hydrophones in small blood vessels to monitor blood pressure. Negative Poisson ratio materials have promise as robust shock absorbers, air filters, and fasteners, and hence, can be used in aircraft and land vehicles.

On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action

NASA Astrophysics Data System (ADS)

Chekhov, L. O.; Mazzocco, M.

2017-12-01

Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.

Miscellaneous methods for measuring matric or water potential

USGS Publications Warehouse

Scanlon, Bridget R.; Andraski, Brian J.; Bilskie, Jim; Dane, Jacob H.; Topp, G. Clarke

2002-01-01

A variety of techniques to measure matric potential or water potential in the laboratory and in the field are described in this section. The techniques described herein require equilibration of some medium whose matric or water potential can be determined from previous calibration or can be measured directly. Under equilibrium conditions the matric or water potential of the medium is equal to that of the soil. The techniques can be divided into: (i) those that measure matric potential and (ii) those that measure water potential (sum of matric and osmotic potentials). Matric potential is determined when the sensor matrix is in direct contact with the soil, so salts are free to diffuse in or out of the sensor matrix, and the equilibrium measurement therefore reflects matric forces acting on the water. Water potential is determined when the sensor is separated from the soil by a vapor gap, so salts are not free to move in or out of the sensor, and the equilibrium measurement reflects the sum of the matric and osmotic forces acting on the water.Seven different techniques are described in this section. Those that measure matric potential include (i) heat dissipation sensors, (ii) electrical resistance sensors, (iii) frequency domain and time domain sensors, and (iv) electro-optical switches. A method that can be used to measure matric potential or water potential is the (v) filter paper method. Techniques that measure water potential include (vi) the Dew Point Potentiameter (Decagon Devices, Inc., Pullman, WA1) (water activity meter) and (vii) vapor equilibration.The first four techniques are electronically based methods for measuring matric potential. Heat dissipation sensors and electrical resistance sensors infer matric potential from previously determined calibration relations between sensor heat dissipation or electrical resistance and matric potential. Frequency-domain and timedomain matric potential sensors measure water content, which is related to matric potential of the sensor through calibration. Electro-optical switches measure changes in light transmission through thin, nylon filters as they absorb or desorb water in response to changes in matric potential. Heat dissipation sensors and electrical resistance sensors are used primarily in the field to provide information on matric potential. Frequency domain matric potential sensors are new and have not been widely used. Time domain matric potential sensors and electro-optical switches are new and have not been commercialized. For the fifth technique, filter paper is used as the standard matrix. The filter paper technique measures matric potential when the filter paper is in direct contact with soil or water potential when separated from soil by a vapor gap. The Dew Point Potentiameter calculates water potential from the measured dew point and sample temperature. The vapor equilibration technique involves equilibration of soil samples with salt solutions of known osmotic potential. The filter paper, Dew Point Potentiameter, and vapor equilibration techniques are generally used in the laboratory to measure water potential of disturbed field samples or to measure water potential for water retention functions.

Construction of fuzzy spaces and their applications to matrix models

NASA Astrophysics Data System (ADS)

Abe, Yasuhiro

Quantization of spacetime by means of finite dimensional matrices is the basic idea of fuzzy spaces. There remains an issue of quantizing time, however, the idea is simple and it provides an interesting interplay of various ideas in mathematics and physics. Shedding some light on such an interplay is the main theme of this dissertation. The dissertation roughly separates into two parts. In the first part, we consider rather mathematical aspects of fuzzy spaces, namely, their construction. We begin with a review of construction of fuzzy complex projective spaces CP k (k = 1, 2, · · ·) in relation to geometric quantization. This construction facilitates defining symbols and star products on fuzzy CPk. Algebraic construction of fuzzy CPk is also discussed. We then present construction of fuzzy S 4, utilizing the fact that CP3 is an S2 bundle over S4. Fuzzy S4 is obtained by imposing an additional algebraic constraint on fuzzy CP3. Consequently it is proposed that coordinates on fuzzy S4 are described by certain block-diagonal matrices. It is also found that fuzzy S8 can analogously be constructed. In the second part of this dissertation, we consider applications of fuzzy spaces to physics. We first consider theories of gravity on fuzzy spaces, anticipating that they may offer a novel way of regularizing spacetime dynamics. We obtain actions for gravity on fuzzy S2 and on fuzzy CP3 in terms of finite dimensional matrices. Application to M(atrix) theory is also discussed. With an introduction of extra potentials to the theory, we show that it also has new brane solutions whose transverse directions are described by fuzzy S 4 and fuzzy CP3. The extra potentials can be considered as fuzzy versions of differential forms or fluxes, which enable us to discuss compactification models of M(atrix) theory. In particular, compactification down to fuzzy S4 is discussed and a realistic matrix model of M-theory in four-dimensions is proposed.

Computation of eigenpairs of Ax = lambda Bx for vibrations of spinning deformable bodies

NASA Technical Reports Server (NTRS)

Utku, S.; Clemente, J. L. M.

1984-01-01

It is shown that, when linear theory is used, the general eigenvalue problem related with the free vibrations of spinning deformable bodies is of the type AX = lambda Bx, where A is Hermitian, and B is real positive definite. Since the order n of the matrices may be large, and A and B are banded or block banded, due to the economics of the numerical solution, one is interested in obtaining only those eigenvalues which fall within the frequency band of interest of the problem. The paper extends the well known method of bisections and iteration of R to the n power to n dimensional complex spaces, i.e., to C to the n power, so that it can be applied to the present problem.

Application of Stochastic Automata Networks for Creation of Continuous Time Markov Chain Models of Voltage Gating of Gap Junction Channels

PubMed Central

Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Bukauskas, Feliksas F.

2015-01-01

The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times. PMID:25705700

Further Results on Sufficient LMI Conditions for H∞ Static Output Feedback Control of Discrete-Time Systems

NASA Astrophysics Data System (ADS)

Feng, Zhi-Yong; Xu, Li; Matsushita, Shin-Ya; Wu, Min

Further results on sufficient LMI conditions for H∞ static output feedback (SOF) control of discrete-time systems are presented in this paper, which provide some new insights into this issue. First, by introducing a slack variable with block-triangular structure and choosing the coordinate transformation matrix properly, the conservativeness of one kind of existing sufficient LMI condition is further reduced. Then, by introducing a slack variable with linear matrix equality constraint, another kind of sufficient LMI condition is proposed. Furthermore, the relation of these two kinds of LMI conditions are revealed for the first time through analyzing the effect of different choices of coordinate transformation matrices. Finally, a numerical example is provided to demonstrate the effectiveness and merits of the proposed methods.

Newton-based optimization for Kullback-Leibler nonnegative tensor factorizations

DOE PAGES

Plantenga, Todd; Kolda, Tamara G.; Hansen, Samantha

2015-04-30

Tensor factorizations with nonnegativity constraints have found application in analysing data from cyber traffic, social networks, and other areas. We consider application data best described as being generated by a Poisson process (e.g. count data), which leads to sparse tensors that can be modelled by sparse factor matrices. In this paper, we investigate efficient techniques for computing an appropriate canonical polyadic tensor factorization based on the Kullback–Leibler divergence function. We propose novel subproblem solvers within the standard alternating block variable approach. Our new methods exploit structure and reformulate the optimization problem as small independent subproblems. We employ bound-constrained Newton andmore » quasi-Newton methods. Finally, we compare our algorithms against other codes, demonstrating superior speed for high accuracy results and the ability to quickly find sparse solutions.« less

Connecting Fermion Masses and Mixings to BSM Physics - Quarks

NASA Astrophysics Data System (ADS)

Goldman, Terrence; Stephenson, Gerard J., Jr.

2015-10-01

The ``democratic'' mass matrix with BSM physics assumptions has been studied without success. We invert the process and use the ``democratic'' mass matrix plus a parametrization of all possible BSM corrections to analyze the implications of the observed masses and CKM weak interaction current mixing for the BSM parameter values for the up-quarks and down-quarks. We observe that the small mixing of the so-called ``third generation'' is directly related to the large mass gap from the two lighter generations. Conversely, the relatively large value of the Cabibbo angle arises because the mass matrices in the light sub-sector (block diagonalized from the full three channel problem) are neither diagonal nor degenerate and differ significantly between the up and down cases. Alt email:t.goldman@gmail.com

Implementation of an ADI method on parallel computers

NASA Technical Reports Server (NTRS)

Fatoohi, Raad A.; Grosch, Chester E.

1987-01-01

The implementation of an ADI method for solving the diffusion equation on three parallel/vector computers is discussed. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, an SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the FLEX/32 and CRAY/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.

Implementation of an ADI method on parallel computers

NASA Technical Reports Server (NTRS)

Fatoohi, Raad A.; Grosch, Chester E.

1987-01-01

In this paper the implementation of an ADI method for solving the diffusion equation on three parallel/vector computers is discussed. The computers were chosen so as to encompass a variety of architectures. They are the MPP, an SIMD machine with 16-Kbit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the Flex/32 and Cray/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally conclusions are presented.

Pentadiagonal alternating-direction-implicit finite-difference time-domain method for two-dimensional Schrödinger equation

NASA Astrophysics Data System (ADS)

Tay, Wei Choon; Tan, Eng Leong

2014-07-01

In this paper, we have proposed a pentadiagonal alternating-direction-implicit (Penta-ADI) finite-difference time-domain (FDTD) method for the two-dimensional Schrödinger equation. Through the separation of complex wave function into real and imaginary parts, a pentadiagonal system of equations for the ADI method is obtained, which results in our Penta-ADI method. The Penta-ADI method is further simplified into pentadiagonal fundamental ADI (Penta-FADI) method, which has matrix-operator-free right-hand-sides (RHS), leading to the simplest and most concise update equations. As the Penta-FADI method involves five stencils in the left-hand-sides (LHS) of the pentadiagonal update equations, special treatments that are required for the implementation of the Dirichlet's boundary conditions will be discussed. Using the Penta-FADI method, a significantly higher efficiency gain can be achieved over the conventional Tri-ADI method, which involves a tridiagonal system of equations.

Role of heat equation in lap joint for welding process

NASA Astrophysics Data System (ADS)

Kumar, P.; Rohit, Sooraj

2017-07-01

Welding is predominantly used in industrial purposes and growth in their industry, which gives exact welding and more efficient. The major advantage of using this welding technique at initial stage it takes very low heat to weld the portion and gives a good result of low distortion in modules. In this context, two dissimilar metals copper and nickel are chosen for analysis in tungsten inert gas welding (TIG) in which length is 300 mm and breadth is 100 mm thickness 15 mm welded at room temperature a welded portion zone is formed simulation analysis has done on CATIA® and ANSYS®and MATLAB® code is generated for calculating temperatures at each node to calculate temperature at each node a new technique is used tri-diagonal matrix algorithm is used (TDMA) Steady state one dimension heat is calculated results compared between simulation analysis and analytical analysis temperature at each node is calculated both the temperatures are equal with error.

Cell-adhesive RGD peptide-displaying M13 bacteriophage/PLGA nanofiber matrices for growth of fibroblasts.

PubMed

Shin, Yong Cheol; Lee, Jong Ho; Jin, Linhua; Kim, Min Jeong; Oh, Jin-Woo; Kim, Tai Wan; Han, Dong-Wook

2014-01-01

M13 bacteriophages can be readily fabricated as nanofibers due to non-toxic bacterial virus with a nanofiber-like shape. In the present study, we prepared hybrid nanofiber matrices composed of poly(lactic-co-glycolic acid, PLGA) and M13 bacteriophages which were genetically modified to display the RGD peptide on their surface (RGD-M13 phage). The surface morphology and chemical composition of hybrid nanofiber matrices were characterized by scanning electron microscopy (SEM) and Raman spectroscopy, respectively. Immunofluorescence staining was conducted to investigate the existence of M13 bacteriophages in RGD-M13 phage/PLGA hybrid nanofibers. In addition, the attachment and proliferation of three different types of fibroblasts on RGD-M13 phage/PLGA nanofiber matrices were evaluated to explore how fibroblasts interact with these matrices. SEM images showed that RGD-M13 phage/PLGA hybrid matrices had the non-woven porous structure, quite similar to that of natural extracellular matrices, having an average fiber diameter of about 190 nm. Immunofluorescence images and Raman spectra revealed that RGD-M13 phages were homogeneously distributed in entire matrices. Moreover, the attachment and proliferation of fibroblasts cultured on RGD-M13 phage/PLGA matrices were significantly enhanced due to enriched RGD moieties on hybrid matrices. These results suggest that RGD-M13 phage/PLGA matrices can be efficiently used as biomimetic scaffolds for tissue engineering applications.

Bayes linear covariance matrix adjustment

NASA Astrophysics Data System (ADS)

Wilkinson, Darren J.

1995-12-01

In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices is motivated and constructed. The inner-product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability and related specifications to obtain representations allowing analysis. Adjustment is associated with orthogonal projection, and illustrated with examples of adjustments for some common problems. The problem of adjusting the covariance matrices underlying exchangeable random vectors is tackled and discussed. Learning about the covariance matrices associated with multivariate time series dynamic linear models is shown to be amenable to a similar approach. Diagnostics for matrix adjustments are also discussed.

Mechano-responsive hydrogels crosslinked by reactive block copolymer micelles

NASA Astrophysics Data System (ADS)

Xiao, Longxi

Hydrogels are crosslinked polymeric networks that can swell in water without dissolution. Owing to their structural similarity to the native extracelluar matrices, hydrogels have been widely used in biomedical applications. Synthetic hydrogels have been designed to respond to various stimuli, but mechanical signals have not incorporated into hydrogel matrices. Because most tissues in the body are subjected to various types of mechanical forces, and cells within these tissues have sophisticated mechano-transduction machinery, this thesis is focused on developing hydrogel materials with built-in mechano-sensing mechanisms for use as tissue engineering scaffolds or drug release devices. Self-assembled block copolymer micelles (BCMs) with reactive handles were employed as the nanoscopic crosslinkers for the construction of covalently crosslinked networks. BCMs were assembled from amphiphilic diblock copolymers of poly(n-butyl acrylate) and poly(acrylic acid) partially modified with acrylate. Radical polymerization of acrylamide in the presence of micellar crosslinkers gave rise to elastomeric hydrogels whose mechanical properties can be tuned by varying the BCM composition and concentration. TEM imaging revealed that the covalently integrated BCMs underwent strain-dependent reversible deformation. A model hydrophobic drug, pyrene, loaded into the core of BCMs prior to the hydrogel formation, was dynamically released in response to externally applied mechanical forces, through force-induced reversible micelle deformation and the penetration of water molecules into the micelle core. The mechano-responsive hydrogel has been studied for tissue repair and regeneration purposes. Glycidyl methacrylate (GMA)-modified hyaluronic acid (HA) was photochemically crosslinked in the presence of dexamethasone (DEX)-loaded crosslinkable BCMs. The resultant HA gels (HAxBCM) contain covalently integrated micellar compartments with DEX being sequestered in the hydrophobic core. Compared to the traditional HA gels prepared by radical crosslinking of HAGMA, HAxBCM gels exhibited improved drug loading and release capacity. Moreover, compressive forces exerted on the gels were transmitted to the crosslinked BCMs, resulting in a force-modulated DEX release on demand. Micelle mobility in the crosslinked networks was analyzed by fluorescence correlation spectroscopy using nile red loaded BCMs. The anti-inflammatory activities of DEX-releasing HAxBCM gels were evaluated via the in vitro culture of lipopolysaccharide-activated macrophages.

High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices

NASA Astrophysics Data System (ADS)

Dunham, Benjamin Z.

This work presents a new automatic differentiation method, Nilpotent Matrix Differentiation (NMD), capable of propagating any order of mixed or univariate derivative through common linear algebra functions--most notably third-party sparse solvers and decomposition routines, in addition to basic matrix arithmetic operations and power series--without changing data-type or modifying code line by line; this allows differentiation across sequences of arbitrarily many such functions with minimal implementation effort. NMD works by enlarging the matrices and vectors passed to the routines, replacing each original scalar with a matrix block augmented by derivative data; these blocks are constructed with special sparsity structures, termed "stencils," each designed to be isomorphic to a particular multidimensional hypercomplex algebra. The algebras are in turn designed such that Taylor expansions of hypercomplex function evaluations are finite in length and thus exactly track derivatives without approximation error. Although this use of the method in the "forward mode" is unique in its own right, it is also possible to apply it to existing implementations of the (first-order) discrete adjoint method to find high-order derivatives with lowered cost complexity; for example, for a problem with N inputs and an adjoint solver whose cost is independent of N--i.e., O(1)--the N x N Hessian can be found in O(N) time, which is comparable to existing second-order adjoint methods that require far more problem-specific implementation effort. Higher derivatives are likewise less expensive--e.g., a N x N x N rank-three tensor can be found in O(N2). Alternatively, a Hessian-vector product can be found in O(1) time, which may open up many matrix-based simulations to a range of existing optimization or surrogate modeling approaches. As a final corollary in parallel to the NMD-adjoint hybrid method, the existing complex-step differentiation (CD) technique is also shown to be capable of finding the Hessian-vector product. All variants are implemented on a stochastic diffusion problem and compared in-depth with various cost and accuracy metrics.

Use of job-exposure matrices to estimate occupational exposure to pesticides: A review.

PubMed

Carles, Camille; Bouvier, Ghislaine; Lebailly, Pierre; Baldi, Isabelle

2017-03-01

The health effects of pesticides have been extensively studied in epidemiology, mainly in agricultural populations. However, pesticide exposure assessment remains a key methodological issue for epidemiological studies. Besides self-reported information, expert assessment or metrology, job-exposure matrices still appear to be an interesting tool. We reviewed all existing matrices assessing occupational exposure to pesticides in epidemiological studies and described the exposure parameters they included. We identified two types of matrices, (i) generic ones that are generally used in case-control studies and document broad categories of pesticides in a large range of jobs, and (ii) specific matrices, developed for use in agricultural cohorts, that generally provide exposure metrics at the active ingredient level. The various applications of these matrices in epidemiological studies have proven that they are valuable tools to assess pesticide exposure. Specific matrices are particularly promising for use in agricultural cohorts. However, results obtained with matrices have rarely been compared with those obtained with other tools. In addition, the external validity of the given estimates has not been adequately discussed. Yet, matrices would help in reducing misclassification and in quantifying cumulated exposures, to improve knowledge about the chronic health effects of pesticides.

Stochastic local operations and classical communication (SLOCC) and local unitary operations (LU) classifications of n qubits via ranks and singular values of the spin-flipping matrices

NASA Astrophysics Data System (ADS)

Li, Dafa

2018-06-01

We construct ℓ -spin-flipping matrices from the coefficient matrices of pure states of n qubits and show that the ℓ -spin-flipping matrices are congruent and unitary congruent whenever two pure states of n qubits are SLOCC and LU equivalent, respectively. The congruence implies the invariance of ranks of the ℓ -spin-flipping matrices under SLOCC and then permits a reduction of SLOCC classification of n qubits to calculation of ranks of the ℓ -spin-flipping matrices. The unitary congruence implies the invariance of singular values of the ℓ -spin-flipping matrices under LU and then permits a reduction of LU classification of n qubits to calculation of singular values of the ℓ -spin-flipping matrices. Furthermore, we show that the invariance of singular values of the ℓ -spin-flipping matrices Ω 1^{(n)} implies the invariance of the concurrence for even n qubits and the invariance of the n-tangle for odd n qubits. Thus, the concurrence and the n-tangle can be used for LU classification and computing the concurrence and the n-tangle only performs additions and multiplications of coefficients of states.

Matrix computations in MACSYMA

NASA Technical Reports Server (NTRS)

Wang, P. S.

1977-01-01

Facilities built into MACSYMA for manipulating matrices with numeric or symbolic entries are described. Computations will be done exactly, keeping symbols as symbols. Topics discussed include how to form a matrix and create other matrices by transforming existing matrices within MACSYMA; arithmetic and other computation with matrices; and user control of computational processes through the use of optional variables. Two algorithms designed for sparse matrices are given. The computing times of several different ways to compute the determinant of a matrix are compared.

Complex symmetric matrices with strongly stable iterates

NASA Technical Reports Server (NTRS)

Tadmor, E.

1985-01-01

Complex-valued symmetric matrices are studied. A simple expression for the spectral norm of such matrices is obtained, by utilizing a unitarily congruent invariant form. A sharp criterion is provided for identifying those symmetric matrices whose spectral norm is not exceeding one: such strongly stable matrices are usually sought in connection with convergent difference approximations to partial differential equations. As an example, the derived criterion is applied to conclude the strong stability of a Lax-Wendroff scheme.

Calculation of controllability and observability matrices for special case of continuous-time multi-order fractional systems.

PubMed

Hassanzadeh, Iman; Tabatabaei, Mohammad

2017-03-28

In this paper, controllability and observability matrices for pseudo upper or lower triangular multi-order fractional systems are derived. It is demonstrated that these systems are controllable and observable if and only if their controllability and observability matrices are full rank. In other words, the rank of these matrices should be equal to the inner dimension of their corresponding state space realizations. To reduce the computational complexities, these matrices are converted to simplified matrices with smaller dimensions. Numerical examples are provided to show the usefulness of the mentioned matrices for controllability and observability analysis of this case of multi-order fractional systems. These examples clarify that the duality concept is not necessarily true for these special systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Determination of the optimal number of components in independent components analysis.

PubMed

Kassouf, Amine; Jouan-Rimbaud Bouveresse, Delphine; Rutledge, Douglas N

2018-03-01

Independent components analysis (ICA) may be considered as one of the most established blind source separation techniques for the treatment of complex data sets in analytical chemistry. Like other similar methods, the determination of the optimal number of latent variables, in this case, independent components (ICs), is a crucial step before any modeling. Therefore, validation methods are required in order to decide about the optimal number of ICs to be used in the computation of the final model. In this paper, three new validation methods are formally presented. The first one, called Random_ICA, is a generalization of the ICA_by_blocks method. Its specificity resides in the random way of splitting the initial data matrix into two blocks, and then repeating this procedure several times, giving a broader perspective for the selection of the optimal number of ICs. The second method, called KMO_ICA_Residuals is based on the computation of the Kaiser-Meyer-Olkin (KMO) index of the transposed residual matrices obtained after progressive extraction of ICs. The third method, called ICA_corr_y, helps to select the optimal number of ICs by computing the correlations between calculated proportions and known physico-chemical information about samples, generally concentrations, or between a source signal known to be present in the mixture and the signals extracted by ICA. These three methods were tested using varied simulated and experimental data sets and compared, when necessary, to ICA_by_blocks. Results were relevant and in line with expected ones, proving the reliability of the three proposed methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Fast evaluation of scaled opposite spin second-order Møller-Plesset correlation energies using auxiliary basis expansions and exploiting sparsity.

PubMed

Jung, Yousung; Shao, Yihan; Head-Gordon, Martin

2007-09-01

The scaled opposite spin Møller-Plesset method (SOS-MP2) is an economical way of obtaining correlation energies that are computationally cheaper, and yet, in a statistical sense, of higher quality than standard MP2 theory, by introducing one empirical parameter. But SOS-MP2 still has a fourth-order scaling step that makes the method inapplicable to very large molecular systems. We reduce the scaling of SOS-MP2 by exploiting the sparsity of expansion coefficients and local integral matrices, by performing local auxiliary basis expansions for the occupied-virtual product distributions. To exploit sparsity of 3-index local quantities, we use a blocking scheme in which entire zero-rows and columns, for a given third global index, are deleted by comparison against a numerical threshold. This approach minimizes sparse matrix book-keeping overhead, and also provides sufficiently large submatrices after blocking, to allow efficient matrix-matrix multiplies. The resulting algorithm is formally cubic scaling, and requires only moderate computational resources (quadratic memory and disk space) and, in favorable cases, is shown to yield effective quadratic scaling behavior in the size regime we can apply it to. Errors associated with local fitting using the attenuated Coulomb metric and numerical thresholds in the blocking procedure are found to be insignificant in terms of the predicted relative energies. A diverse set of test calculations shows that the size of system where significant computational savings can be achieved depends strongly on the dimensionality of the system, and the extent of localizability of the molecular orbitals. Copyright 2007 Wiley Periodicals, Inc.

Almost commuting self-adjoint matrices: The real and self-dual cases

NASA Astrophysics Data System (ADS)

Loring, Terry A.; Sørensen, Adam P. W.

2016-08-01

We show that a pair of almost commuting self-adjoint, symmetric matrices is close to a pair of commuting self-adjoint, symmetric matrices (in a uniform way). Moreover, we prove that the same holds with self-dual in place of symmetric and also for paths of self-adjoint matrices. Since a symmetric, self-adjoint matrix is real, we get a real version of Huaxin Lin’s famous theorem on almost commuting matrices. Similarly, the self-dual case gives a version for matrices over the quaternions. To prove these results, we develop a theory of semiprojectivity for real C*-algebras and also examine various definitions of low-rank for real C*-algebras.

Overlaid caption extraction in news video based on SVM

NASA Astrophysics Data System (ADS)

Liu, Manman; Su, Yuting; Ji, Zhong

2007-11-01

Overlaid caption in news video often carries condensed semantic information which is key cues for content-based video indexing and retrieval. However, it is still a challenging work to extract caption from video because of its complex background and low resolution. In this paper, we propose an effective overlaid caption extraction approach for news video. We first scan the video key frames using a small window, and then classify the blocks into the text and non-text ones via support vector machine (SVM), with statistical features extracted from the gray level co-occurrence matrices, the LH and HL sub-bands wavelet coefficients and the orientated edge intensity ratios. Finally morphological filtering and projection profile analysis are employed to localize and refine the candidate caption regions. Experiments show its high performance on four 30-minute news video programs.

Oxygen plasma resistant phosphine oxide containing imide/arylene copolymers

NASA Technical Reports Server (NTRS)

Jensen, Brian J.

1993-01-01

A series of oxygen plasma resistant imide/arylene ether copolymers were prepared by reacting anhydride-terminated poly(amide acids) and amine-terminated polyarylene ethers containing phosphine oxide units. Inherent viscosities for these copolymers ranged from 0.42 to 0.80 dL/g. After curing, the resulting copolymers had glass transition temperatures ranging from 224 C to 228 C. Solution cast films of the block copolymers were tough and flexible with tensile strength, tensile moduli, and elongation at break up to 16.1 ksi, 439 ksi, and 23 percent, respectively at 25 C and 9.1 ksi, 308 ksi and 97 percent, respectively at 150 C. The copolymers show a significant improvement in resistance to oxygen plasma when compared to the commercial polyimide Kapton. The imide/arylene ether copolymers containing phosphine oxide units are suitable as coatings, films, adhesives, and composite matrices.

M2-brane surface operators and gauge theory dualities in Toda

NASA Astrophysics Data System (ADS)

Gomis, Jaume; Le Floch, Bruno

2016-04-01

We give a microscopic two dimensional {N} = (2, 2) gauge theory description of arbitrary M2-branes ending on N f M5-branes wrapping a punctured Riemann surface. These realize surface operators in four dimensional {N} = 2 field theories. We show that the expectation value of these surface operators on the sphere is captured by a Toda CFT correlation function in the presence of an additional degenerate vertex operator labelled by a representation {R} of SU( N f ), which also labels M2-branes ending on M5-branes. We prove that symmetries of Toda CFT correlators provide a geometric realization of dualities between two dimensional gauge theories, including {N} = (2, 2) analogues of Seiberg and Kutasov-Schwimmer dualities. As a bonus, we find new explicit conformal blocks, braiding matrices, and fusion rules in Toda CFT.

The Level and Nature of Autistic Intelligence

PubMed Central

Dawson, Michelle; Soulières, Isabelle; Ann Gernsbacher, Morton; Mottron, Laurent

2015-01-01

Autistics are presumed to be characterized by cognitive impairment, and their cognitive strengths (e.g., in Block Design performance) are frequently interpreted as low-level by-products of high-level deficits, not as direct manifestations of intelligence. Recent attempts to identify the neuroanatomical and neurofunctional signature of autism have been positioned on this universal, but untested, assumption. We therefore assessed a broad sample of 38 autistic children on the preeminent test of fluid intelligence, Raven’s Progressive Matrices. Their scores were, on average, 30 percentile points, and in some cases more than 70 percentile points, higher than their scores on the Wechsler scales of intelligence. Typically developing control children showed no such discrepancy, and a similar contrast was observed when a sample of autistic adults was compared with a sample of nonautistic adults. We conclude that intelligence has been underestimated in autistics. PMID:17680932

Decision Matrices: Tools to Enhance Middle School Engineering Instruction

ERIC Educational Resources Information Center

Gonczi, Amanda L.; Bergman, Brenda G.; Huntoon, Jackie; Allen, Robin; McIntyre, Barb; Turner, Sheri; Davis, Jen; Handler, Rob

2017-01-01

Decision matrices are valuable engineering tools. They allow engineers to objectively examine solution options. Decision matrices can be incorporated in K-12 classrooms to support authentic engineering instruction. In this article we provide examples of how decision matrices have been incorporated into 6th and 7th grade classrooms as part of an…

19 CFR 10.90 - Master records and metal matrices.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 1 2011-04-01 2011-04-01 false Master records and metal matrices. 10.90 Section... Master Records, and Metal Matrices § 10.90 Master records and metal matrices. (a) Consumption entries... made, of each master record or metal matrix covered thereby. (c) A bond on Customs Form 301, containing...

19 CFR 10.90 - Master records and metal matrices.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 1 2013-04-01 2013-04-01 false Master records and metal matrices. 10.90 Section... Master Records, and Metal Matrices § 10.90 Master records and metal matrices. (a) Consumption entries... made, of each master record or metal matrix covered thereby. (c) A bond on Customs Form 301, containing...

19 CFR 10.90 - Master records and metal matrices.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 1 2014-04-01 2014-04-01 false Master records and metal matrices. 10.90 Section... Master Records, and Metal Matrices § 10.90 Master records and metal matrices. (a) Consumption entries... made, of each master record or metal matrix covered thereby. (c) A bond on Customs Form 301, containing...

19 CFR 10.90 - Master records and metal matrices.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 1 2012-04-01 2012-04-01 false Master records and metal matrices. 10.90 Section... Master Records, and Metal Matrices § 10.90 Master records and metal matrices. (a) Consumption entries... made, of each master record or metal matrix covered thereby. (c) A bond on Customs Form 301, containing...

19 CFR 10.90 - Master records and metal matrices.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Master records and metal matrices. 10.90 Section... Master Records, and Metal Matrices § 10.90 Master records and metal matrices. (a) Consumption entries... made, of each master record or metal matrix covered thereby. (c) A bond on Customs Form 301, containing...

Self-consistent field for fragmented quantum mechanical model of large molecular systems.

PubMed

Jin, Yingdi; Su, Neil Qiang; Xu, Xin; Hu, Hao

2016-01-30

Fragment-based linear scaling quantum chemistry methods are a promising tool for the accurate simulation of chemical and biomolecular systems. Because of the coupled inter-fragment electrostatic interactions, a dual-layer iterative scheme is often employed to compute the fragment electronic structure and the total energy. In the dual-layer scheme, the self-consistent field (SCF) of the electronic structure of a fragment must be solved first, then followed by the updating of the inter-fragment electrostatic interactions. The two steps are sequentially carried out and repeated; as such a significant total number of fragment SCF iterations is required to converge the total energy and becomes the computational bottleneck in many fragment quantum chemistry methods. To reduce the number of fragment SCF iterations and speed up the convergence of the total energy, we develop here a new SCF scheme in which the inter-fragment interactions can be updated concurrently without converging the fragment electronic structure. By constructing the global, block-wise Fock matrix and density matrix, we prove that the commutation between the two global matrices guarantees the commutation of the corresponding matrices in each fragment. Therefore, many highly efficient numerical techniques such as the direct inversion of the iterative subspace method can be employed to converge simultaneously the electronic structure of all fragments, reducing significantly the computational cost. Numerical examples for water clusters of different sizes suggest that the method shall be very useful in improving the scalability of fragment quantum chemistry methods. © 2015 Wiley Periodicals, Inc.

Amyloid fibril systems reduce, stabilize and deliver bioavailable nanosized iron

NASA Astrophysics Data System (ADS)

Shen, Yi; Posavec, Lidija; Bolisetty, Sreenath; Hilty, Florentine M.; Nyström, Gustav; Kohlbrecher, Joachim; Hilbe, Monika; Rossi, Antonella; Baumgartner, Jeannine; Zimmermann, Michael B.; Mezzenga, Raffaele

2017-07-01

Iron-deficiency anaemia (IDA) is a major global public health problem. A sustainable and cost-effective strategy to reduce IDA is iron fortification of foods, but the most bioavailable fortificants cause adverse organoleptic changes in foods. Iron nanoparticles are a promising solution in food matrices, although their tendency to oxidize and rapidly aggregate in solution severely limits their use in fortification. Amyloid fibrils are protein aggregates initially known for their association with neurodegenerative disorders, but recently described in the context of biological functions in living organisms and emerging as unique biomaterial building blocks. Here, we show an original application for these protein fibrils as efficient carriers for iron fortification. We use biodegradable amyloid fibrils from β-lactoglobulin, an inexpensive milk protein with natural reducing effects, as anti-oxidizing nanocarriers and colloidal stabilizers for iron nanoparticles. The resulting hybrid material forms a stable protein-iron colloidal dispersion that undergoes rapid dissolution and releases iron ions during acidic and enzymatic in vitro digestion. Importantly, this hybrid shows high in vivo iron bioavailability, equivalent to ferrous sulfate in haemoglobin-repletion and stable-isotope studies in rats, but with reduced organoleptic changes in foods. Feeding the rats with these hybrid materials did not result in abnormal iron accumulation in any organs, or changes in whole blood glutathione concentrations, inferring their primary safety. Therefore, these iron-amyloid fibril hybrids emerge as novel, highly effective delivery systems for iron in both solid and liquid matrices.

Crosslinked type II collagen matrices: preparation, characterization, and potential for cartilage engineering.

PubMed

Pieper, J S; van der Kraan, P M; Hafmans, T; Kamp, J; Buma, P; van Susante, J L C; van den Berg, W B; Veerkamp, J H; van Kuppevelt, T H

2002-08-01

The limited intrinsic repair capacity of articular cartilage has stimulated continuing efforts to develop tissue engineered analogues. Matrices composed of type II collagen and chondroitin sulfate (CS), the major constituents of hyaline cartilage, may create an appropriate environment for the generation of cartilage-like tissue. In this study, we prepared, characterized, and evaluated type 11 collagen matrices with and without CS. Type II collagen matrices were prepared using purified, pepsin-treated, type II collagen. Techniques applied to prepare type I collagen matrices were found unsuitable for type II collagen. Crosslinking of collagen and covalent attachment of CS was performed using 1-ethyl-3-(3-dimethyl aminopropyl)carbodiimide. Porous matrices were prepared by freezing and lyophilization, and their physico-chemical characteristics (degree of crosslinking, denaturing temperature, collagenase-resistance, amount of CS incorporated) established. Matrices were evaluated for their capacity to sustain chondrocyte proliferation and differentiation in vitro. After 7 d of culture, chondrocytes were mainly located at the periphery of the matrices. In contrast to type I collagen, type II collagen supported the distribution of cells throughout the matrix. After 14 d of culture, matrices were surfaced with a cartilagenous-like layer, and occasionally clusters of chondrocytes were present inside the matrix. Chondrocytes proliferated and differentiated as indicated by biochemical analyses, ultrastructural observations, and reverse transcriptase PCR for collagen types I, II and X. No major differences were observed with respect to the presence or absence of CS in the matrices.

Approximate tensor-product preconditioners for very high order discontinuous Galerkin methods

NASA Astrophysics Data System (ADS)

Pazner, Will; Persson, Per-Olof

2018-02-01

In this paper, we develop a new tensor-product based preconditioner for discontinuous Galerkin methods with polynomial degrees higher than those typically employed. This preconditioner uses an automatic, purely algebraic method to approximate the exact block Jacobi preconditioner by Kronecker products of several small, one-dimensional matrices. Traditional matrix-based preconditioners require O (p2d) storage and O (p3d) computational work, where p is the degree of basis polynomials used, and d is the spatial dimension. Our SVD-based tensor-product preconditioner requires O (p d + 1) storage, O (p d + 1) work in two spatial dimensions, and O (p d + 2) work in three spatial dimensions. Combined with a matrix-free Newton-Krylov solver, these preconditioners allow for the solution of DG systems in linear time in p per degree of freedom in 2D, and reduce the computational complexity from O (p9) to O (p5) in 3D. Numerical results are shown in 2D and 3D for the advection, Euler, and Navier-Stokes equations, using polynomials of degree up to p = 30. For many test cases, the preconditioner results in similar iteration counts when compared with the exact block Jacobi preconditioner, and performance is significantly improved for high polynomial degrees p.

Selection of sugar cane families by using BLUP and multi-diverse analyses for planting in the Brazilian savannah.

PubMed

Barbosa, M H P; Ferreira, A; Peixoto, L A; Resende, M D V; Nascimento, M; Silva, F F

2014-03-12

This study evaluated different strategies to select sugar cane families and obtain clones adapted to the conditions of the Brazilian savannah. Specifically, 7 experiments were conducted, with 10 full sib families, and 2 witnesses in common to all experiments, in each experiment. The plants were grown in random blocks, with witnesses in common (incomplete blocks), and 6 repetitions of each experiment. The data were analyzed through the methodology of mixed patterns, in which the matrices of kinship between the families were identified by the method of restricted maximum likelihood. The characteristics that were evaluated included soluble solids content (BRIX), BRIX ton/ha, average mass of a culm, number of culms/m, and tons of culms/ha. A multi-diverse alternative based on the analysis of groupings by using the UPGMA method was used to identify the most viable families for selection, when considering the genotypic effects on all characteristics. This method appeared suitable for the selection of families, with 5 family groups being formed. The families that formed Group 2 appeared superior to all other families for all the evaluated characteristics. It is recommended that the families in Group 2 are preferentially used in sugar cane improvement programs to obtain varieties optimally adapted to the conditions of the Brazilian savannah.

New algorithm for tensor contractions on multi-core CPUs, GPUs, and accelerators enables CCSD and EOM-CCSD calculations with over 1000 basis functions on a single compute node.

PubMed

Kaliman, Ilya A; Krylov, Anna I

2017-04-30

A new hardware-agnostic contraction algorithm for tensors of arbitrary symmetry and sparsity is presented. The algorithm is implemented as a stand-alone open-source code libxm. This code is also integrated with general tensor library libtensor and with the Q-Chem quantum-chemistry package. An overview of the algorithm, its implementation, and benchmarks are presented. Similarly to other tensor software, the algorithm exploits efficient matrix multiplication libraries and assumes that tensors are stored in a block-tensor form. The distinguishing features of the algorithm are: (i) efficient repackaging of the individual blocks into large matrices and back, which affords efficient graphics processing unit (GPU)-enabled calculations without modifications of higher-level codes; (ii) fully asynchronous data transfer between disk storage and fast memory. The algorithm enables canonical all-electron coupled-cluster and equation-of-motion coupled-cluster calculations with single and double substitutions (CCSD and EOM-CCSD) with over 1000 basis functions on a single quad-GPU machine. We show that the algorithm exhibits predicted theoretical scaling for canonical CCSD calculations, O(N 6 ), irrespective of the data size on disk. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; Govind, Niranjan; Yang, Chao

2017-12-01

We present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.

A novel color image compression algorithm using the human visual contrast sensitivity characteristics

NASA Astrophysics Data System (ADS)

Yao, Juncai; Liu, Guizhong

2017-03-01

In order to achieve higher image compression ratio and improve visual perception of the decompressed image, a novel color image compression scheme based on the contrast sensitivity characteristics of the human visual system (HVS) is proposed. In the proposed scheme, firstly the image is converted into the YCrCb color space and divided into sub-blocks. Afterwards, the discrete cosine transform is carried out for each sub-block, and three quantization matrices are built to quantize the frequency spectrum coefficients of the images by combining the contrast sensitivity characteristics of HVS. The Huffman algorithm is used to encode the quantized data. The inverse process involves decompression and matching to reconstruct the decompressed color image. And simulations are carried out for two color images. The results show that the average structural similarity index measurement (SSIM) and peak signal to noise ratio (PSNR) under the approximate compression ratio could be increased by 2.78% and 5.48%, respectively, compared with the joint photographic experts group (JPEG) compression. The results indicate that the proposed compression algorithm in the text is feasible and effective to achieve higher compression ratio under ensuring the encoding and image quality, which can fully meet the needs of storage and transmission of color images in daily life.

Design, parametrization, and pole placement of stabilizing output feedback compensators via injective cogenerator quotient signal modules.

PubMed

Blumthaler, Ingrid; Oberst, Ulrich

2012-03-01

Control design belongs to the most important and difficult tasks of control engineering and has therefore been treated by many prominent researchers and in many textbooks, the systems being generally described by their transfer matrices or by Rosenbrock equations and more recently also as behaviors. Our approach to controller design uses, in addition to the ideas of our predecessors on coprime factorizations of transfer matrices and on the parametrization of stabilizing compensators, a new mathematical technique which enables simpler design and also new theorems in spite of the many outstanding results of the literature: (1) We use an injective cogenerator signal module ℱ over the polynomial algebra [Formula: see text] (F an infinite field), a saturated multiplicatively closed set T of stable polynomials and its quotient ring [Formula: see text] of stable rational functions. This enables the simultaneous treatment of continuous and discrete systems and of all notions of stability, called T-stability. We investigate stabilizing control design by output feedback of input/output (IO) behaviors and study the full feedback IO behavior, especially its autonomous part and not only its transfer matrix. (2) The new technique is characterized by the permanent application of the injective cogenerator quotient signal module [Formula: see text] and of quotient behaviors [Formula: see text] of [Formula: see text]-behaviors B. (3) For the control tasks of tracking, disturbance rejection, model matching, and decoupling and not necessarily proper plants we derive necessary and sufficient conditions for the existence of proper stabilizing compensators with proper and stable closed loop behaviors, parametrize all such compensators as IO behaviors and not only their transfer matrices and give new algorithms for their construction. Moreover we solve the problem of pole placement or spectral assignability for the complete feedback behavior. The properness of the full feedback behavior ensures the absence of impulsive solutions in the continuous case, and that of the compensator enables its realization by Kalman state space equations or elementary building blocks. We note that every behavior admits an IO decomposition with proper transfer matrix, but that most of these decompositions do not have this property, and therefore we do not assume the properness of the plant. (4) The new technique can also be applied to more general control interconnections according to Willems, in particular to two-parameter feedback compensators and to the recent tracking framework of Fiaz/Takaba/Trentelman. In contrast to these authors, however, we pay special attention to the properness of all constructed transfer matrices which requires more subtle algorithms.

Matrices. New Topics for Secondary School Mathematics: Materials and Software.

ERIC Educational Resources Information Center

North Carolina School of Science and Mathematics. Dept. of Mathematics and Computer Science.

This material on matrices is part of "Introduction to College Mathematics" (ICM), designed to prepare high school students who have students who have completed algebra II for the variety of mathematics they will encounter in college and beyond. The concept goals of this unit are to use matrices to model real-world phenomena, to use matrices as…

Generalized matrix summability of a conjugate derived Fourier series.

PubMed

Mursaleen, M; Alotaibi, Abdullah

2017-01-01

The study of infinite matrices is important in the theory of summability and in approximation. In particular, Toeplitz matrices or regular matrices and almost regular matrices have been very useful in this context. In this paper, we propose to use a more general matrix method to obtain necessary and sufficient conditions to sum the conjugate derived Fourier series.

Rhotrix Vector Spaces

ERIC Educational Resources Information Center

Aminu, Abdulhadi

2010-01-01

By rhotrix we understand an object that lies in some way between (n x n)-dimensional matrices and (2n - 1) x (2n - 1)-dimensional matrices. Representation of vectors in rhotrices is different from the representation of vectors in matrices. A number of vector spaces in matrices and their properties are known. On the other hand, little seems to be…

Commutative semigroups of real and complex matrices. [with use of the jordan form

NASA Technical Reports Server (NTRS)

Brown, D. R.

1974-01-01

The computation of divergence is studied. Covariance matrices to be analyzed admit a common diagonalization, or even triangulation. Sufficient conditions are given for such phenomena to take place, the arguments cover both real and complex matrices, and are not restricted to Hermotian or other special forms. Specifically, it is shown to be sufficient that the matrices in question commute in order to admit a common triangulation. Several results hold in the case that the matrices in question form a closed and bounded set, rather than only in the finite case.

Field matric potential sensor

DOEpatents

Hubbell, Joel M.; Sisson, James B.

2001-01-01

A method of determining matric potential of a sample, the method comprising placing the sample in a container, the container having an opening; and contacting the sample with a tensiometer via the opening. An apparatus for determining matric potential of a sample, the apparatus comprising a housing configured to receive a sample; a portable matric potential sensing device extending into the housing and having a porous member; and a wall closing the housing to insulate the sample and at least a portion of the matric potential sensing device including the porous member.

Time-Resolved Nucleic Acid Hybridization Beacons Utilizing Unimolecular and Toehold-Mediated Strand Displacement Designs.

PubMed

Massey, Melissa; Ancona, Mario G; Medintz, Igor L; Algar, W Russ

2015-12-01

Nucleic acid hybridization probes are sought after for numerous assay and imaging applications. These probes are often limited by the properties of fluorescent dyes, prompting the development of new probes where dyes are paired with novel or nontraditional luminescent materials. Luminescent terbium complexes are an example of such a material, and these complexes offer several unique spectroscopic advantages. Here, we demonstrate two nonstem-loop designs for light-up nucleic acid hybridization beacons that utilize time-resolved Förster resonance energy transfer (TR-FRET) between a luminescent Lumi4-Tb cryptate (Tb) donor and a fluorescent reporter dye, where time-resolved emission from the dye provides an analytical signal. Both designs are based on probe oligonucleotides that are labeled at their opposite termini with Tb and a fluorescent reporter dye. In one design, a probe is partially blocked with a quencher dye-labeled oligonucleotide, and target hybridization is signaled through toehold-mediated strand displacement and loss of a competitive FRET pathway. In the other design, the intrinsic folding properties of an unblocked probe are utilized in combination with a temporal mechanism for signaling target hybridization. This temporal mechanism is based on a recently elucidated "sweet spot" for TR-FRET measurements and exploits distance control over FRET efficiencies to shift the Tb lifetime within or outside the time-gated detection window for measurements. Both the blocked and unblocked beacons offer nanomolar (femtomole) detection limits, response times on the order of minutes, multiplexing through the use of different reporter dyes, and detection in complex matrices such as serum and blood. The blocked beacons offer better mismatch selectivity, whereas the unblocked beacons are simpler in design. The temporal mechanism of signaling utilized with the unblocked beacons also plays a significant role with the blocked beacons and represents a new and effective strategy for developing FRET probes for bioassays.

Multiscale analysis of the fracture pattern in granite, example of Tamariu's granite, Catalunya.

NASA Astrophysics Data System (ADS)

Bertrand, L.; LeGarzic, E.; Géraud, Y.; Diraison, M.

2012-04-01

Crystalline rocks can be the host of important fluid flow and therefore they can provide a good reservoir potential. In this kind of rocks, the matrice porosity is in general low and a large part of the permeability is governed by the fracture pattern. Thus, they are the first interest of studies in order to characterize and model the fluid flows. Actual reservoirs are underground, and the only access to the fracture pattern is with boreholes and seismic lines. Those methods are investigating different scales and dimensions: seismic is in 3D at a global scale whereas boreholes are 1D at a localized scale. To make the link between the different data, it is necessary to study field analogues where such fractured rocks are outcropping. Tamariu's granite, in Catalunya, has recently been studied as a field analogue of a fractured reservoir. The previous studies have lead to define structural blocks at different scales, linked to the regional deformation. This study's aim is to characterize the internal fracturation of a single structural block with a statistical analysis. We used one dimension scan lines at the scale of a block and 2 dimensions mapping at a more precise scale until the grain scale. The data highlighted that the fracture and fault lengths have a power law relation in 8 orders of scales. So this power law is stretching between seismic and borehole scales. Therefore, the data fit with a very good trust in the power law exponent, which is very well defined. The link between the reservoir scale faults and the internal block fracturation has also been defined in term of the structures orientation. Finally, a comparison between the 1D and 2D measurement could be done. The 1D scan lines show correctly the different fractures families but samples incompletely a part the fracture pattern, whereas the 2D maps which show more the global trends of the fractures and could lose some minor trends orientations.

On the application of under-decimated filter banks

NASA Technical Reports Server (NTRS)

Lin, Y.-P.; Vaidyanathan, P. P.

1994-01-01

Maximally decimated filter banks have been extensively studied in the past. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding. Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate. However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed. In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution. This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving. In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels. Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform (DFT) filter banks and the cosine modulated filter banks. They are well known for their low complexity. In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate. Furthermore, for both systems, the implementation cost of the analysis or synthesis bank is comparable to that of one prototype filter plus some low-complexity modulation matrices. The individual analysis and synthesis filters have complex coefficients in the DFT filter banks but have real coefficients in the cosine modulated filter banks.

On the application of under-decimated filter banks

NASA Astrophysics Data System (ADS)

Lin, Y.-P.; Vaidyanathan, P. P.

1994-11-01

Maximally decimated filter banks have been extensively studied in the past. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding. Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate. However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed. In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution. This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving. In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels. Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform (DFT) filter banks and the cosine modulated filter banks. They are well known for their low complexity. In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate.

The underexposed role of food matrices in probiotic products: Reviewing the relationship between carrier matrices and product parameters.

PubMed

Flach, Joost; van der Waal, Mark B; van den Nieuwboer, Maurits; Claassen, Eric; Larsen, Olaf F A

2017-06-13

Probiotic microorganisms are increasingly incorporated into food matrices in order to confer proposed health benefits on the consumer. It is important that the health benefits, sensory properties, shelf-life and probiotic gastrointestinal tract (GIT) survival of these products are carefully balanced as they determine functionality and drive consumer acceptance. The strain-specific effects of probiotic species are imperative in this process but carrier matrices may play a pivotal role as well. This study therefore recapitulates the wealth of knowledge on carrier matrices and their interaction with probiotic strains. The most substantiated carrier matrices, factors that influence probiotic functionality and matrix effects on shelf-life, GIT survival and clinical efficacy are reviewed. Results indicate that carrier matrices have a significant impact on the quality of probiotic products. Matrix components, such as proteins, carbohydrates and flavoring agents are shown to alter probiotic efficacy and viability. In vivo studies furthermore revealed strain-dependent matrix effects on the GIT survival of probiotic bacteria. However, only a limited number of studies have specifically addressed the effects of carrier matrices on the aforementioned product-parameters; most studies seem to focus solely on the strain-specific effects of probiotic microorganisms. This hampers the innovation of probiotic products. More human studies, comparing not only different probiotic strains but different carrier matrices as well, are needed to drive the innovation cycle.

Electrospun Zein/PCL Fibrous Matrices Release Tetracycline in a Controlled Manner, Killing Staphylococcus aureus Both in Biofilms and Ex Vivo on Pig Skin, and are Compatible with Human Skin Cells.

PubMed

Alhusein, Nour; Blagbrough, Ian S; Beeton, Michael L; Bolhuis, Albert; De Bank, Paul A

2016-01-01

To investigate the destruction of clinically-relevant bacteria within biofilms via the sustained release of the antibiotic tetracycline from zein-based electrospun polymeric fibrous matrices and to demonstrate the compatibility of such wound dressing matrices with human skin cells. Zein/PCL triple layered fibrous dressings with entrapped tetracycline were electrospun. The successful entrapment of tetracycline in these dressings was validated. The successful release of bioactive tetracycline, the destruction of preformed biofilms, and the viability of fibroblast (FEK4) cells were investigated. The sustained release of tetracycline from these matrices led to the efficient destruction of preformed biofilms from Staphylococcus aureus MRSA252 in vitro, and of MRSA252 and ATCC 25923 bacteria in an ex vivo pig skin model using 1 × 1 cm square matrices containing tetracycline (30 μg). Human FEK4 cells grew normally in the presence of these matrices. The ability of the zein-based matrices to destroy bacteria within increasingly complex in vitro biofilm models was clearly established. An ex vivo pig skin assay showed that these matrices, with entrapped tetracycline, efficiently kill bacteria and this, combined with their compatibility with a human skin cell line suggest these matrices are well suited for applications in wound healing and infection control.

Core-shell alginate-ghatti gum modified montmorillonite composite matrices for stomach-specific flurbiprofen delivery.

PubMed

Bera, Hriday; Ippagunta, Sohitha Reddy; Kumar, Sanoj; Vangala, Pavani

2017-07-01

Novel alginate-arabic gum (AG) gel membrane coated alginate-ghatti gum (GG) modified montmorillonite (MMT) composite matrices were developed for intragastric flurbiprofen (FLU) delivery by combining floating and mucoadhesion mechanisms. The clay-biopolymer composite matrices containing FLU as core were accomplished by ionic-gelation technique. Effects of polymer-blend (alginate:GG) ratios and crosslinker (CaCl 2 ) concentrations on drug entrapment efficiency (DEE, %) and cumulative drug release after 8h (Q 8h , %) were studied to optimize the core matrices by a 3 2 factorial design. The optimized matrices (F-O) demonstrated DEE of 91.69±1.43% and Q 8h of 74.96±1.56% with minimum errors in prediction. The alginate-AG gel membrane enveloped optimized matrices (F-O, coated) exhibited superior buoyancy, better ex vivo mucoadhesion and slower drug release rate. The drug release profile of FLU-loaded uncoated and coated optimized matrices was best fitted in Korsmeyer-Peppas model with anomalous diffusion and case-II transport driven mechanism, respectively. The uncoated and coated matrices containing FLU were also characterized for drug-excipients compatibility, drug crystallinity, thermal behaviour and surface morphology. Thus, the newly developed alginate-AG gel membrane coated alginate-GG modified MMT composite matrices are appropriate for intragastric delivery of FLU over an extended period of time with improved therapeutic benefits. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel value-added uses for sweet potato juice and flour in polyphenol- and protein-enriched functional food ingredients.

PubMed

Grace, Mary H; Truong, An N; Truong, Van-Den; Raskin, Ilya; Lila, Mary Ann

2015-09-01

Blackcurrant, blueberry, and muscadine grape juices were efficiently sorbed, concentrated, and stabilized into dry granular ingredient matrices which combined anti-inflammatory and antioxidant fruit polyphenols with sweet potato functional constituents (carotenoids, vitamins, polyphenols, fibers). Total phenolics were highest in blackcurrant-orange sweet potato ingredient matrices (34.03 mg/g), and lowest in muscadine grape-yellow sweet potato matrices (10.56 mg/g). Similarly, anthocyanins were most concentrated in blackcurrant-fortified orange and yellow sweet potato matrices (5.40 and 6.54 mg/g, respectively). Alternatively, other protein-rich edible matrices (defatted soy flour, light roasted peanut flour, and rice protein concentrate) efficiently captured polyphenols (6.09-9.46 mg/g) and anthocyanins (0.77-1.27 mg/g) from purple-fleshed sweet potato juice, with comparable efficiency. Antioxidant activity correlated well with total phenolic content. All formulated ingredient matrices stabilized and preserved polyphenols for up to 24 weeks, even when stored at 37°C. Complexation with juice-derived polyphenols did not significantly alter protein or carbohydrate profiles of the matrices. Sensory evaluation of the ingredient matrices suggested potential uses for a wide range of functional food products.

Response of rotation-translation blocked proteins using Langevin dynamics on a locally harmonic landscape.

PubMed

Manson, Anthony C; Coalson, Rob D

2012-10-11

Langevin dynamics is used to compute the time evolution of the nonequilibrium motion of the atomic coordinates of a protein in response to ligand dissociation. The protein potential energy surface (PES) is approximated by a harmonic basin about the minimum of the unliganded state. Upon ligand dissociation, the protein undergoes relaxation from the bound to the unbound state. A coarse graining scheme based on rotation translation blocks (RTB) is applied to the relaxation of the two domain iron transport protein, ferric binding protein. This scheme provides a natural and efficient way to freeze out the small amplitude, high frequency motions within each rigid fragment, thereby allowing for the number of dynamical degrees of freedom to be reduced. The results obtained from all flexible atom (constraint free) dynamics are compared to those obtained using RTB-Langevin dynamics. To assess the impact of the assumed rigid fragment clustering on the temporal relaxation dynamics of the protein molecule, three distinct rigid block decompositions were generated and their responses compared. Each of the decompositions was a variant of the one-block-per-residue grouping, with their force and friction matrices being derived from their fully flexible counterpart. Monitoring the time evolution of the distance separating a selected pair of amino acids, the response curves of the blocked decompositions were similar in shape to each other and to the control system in which all atomic degrees of freedom are fully independent. The similar shape of the blocked responses showed that the variations in grouping had only a minor impact on the kinematics. Compared with the all atom responses, however, the blocked responses were faster as a result of the instantaneous transmission of force throughout each rigid block. This occurred because rigid blocking does not permit any intrablock deformation that could store or divert energy. It was found, however, that this accelerated response could be successfully corrected by scaling each eigenvalue in the appropriate propagation matrix by the least-squares fitted slope of the blocked vs nonblocked eigenvalue spectra. The RTB responses for each test system were dominated by small eigenvalue overdamped Langevin modes. The large eigenvalue members of each response dissipated within the first 5 ps, after which the long time response was dominated by a modest set of low energy, overdamped normal modes, that were characterized by highly cooperative, functionally relevant displacements. The response assuming that the system is in the overdamped limit was compared to the full phase space Langevin dynamics results. The responses after the first 5 ps were nearly identical, confirming that the inertial components were significant only in the initial stages of the relaxation. Since the propagator matrix in the overdamped formulation is real-symmetric and does not require the inertial component in the propagator, the computation time and memory footprint was reduced by 1 order of magnitude.

Inference for High-dimensional Differential Correlation Matrices.

PubMed

Cai, T Tony; Zhang, Anru

2016-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

On Fluctuations of Eigenvalues of Random Band Matrices

NASA Astrophysics Data System (ADS)

Shcherbina, M.

2015-10-01

We consider the fluctuations of linear eigenvalue statistics of random band matrices whose entries have the form with i.i.d. possessing the th moment, where the function u has a finite support , so that M has only nonzero diagonals. The parameter b (called the bandwidth) is assumed to grow with n in a way such that . Without any additional assumptions on the growth of b we prove CLT for linear eigenvalue statistics for a rather wide class of test functions. Thus we improve and generalize the results of the previous papers (Jana et al., arXiv:1412.2445; Li et al. Random Matrices 2:04, 2013), where CLT was proven under the assumption . Moreover, we develop a method which allows to prove automatically the CLT for linear eigenvalue statistics of the smooth test functions for almost all classical models of random matrix theory: deformed Wigner and sample covariance matrices, sparse matrices, diluted random matrices, matrices with heavy tales etc.

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Homology search with binary and trinary scoring matrices.

PubMed

Smith, Scott F

2006-01-01

Protein homology search can be accelerated with the use of bit-parallel algorithms in conjunction with constraints on the values contained in the scoring matrices. Trinary scoring matrices (containing only the values -1, 0, and 1) allow for significant acceleration without significant reduction in the receiver operating characteristic (ROC) score of a Smith-Waterman search. Binary scoring matrices (containing the values 0 and 1) result in some reduction in ROC score, but result in even more acceleration. Binary scoring matrices and five-bit saturating scores can be used for fast prefilters to the Smith-Waterman algorithm.

Methods for Quantum Circuit Design and Simulation

DTIC Science & Technology

2010-03-01

cannot be deter- mined given the one output. Reversible gates, expressed mathematically, are unitary matrices. 16 3.3.1 PAULI Gates/Matrices Three...common single-qubit gates are expressed mathematically as Pauli matrices, which are 2x2 matrices. A 2x2 quantum gate can be applied to a single quantum...bit (a 2x1 column vector). The Pauli matrices are expressed as follows: X =   0 1 1 0   Y =   0 −i i 0   Z =   1 0 0 −1   (3.10) where i

An automated procedure for calculating system matrices from perturbation data generated by an EAI Pacer and 100 hybrid computer system

NASA Technical Reports Server (NTRS)

Milner, E. J.; Krosel, S. M.

1977-01-01

Techniques are presented for determining the elements of the A, B, C, and D state variable matrices for systems simulated on an EAI Pacer 100 hybrid computer. An automated procedure systematically generates disturbance data necessary to linearize the simulation model and stores these data on a floppy disk. A separate digital program verifies this data, calculates the elements of the system matrices, and prints these matrices appropriately labeled. The partial derivatives forming the elements of the state variable matrices are approximated by finite difference calculations.

Invertible flexible matrices

NASA Astrophysics Data System (ADS)

Justino, Júlia

2017-06-01

Matrices with coefficients having uncertainties of type o (.) or O (.), called flexible matrices, are studied from the point of view of nonstandard analysis. The uncertainties of the afore-mentioned kind will be given in the form of the so-called neutrices, for instance the set of all infinitesimals. Since flexible matrices have uncertainties in their coefficients, it is not possible to define the identity matrix in an unique way and so the notion of spectral identity matrix arises. Not all nonsingular flexible matrices can be turned into a spectral identity matrix using Gauss-Jordan elimination method, implying that that not all nonsingular flexible matrices have the inverse matrix. Under certain conditions upon the size of the uncertainties appearing in a nonsingular flexible matrix, a general theorem concerning the boundaries of its minors is presented which guarantees the existence of the inverse matrix of a nonsingular flexible matrix.

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

PubMed

Tan, Yen Hock; Huang, He; Kihara, Daisuke

2006-08-15

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

The Development of Novel Nanodiamond Based MALDI Matrices for the Analysis of Small Organic Pharmaceuticals

NASA Astrophysics Data System (ADS)

Chitanda, Jackson M.; Zhang, Haixia; Pahl, Erica; Purves, Randy W.; El-Aneed, Anas

2016-10-01

The utility of novel functionalized nanodiamonds (NDs) as matrices for matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) is described herein. MALDI-MS analysis of small organic compounds (<1000 Da) is typically complex because of interferences from numerous cluster ions formed when using conventional matrices. To expand the use of MALDI for the analysis of small molecules, novel matrices were designed by covalently linking conventional matrices (or a lysine moiety) to detonated NDs. Four new functionalized NDs were evaluated for their ionization capabilities using five pharmaceuticals with varying molecular structures. Two ND matrices were able to ionize all tested pharmaceuticals in the negative ion mode, producing the deprotonated ions [M - H]-. Ion intensity for target analytes was generally strong with enhanced signal-to-noise ratios compared with conventional matrices. The negative ion mode is of great importance for biological samples as interference from endogenous compounds is inherently minimized in the negative ion mode. Since the molecular structures of the tested pharmaceuticals did not suggest that negative ion mode would be preferable, this result magnifies the importance of these findings. On the other hand, conventional matrices primarily facilitated the ionization as expected in the positive ion mode, producing either the protonated molecules [M + H]+ or cationic adducts (typically producing complex spectra with numerous adduct peaks). The data presented in this study suggests that these matrices may offer advantages for the analysis of low molecular weight pharmaceuticals/metabolites.

The Development of Novel Nanodiamond Based MALDI Matrices for the Analysis of Small Organic Pharmaceuticals.

PubMed

Chitanda, Jackson M; Zhang, Haixia; Pahl, Erica; Purves, Randy W; El-Aneed, Anas

2016-10-01

The utility of novel functionalized nanodiamonds (NDs) as matrices for matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) is described herein. MALDI-MS analysis of small organic compounds (<1000 Da) is typically complex because of interferences from numerous cluster ions formed when using conventional matrices. To expand the use of MALDI for the analysis of small molecules, novel matrices were designed by covalently linking conventional matrices (or a lysine moiety) to detonated NDs. Four new functionalized NDs were evaluated for their ionization capabilities using five pharmaceuticals with varying molecular structures. Two ND matrices were able to ionize all tested pharmaceuticals in the negative ion mode, producing the deprotonated ions [M - H](-). Ion intensity for target analytes was generally strong with enhanced signal-to-noise ratios compared with conventional matrices. The negative ion mode is of great importance for biological samples as interference from endogenous compounds is inherently minimized in the negative ion mode. Since the molecular structures of the tested pharmaceuticals did not suggest that negative ion mode would be preferable, this result magnifies the importance of these findings. On the other hand, conventional matrices primarily facilitated the ionization as expected in the positive ion mode, producing either the protonated molecules [M + H](+) or cationic adducts (typically producing complex spectra with numerous adduct peaks). The data presented in this study suggests that these matrices may offer advantages for the analysis of low molecular weight pharmaceuticals/metabolites. Graphical Abstract ᅟ.

Quantization of an electromagnetic field in two-dimensional photonic structures based on the scattering matrix formalism ( S-quantization)

NASA Astrophysics Data System (ADS)

Ivanov, K. A.; Nikolaev, V. V.; Gubaydullin, A. R.; Kaliteevski, M. A.

2017-10-01

Based on the scattering matrix formalism, we have developed a method of quantization of an electromagnetic field in two-dimensional photonic nanostructures ( S-quantization in the two-dimensional case). In this method, the fields at the boundaries of the quantization box are expanded into a Fourier series and are related with each other by the scattering matrix of the system, which is the product of matrices describing the propagation of plane waves in empty regions of the quantization box and the scattering matrix of the photonic structure (or an arbitrary inhomogeneity). The quantization condition (similarly to the onedimensional case) is formulated as follows: the eigenvalues of the scattering matrix are equal to unity, which corresponds to the fact that the set of waves that are incident on the structure (components of the expansion into the Fourier series) is equal to the set of waves that travel away from the structure (outgoing waves). The coefficients of the matrix of scattering through the inhomogeneous structure have been calculated using the following procedure: the structure is divided into parallel layers such that the permittivity in each layer varies only along the axis that is perpendicular to the layers. Using the Fourier transform, the Maxwell equations have been written in the form of a matrix that relates the Fourier components of the electric field at the boundaries of neighboring layers. The product of these matrices is the transfer matrix in the basis of the Fourier components of the electric field. Represented in a block form, it is composed by matrices that contain the reflection and transmission coefficients for the Fourier components of the field, which, in turn, constitute the scattering matrix. The developed method considerably simplifies the calculation scheme for the analysis of the behavior of the electromagnetic field in structures with a two-dimensional inhomogeneity. In addition, this method makes it possible to obviate difficulties that arise in the analysis of the Purcell effect because of the divergence of the integral describing the effective volume of the mode in open systems.

Specific enrichment of a targeted nitrotyrosine-containing peptide from complex matrices and relative quantification for liquid chromatography-mass spectrometry analysis.

PubMed

Yang, Yun

2017-02-17

Protein tyrosine nitration is considered an important non-enzymatic post-translational modification. In the tyrosine nitration process, 3-nitrotyrosine is formed and recognized as a biomarker of nitrosative/nitrative stress implicated in inflammatory responses and age-related disorders. In view of the complexity of biological samples and the ultra-low abundance of protein-incorporated nitrotyrosine, selective enrichment of nitrotyrosine-containing peptides prior to chromatographic separation is crucial. Herein, I report a simple yet highly specific and efficient enrichment method for nitrotyrosine-containing peptides. After blocking all primary amines in the sample by acetylation with acetic anhydride, I then further converted all nitrotyrosine residues into aminotyrosine residues by reduction with dithiothreitol and hemin. Therefore, I eliminated the side-product with 80Da adduct, since inevitable considerable amount of which was generated in the widely used reduction mediated by sodium dithionite. Both acetylation and reduction yields were close to 100%, and my one-pot sample derivatization applied no solid phase extraction steps or sample transference to avoid sample loss. To capture and release aminotyrosine-containing peptides, I synthesized an N-hydroxysuccinimide-ester-functionalized stationary phase which had very high affinity towards amino groups and possessed a base-cleavable ester linker to retrieve targeted peptides by hydrolysis. I validated this strategy by highly efficient enrichment of the targeted peptide from complex matrices of trypsin-digested bovine serum albumin (BSA) and human plasma spiked with derivatized nitrotyrosine-containing angiotensin II. My enrichment method successfully removed most untargeted peptides in those samples. By relative quantification with home-made identical and stable-isotope labelled internal standards, I investigated the recoveries of a nitrotyrosine-containing peptide from complex biological matrices during enrichment for the first time. Mean recoveries were 49.8% and 41.1% (n=6) for the enrichment of nitrotyrosine-containing angiotensin II from 1:100 (w/w) BSA digest and from 1:10 000 (w/w) human plasma digest, respectively. My enrichment method demonstrated great potential in future applications to clinical samples and biomarker discovery. Copyright © 2017 Elsevier B.V. All rights reserved.

On Parametrization of the Linear GL(4,C) and Unitary SU(4) Groups in Terms of Dirac Matrices

NASA Astrophysics Data System (ADS)

Red'Kov, Victor M.; Bogush, Andrei A.; Tokarevskaya, Natalia G.

2008-02-01

Parametrization of 4 × 4-matrices G of the complex linear group GL(4,C) in terms of four complex 4-vector parameters (k,m,n,l) is investigated. Additional restrictions separating some subgroups of GL(4,C) are given explicitly. In the given parametrization, the problem of inverting any 4 × 4 matrix G is solved. Expression for determinant of any matrix G is found: det G = F(k,m,n,l). Unitarity conditions G+ = G-1 have been formulated in the form of non-linear cubic algebraic equations including complex conjugation. Several simplest solutions of these unitarity equations have been found: three 2-parametric subgroups G1, G2, G3 - each of subgroups consists of two commuting Abelian unitary groups; 4-parametric unitary subgroup consis! ting of a product of a 3-parametric group isomorphic SU(2) and 1-parametric Abelian group. The Dirac basis of generators Λk, being of Gell-Mann type, substantially differs from the basis λi used in the literature on SU(4) group, formulas relating them are found - they permit to separate SU(3) subgroup in SU(4). Special way to list 15 Dirac generators of GL(4,C) can be used {Λk} = {μiÅνjÅ(μiVνj = KÅL ÅM )}, which permit to factorize SU(4) transformations according to S = eiaμ eibνeikKeilLeimM, where two first factors commute with each other and are isomorphic to SU(2) group, the three last ones are 3-parametric groups, each of them consisting of three Abelian commuting unitary subgroups. Besides, the structure of fifteen Dirac matrices Λk permits to separate twenty 3-parametric subgroups in SU(4) isomorphic to SU(2); those subgroups might be used as bigger elementary blocks in constructing of a general transformation SU(4). It is shown how one can specify the present approach for the pseudounitary group SU(2,2) and SU(3,1).

Extraction and Analysis of Sulfur Mustard (HD) from Various Food Matrices by Gas ChromatographyMass Spectrometry

DTIC Science & Technology

2016-01-01

EXTRACTION AND ANALYSIS OF SULFUR MUSTARD (HD) FROM VARIOUS FOOD MATRICES BY GAS CHROMATOGRAPHY–MASS...Sulfur Mustard (HD) from Various Food Matrices by Gas Chromatography–Mass Spectrometry 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...spectrometry was used to analyze sulfur mustard (HD) in various food matrices. The development of a solid-phase extraction method using a normal

Novel value-added uses for sweet potato juice and flour in polyphenol- and protein-enriched functional food ingredients

PubMed Central

Grace, Mary H; Truong, An N; Truong, Van-Den; Raskin, Ilya; Lila, Mary Ann

2015-01-01

Blackcurrant, blueberry, and muscadine grape juices were efficiently sorbed, concentrated, and stabilized into dry granular ingredient matrices which combined anti-inflammatory and antioxidant fruit polyphenols with sweet potato functional constituents (carotenoids, vitamins, polyphenols, fibers). Total phenolics were highest in blackcurrant-orange sweet potato ingredient matrices (34.03 mg/g), and lowest in muscadine grape-yellow sweet potato matrices (10.56 mg/g). Similarly, anthocyanins were most concentrated in blackcurrant-fortified orange and yellow sweet potato matrices (5.40 and 6.54 mg/g, respectively). Alternatively, other protein-rich edible matrices (defatted soy flour, light roasted peanut flour, and rice protein concentrate) efficiently captured polyphenols (6.09–9.46 mg/g) and anthocyanins (0.77–1.27 mg/g) from purple-fleshed sweet potato juice, with comparable efficiency. Antioxidant activity correlated well with total phenolic content. All formulated ingredient matrices stabilized and preserved polyphenols for up to 24 weeks, even when stored at 37°C. Complexation with juice-derived polyphenols did not significantly alter protein or carbohydrate profiles of the matrices. Sensory evaluation of the ingredient matrices suggested potential uses for a wide range of functional food products. PMID:26405527

The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis

PubMed Central

2011-01-01

Background CADM is a statistical test used to estimate the level of Congruence Among Distance Matrices. It has been shown in previous studies to have a correct rate of type I error and good power when applied to dissimilarity matrices and to ultrametric distance matrices. Contrary to most other tests of incongruence used in phylogenetic analysis, the null hypothesis of the CADM test assumes complete incongruence of the phylogenetic trees instead of congruence. In this study, we performed computer simulations to assess the type I error rate and power of the test. It was applied to additive distance matrices representing phylogenies and to genetic distance matrices obtained from nucleotide sequences of different lengths that were simulated on randomly generated trees of varying sizes, and under different evolutionary conditions. Results Our results showed that the test has an accurate type I error rate and good power. As expected, power increased with the number of objects (i.e., taxa), the number of partially or completely congruent matrices and the level of congruence among distance matrices. Conclusions Based on our results, we suggest that CADM is an excellent candidate to test for congruence and, when present, to estimate its level in phylogenomic studies where numerous genes are analysed simultaneously. PMID:21388552

Virial expansion for almost diagonal random matrices

NASA Astrophysics Data System (ADS)

Yevtushenko, Oleg; Kravtsov, Vladimir E.

2003-08-01

Energy level statistics of Hermitian random matrices hat H with Gaussian independent random entries Higeqj is studied for a generic ensemble of almost diagonal random matrices with langle|Hii|2rangle ~ 1 and langle|Hi\

Two New Fluorogenic Aptasensors Based on Capped Mesoporous Silica Nanoparticles to Detect Ochratoxin A

PubMed Central

Ribes, Àngela; Santiago‐Felipe, Sara; Bernardos, Andrea; Marcos, M. Dolores; Pardo, Teresa; Sancenón, Félix; Aznar, Elena

2017-01-01

Abstract Aptamers have been used as recognition elements for several molecules due to their great affinity and selectivity. Additionally, mesoporous nanomaterials have demonstrated great potential in sensing applications. Based on these concepts, we report herein the use of two aptamer‐capped mesoporous silica materials for the selective detection of ochratoxin A (OTA). A specific aptamer for OTA was used to block the pores of rhodamine B‐loaded mesoporous silica nanoparticles. Two solids were prepared in which the aptamer capped the porous scaffolds by using a covalent or electrostatic approach. Whereas the prepared materials remained capped in water, dye delivery was selectively observed in the presence of OTA. The protocol showed excellent analytical performance in terms of sensitivity (limit of detection: 0.5–0.05 nm), reproducibility, and selectivity. Moreover, the aptasensors were tested for OTA detection in commercial foodstuff matrices, which demonstrated their potential applicability in real samples. PMID:29046860

A new parallel-vector finite element analysis software on distributed-memory computers

NASA Technical Reports Server (NTRS)

Qin, Jiangning; Nguyen, Duc T.

1993-01-01

A new parallel-vector finite element analysis software package MPFEA (Massively Parallel-vector Finite Element Analysis) is developed for large-scale structural analysis on massively parallel computers with distributed-memory. MPFEA is designed for parallel generation and assembly of the global finite element stiffness matrices as well as parallel solution of the simultaneous linear equations, since these are often the major time-consuming parts of a finite element analysis. Block-skyline storage scheme along with vector-unrolling techniques are used to enhance the vector performance. Communications among processors are carried out concurrently with arithmetic operations to reduce the total execution time. Numerical results on the Intel iPSC/860 computers (such as the Intel Gamma with 128 processors and the Intel Touchstone Delta with 512 processors) are presented, including an aircraft structure and some very large truss structures, to demonstrate the efficiency and accuracy of MPFEA.

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.

PubMed

Taylor, Dane; Shai, Saray; Stanley, Natalie; Mucha, Peter J

2016-06-03

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.

Two-dimensional analytical modeling of a linear variable filter for spectral order sorting.

PubMed

Ko, Cheng-Hao; Wu, Yueh-Hsun; Tsai, Jih-Run; Wang, Bang-Ji; Chakraborty, Symphony

2016-06-10

A two-dimensional thin film thickness model based on the geometry of a commercial coater which can calculate more effectively the profiles of linear variable filters (LVFs) has been developed. This is done by isolating the substrate plane as an independent coordinate (local coordinate), while the rotation and translation matrices are used to establish the coordinate transformation and combine the characteristic vector with the step function to build a borderline which can conclude whether the local mask will block the deposition or not. The height of the local mask has been increased up to 40 mm in the proposed model, and two-dimensional simulations are developed to obtain a thin film profile deposition on the substrate inside the evaporation chamber to achieve the specific request of producing a LVF zone width in a more economical way than previously reported [Opt. Express23, 5102 (2015)OPEXFF1094-408710.1364/OE.23.005102].

Transmission over UWB channels with OFDM system using LDPC coding

NASA Astrophysics Data System (ADS)

Dziwoki, Grzegorz; Kucharczyk, Marcin; Sulek, Wojciech

2009-06-01

Hostile wireless environment requires use of sophisticated signal processing methods. The paper concerns on Ultra Wideband (UWB) transmission over Personal Area Networks (PAN) including MB-OFDM specification of physical layer. In presented work the transmission system with OFDM modulation was connected with LDPC encoder/decoder. Additionally the frame and bit error rate (FER and BER) of the system was decreased using results from the LDPC decoder in a kind of turbo equalization algorithm for better channel estimation. Computational block using evolutionary strategy, from genetic algorithms family, was also used in presented system. It was placed after SPA (Sum-Product Algorithm) decoder and is conditionally turned on in the decoding process. The result is increased effectiveness of the whole system, especially lower FER. The system was tested with two types of LDPC codes, depending on type of parity check matrices: randomly generated and constructed deterministically, optimized for practical decoder architecture implemented in the FPGA device.

A biconjugate gradient type algorithm on massively parallel architectures

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Hochbruck, Marlis

1991-01-01

The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradient algorithm for Hermitian positive definite matrices to general non-Hermitian linear systems. Unfortunately, the original BCG algorithm is susceptible to possible breakdowns and numerical instabilities. Recently, Freund and Nachtigal have proposed a novel BCG type approach, the quasi-minimal residual method (QMR), which overcomes the problems of BCG. Here, an implementation is presented of QMR based on an s-step version of the nonsymmetric look-ahead Lanczos algorithm. The main feature of the s-step Lanczos algorithm is that, in general, all inner products, except for one, can be computed in parallel at the end of each block; this is unlike the other standard Lanczos process where inner products are generated sequentially. The resulting implementation of QMR is particularly attractive on massively parallel SIMD architectures, such as the Connection Machine.

The analysis of convolutional codes via the extended Smith algorithm

NASA Technical Reports Server (NTRS)

Mceliece, R. J.; Onyszchuk, I.

1993-01-01

Convolutional codes have been the central part of most error-control systems in deep-space communication for many years. Almost all such applications, however, have used the restricted class of (n,1), also known as 'rate 1/n,' convolutional codes. The more general class of (n,k) convolutional codes contains many potentially useful codes, but their algebraic theory is difficult and has proved to be a stumbling block in the evolution of convolutional coding systems. In this article, the situation is improved by describing a set of practical algorithms for computing certain basic things about a convolutional code (among them the degree, the Forney indices, a minimal generator matrix, and a parity-check matrix), which are usually needed before a system using the code can be built. The approach is based on the classic Forney theory for convolutional codes, together with the extended Smith algorithm for polynomial matrices, which is introduced in this article.

Molecular-Barrier-Enhanced Aromatic Fluorophores in Cocrystals with Unity Quantum Efficiency.

PubMed

Ye, Huanqing; Liu, Guangfeng; Liu, Sheng; Casanova, David; Ye, Xin; Tao, Xutang; Zhang, Qichun; Xiong, Qihua

2018-02-12

Singlet-triplet conversion in organic light-emitting materials introduces non-emissive (dark) and long-lived triplet states, which represents a significant challenge in constraining the optical properties. There have been considerable attempts at separating singlets and triplets in long-chain polymers, scavenging triplets, and quenching triplets with heavy metals; nonetheless, such triplet-induced loss cannot be fully eliminated. Herein, a new strategy of crafting a periodic molecular barrier into the π-conjugated matrices of organic aromatic fluorophores is reported. The molecular barriers effectively block the singlet-to-triplet pathway, resulting in near-unity photoluminescence quantum efficiency (PLQE) of the organic fluorophores. The transient optical spectroscopy measurements confirm the absence of the triplet absorption. These studies provide a general approach to preventing the formation of dark triplet states in organic semiconductors and bring new opportunities for the development of advanced organic optics and photonics. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pair Formation of Hard Core Bosons in Flat Band Systems

NASA Astrophysics Data System (ADS)

Mielke, Andreas

2018-05-01

Hard core bosons in a large class of one or two dimensional flat band systems have an upper critical density, below which the ground states can be described completely. At the critical density, the ground states are Wigner crystals. If one adds a particle to the system at the critical density, the ground state and the low lying multi particle states of the system can be described as a Wigner crystal with an additional pair of particles. The energy band for the pair is separated from the rest of the multi-particle spectrum. The proofs use a Gerschgorin type of argument for block diagonally dominant matrices. In certain one-dimensional or tree-like structures one can show that the pair is localised, for example in the chequerboard chain. For this one-dimensional system with periodic boundary condition the energy band for the pair is flat, the pair is localised.

Inference for High-dimensional Differential Correlation Matrices *

PubMed Central

Cai, T. Tony; Zhang, Anru

2015-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380

Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices

PubMed Central

Monajemi, Hatef; Jafarpour, Sina; Gavish, Matan; Donoho, David L.; Ambikasaran, Sivaram; Bacallado, Sergio; Bharadia, Dinesh; Chen, Yuxin; Choi, Young; Chowdhury, Mainak; Chowdhury, Soham; Damle, Anil; Fithian, Will; Goetz, Georges; Grosenick, Logan; Gross, Sam; Hills, Gage; Hornstein, Michael; Lakkam, Milinda; Lee, Jason; Li, Jian; Liu, Linxi; Sing-Long, Carlos; Marx, Mike; Mittal, Akshay; Monajemi, Hatef; No, Albert; Omrani, Reza; Pekelis, Leonid; Qin, Junjie; Raines, Kevin; Ryu, Ernest; Saxe, Andrew; Shi, Dai; Siilats, Keith; Strauss, David; Tang, Gary; Wang, Chaojun; Zhou, Zoey; Zhu, Zhen

2013-01-01

In compressed sensing, one takes samples of an N-dimensional vector using an matrix A, obtaining undersampled measurements . For random matrices with independent standard Gaussian entries, it is known that, when is k-sparse, there is a precisely determined phase transition: for a certain region in the (,)-phase diagram, convex optimization typically finds the sparsest solution, whereas outside that region, it typically fails. It has been shown empirically that the same property—with the same phase transition location—holds for a wide range of non-Gaussian random matrix ensembles. We report extensive experiments showing that the Gaussian phase transition also describes numerous deterministic matrices, including Spikes and Sines, Spikes and Noiselets, Paley Frames, Delsarte-Goethals Frames, Chirp Sensing Matrices, and Grassmannian Frames. Namely, for each of these deterministic matrices in turn, for a typical k-sparse object, we observe that convex optimization is successful over a region of the phase diagram that coincides with the region known for Gaussian random matrices. Our experiments considered coefficients constrained to for four different sets , and the results establish our finding for each of the four associated phase transitions. PMID:23277588

Amino acid "little Big Bang": representing amino acid substitution matrices as dot products of Euclidian vectors.

PubMed

Zimmermann, Karel; Gibrat, Jean-François

2010-01-04

Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices. We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices. This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.

Unsteady solute-transport simulation in streamflow using a finite-difference model

USGS Publications Warehouse

Land, Larry F.

1978-01-01

This report documents a rather simple, general purpose, one-dimensional, one-parameter, mass-transport model for field use. The model assumes a well-mixed conservative solute that may be coming from an unsteady source and is moving in unsteady streamflow. The quantity of solute being transported is in the units of concentration. Results are reported as such. An implicit finite-difference technique is used to solve the mass transport equation. It consists of creating a tridiagonal matrix and using the Thomas algorithm to solve the matrix for the unknown concentrations at the new time step. The computer program pesented is designed to compute the concentration of a water-quality constituent at any point and at any preselected time in a one-dimensional stream. The model is driven by the inflowing concentration of solute at the upstream boundary and is influenced by the solute entering the stream from tributaries and lateral ground-water inflow and from a source or sink. (Woodard-USGS)

Transpiration and film cooling boundary layer computer program. Volume 2: Computer program and user's manual

NASA Technical Reports Server (NTRS)

Gloss, R. J.

1971-01-01

A finite difference turbulent boundary layer computer program which allows for mass transfer wall cooling and equilibrium chemistry effects is presented. The program is capable of calculating laminar or turbulent boundary layer solutions for an arbitrary ideal gas or an equilibrium hydrogen oxygen system. Either two dimensional or axisymmetric geometric configurations may be considered. The equations are solved, in nondimension-alized physical coordinates, using the implicit Crank-Nicolson technique. The finite difference forms of the conservation of mass, momentum, total enthalpy and elements equations are linearized and uncoupled, thereby generating easily solvable tridiagonal sets of algebraic equations. A detailed description of the computer program, as well as a program user's manual is provided. Detailed descriptions of all boundary layer subroutines are included, as well as a section defining all program symbols of principal importance. Instructions are then given for preparing card input to the program and for interpreting the printed output. Finally, two sample cases are included to illustrate the use of the program.

Analytical and numerical construction of equivalent cables.

PubMed

Lindsay, K A; Rosenberg, J R; Tucker, G

2003-08-01

The mathematical complexity experienced when applying cable theory to arbitrarily branched dendrites has lead to the development of a simple representation of any branched dendrite called the equivalent cable. The equivalent cable is an unbranched model of a dendrite and a one-to-one mapping of potentials and currents on the branched model to those on the unbranched model, and vice versa. The piecewise uniform cable, with a symmetrised tri-diagonal system matrix, is shown to represent the canonical form for an equivalent cable. Through a novel application of the Laplace transform it is demonstrated that an arbitrary branched model of a dendrite can be transformed to the canonical form of an equivalent cable. The characteristic properties of the equivalent cable are extracted from the matrix for the transformed branched model. The one-to-one mapping follows automatically from the construction of the equivalent cable. The equivalent cable is used to provide a new procedure for characterising the location of synaptic contacts on spinal interneurons.

An Efficient Spectral Method for Ordinary Differential Equations with Rational Function Coefficients

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Simultaneous heat and mass transfer inside a vertical channel in evaporating a heated falling glycols liquid film

NASA Astrophysics Data System (ADS)

Nait Alla, Abderrahman; Feddaoui, M'barek; Meftah, Hicham

2015-12-01

The interactive effects of heat and mass transfer in the evaporation of ethylene and propylene glycol flowing as falling films on vertical channel was investigated. The liquid film falls along a left plate which is externally subjected to a uniform heat flux while the right plate is the dry wall and is kept thermally insulated. The model solves the coupled governing equations in both phases together with the boundary and interfacial conditions. The systems of equations obtained by using an implicit finite difference method are solved by Tridiagonal Matrix Algorithm. The influence of the inlet liquid flow, Reynolds number in the gas flow and the wall heat flux on the intensity of heat and mass transfers are examined. A comparison between the results obtained for studied glycols and water in the same conditions is made. The results indicate that water evaporates in more intense way in comparison to glycols and the increase of gas flow rate tends to improve slightly the evaporation.

Kirchhoff index of linear hexagonal chains

NASA Astrophysics Data System (ADS)

Yang, Yujun; Zhang, Heping

The resistance distance rij between vertices i and j of a connected (molecular) graph G is computed as the effective resistance between nodes i and j in the corresponding network constructed from G by replacing each edge of G with a unit resistor. The Kirchhoff index Kf(G) is the sum of resistance distances between all pairs of vertices. In this work, according to the decomposition theorem of Laplacian polynomial, we obtain that the Laplacian spectrum of linear hexagonal chain Ln consists of the Laplacian spectrum of path P2n+1 and eigenvalues of a symmetric tridiagonal matrix of order 2n + 1. By applying the relationship between roots and coefficients of the characteristic polynomial of the above matrix, explicit closed-form formula for Kirchhoff index of Ln is derived in terms of Laplacian spectrum. To our surprise, the Krichhoff index of Ln is approximately to one half of its Wiener index. Finally, we show that holds for all graphs G in a class of graphs including Ln.0

Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves

NASA Astrophysics Data System (ADS)

Qiu, Shi; Liu, Kuang; Eliasson, Veronica

2016-10-01

Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.

Computational manipulation of a radiative MHD flow with Hall current and chemical reaction in the presence of rotating fluid

NASA Astrophysics Data System (ADS)

Alias Suba, Subbu; Muthucumaraswamy, R.

2018-04-01

A numerical analysis of transient radiative MHD(MagnetoHydroDynamic) natural convective flow of a viscous, incompressible, electrically conducting and rotating fluid along a semi-infinite isothermal vertical plate is carried out taking into consideration Hall current, rotation and first order chemical reaction.The coupled non-linear partial differential equations are expressed in difference form using implicit finite difference scheme. The difference equations are then reduced to a system of linear algebraic equations with a tri-diagonal structure which is solved by Thomas Algorithm. The primary and secondary velocity profiles, temperature profile, concentration profile, skin friction, Nusselt number and Sherwood Number are depicted graphically for a range of values of rotation parameter, Hall parameter,magnetic parameter, chemical reaction parameter, radiation parameter, Prandtl number and Schmidt number.It is recognized that rate of heat transfer and rate of mass transfer decrease with increase in time but they increase with increasing values of radiation parameter and Schmidt number respectively.

Computer programs for smoothing and scaling airfoil coordinates

NASA Technical Reports Server (NTRS)

Morgan, H. L., Jr.

1983-01-01

Detailed descriptions are given of the theoretical methods and associated computer codes of a program to smooth and a program to scale arbitrary airfoil coordinates. The smoothing program utilizes both least-squares polynomial and least-squares cubic spline techniques to smooth interatively the second derivatives of the y-axis airfoil coordinates with respect to a transformed x-axis system which unwraps the airfoil and stretches the nose and trailing-edge regions. The corresponding smooth airfoil coordinates are then determined by solving a tridiagonal matrix of simultaneous cubic-spline equations relating the y-axis coordinates and their corresponding second derivatives. A technique for computing the camber and thickness distribution of the smoothed airfoil is also discussed. The scaling program can then be used to scale the thickness distribution generated by the smoothing program to a specific maximum thickness which is then combined with the camber distribution to obtain the final scaled airfoil contour. Computer listings of the smoothing and scaling programs are included.

Three dimensional iterative beam propagation method for optical waveguide devices

NASA Astrophysics Data System (ADS)

Ma, Changbao; Van Keuren, Edward

2006-10-01

The finite difference beam propagation method (FD-BPM) is an effective model for simulating a wide range of optical waveguide structures. The classical FD-BPMs are based on the Crank-Nicholson scheme, and in tridiagonal form can be solved using the Thomas method. We present a different type of algorithm for 3-D structures. In this algorithm, the wave equation is formulated into a large sparse matrix equation which can be solved using iterative methods. The simulation window shifting scheme and threshold technique introduced in our earlier work are utilized to overcome the convergence problem of iterative methods for large sparse matrix equation and wide-angle simulations. This method enables us to develop higher-order 3-D wide-angle (WA-) BPMs based on Pade approximant operators and the multistep method, which are commonly used in WA-BPMs for 2-D structures. Simulations using the new methods will be compared to the analytical results to assure its effectiveness and applicability.

Quantification of VX Nerve Agent in Various Food Matrices by Solid-Phase Extraction Ultra-Performance Liquid ChromatographyTime-of-Flight Mass Spectrometry

DTIC Science & Technology

2016-04-01

QUANTIFICATION OF VX NERVE AGENT IN VARIOUS FOOD MATRICES BY SOLID-PHASE EXTRACTION ULTRA-PERFORMANCE...TITLE AND SUBTITLE Quantification of VX Nerve Agent in Various Food Matrices by Solid-Phase Extraction Ultra-Performance Liquid Chromatography... food matrices. The mixed-mode cation exchange (MCX) sorbent and Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) methods were used for

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.

Surveying the quantum group symmetries of integrable open spin chains

NASA Astrophysics Data System (ADS)

Nepomechie, Rafael I.; Retore, Ana L.

2018-05-01

Using anisotropic R-matrices associated with affine Lie algebras g ˆ (specifically, A2n(2), A2n-1 (2) , Bn(1), Cn(1), Dn(1)) and suitable corresponding K-matrices, we construct families of integrable open quantum spin chains of finite length, whose transfer matrices are invariant under the quantum group corresponding to removing one node from the Dynkin diagram of g ˆ . We show that these transfer matrices also have a duality symmetry (for the cases Cn(1) and Dn(1)) and additional Z2 symmetries that map complex representations to their conjugates (for the cases A2n-1 (2) , Bn(1) and Dn(1)). A key simplification is achieved by working in a certain "unitary" gauge, in which only the unbroken symmetry generators appear. The proofs of these symmetries rely on some new properties of the R-matrices. We use these symmetries to explain the degeneracies of the transfer matrices.

Efficient linear algebra routines for symmetric matrices stored in packed form.

PubMed

Ahlrichs, Reinhart; Tsereteli, Kakha

2002-01-30

Quantum chemistry methods require various linear algebra routines for symmetric matrices, for example, diagonalization or Cholesky decomposition for positive matrices. We present a small set of these basic routines that are efficient and minimize memory requirements.

ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.

PubMed

Fan, Jianqing; Rigollet, Philippe; Wang, Weichen

High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓ r norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics.

ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES

PubMed Central

Fan, Jianqing; Rigollet, Philippe; Wang, Weichen

2016-01-01

High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓr norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics. PMID:26806986

A Study on the Application of the Extended Matrices Based on TRIZ in Constructing a Collaborative Model of Enterprise Network

NASA Astrophysics Data System (ADS)

Yang, Yan; Shao, Yunfei; Tang, Xiaowo

Based on mass related literature on enterprise network, the key influence factors are reduced to Trust, Control, Relationship and Interaction. Meanwhile, the specific contradiction matrices, judgment matrices and strategy collections based on TRIZ are constructed which make the connotation of contradiction matrices in TRIZ extended. Finally they are applied to the construction of the collaborative model on enterprise network based on Multi Agent System (MAS).

Stimulating effect of graphene oxide on myogenesis of C2C12 myoblasts on RGD peptide-decorated PLGA nanofiber matrices.

PubMed

Shin, Yong Cheol; Lee, Jong Ho; Kim, Min Jeong; Hong, Suck Won; Kim, Bongju; Hyun, Jung Keun; Choi, Yu Suk; Park, Jong-Chul; Han, Dong-Wook

2015-01-01

In the field of biomedical engineering, many studies have focused on the possible applications of graphene and related nanomaterials due to their potential for use as scaffolds, coating materials and delivery carriers. On the other hand, electrospun nanofiber matrices composed of diverse biocompatible polymers have attracted tremendous attention for tissue engineering and regenerative medicine. However, their combination is intriguing and still challenging. In the present study, we fabricated nanofiber matrices composed of M13 bacteriophage with RGD peptide displayed on its surface (RGD-M13 phage) and poly(lactic-co-glycolic acid, PLGA) and characterized their physicochemical properties. In addition, the effect of graphene oxide (GO) on the cellular behaviors of C2C12 myoblasts, which were cultured on PLGA decorated with RGD-M13 phage (RGD/PLGA) nanofiber matrices, was investigated. Our results revealed that the RGD/PLGA nanofiber matrices have suitable physicochemical properties as a tissue engineering scaffold and the growth of C2C12 myoblasts were significantly enhanced on the matrices. Moreover, the myogenic differentiation of C2C12 myoblasts was substantially stimulated when they were cultured on the RGD/PLGA matrices in the presence of GO. In conclusion, these findings propose that the combination of RGD/PLGA nanofiber matrices and GO can be used as a promising strategy for skeletal tissue engineering and regeneration.

Electrospun Poly(lactic acid-co-glycolic acid) Scaffolds for Skin Tissue Engineering

PubMed Central

Kumbar, Sangamesh G.; Nukavarapu, Syam Prasad; James, Roshan; Nair, Lakshmi S.; Laurencin, Cato T.

2008-01-01

Electrospun fiber matrices composed of scaffolds of varying fiber diameters were investigated for potential application of severe skin loss. Few systematic studies have been performed to examine the effect of varying fiber diameter electrospun fiber matrices for skin regeneration. The present study reports the fabrication of poly[lactic acid-co-glycolic acid] (PLAGA) matrices with fiber diameters of 150–225, 200–300, 250–467, 500–900, 600–1200, 2500–3000 and 3250–6000 nm via electrospinning. All fiber matrices found to have a tensile modulus from 39.23 ± 8.15 to 79.21 ± 13.71 MPa which falls in the range for normal human skin. Further, the porous fiber matrices have porosity between 38–60 % and average pore diameters between 10–14µm. We evaluated the efficacy of these biodegradable fiber matrices as skin substitutes by seeding them with human skin fibroblasts (hSF). Human skin fibroblasts acquired a well spread morphology and showed significant progressive growth on fiber matrices in the 350–1100 nm diameter range. Collagen type III gene expression was significantly up-regulated in hSF seeded on matrices with fiber diameters in the range of 350–1100 nm. Based on the need, the proposed fiber skin substitutes can be successfully fabricated and optimized for skin fibroblast attachment and growth. PMID:18639927

Redistribution of Sr and rare earth elements in the matrices of CV3 carbonaceous chondrites during aqueous alteration in their parent body

NASA Astrophysics Data System (ADS)

Jogo, Kaori; Ito, Motoo; Nakamura, Tomoki; Kobayashi, Sachio; Lee, Jong Ik

2018-03-01

We measured the abundances of Sr and rare earth elements (REEs) in the matrices of five CV3 carbonaceous chondrites: Meteorite Hills (MET) 00430, MET 01070, La Paz ice field (LAP) 02206, Asuka (A) 881317 and Roberts Massif (RBT) 04143. In the MET 00430 and MET 01074 matrices, the Sr/CI and light REE (LREE, La-Nd)/CI ratios positively correlate with the amounts of Ca-rich secondary minerals, which formed during aqueous alteration in the CV3 chondrite parent body. In contrast, in the LAP 02206 and RBT 04143 matrices, although the Sr/CI ratios correlate with the amounts of Ca-rich secondary minerals, the LREE/CI ratios vary independently from the amounts of any secondary minerals. This suggests that the LREE/CI ratios in these matrices were produced prior to the parent body alteration, probably in the solar nebula. The LREE/CI ratios of the LAP 02206 and RBT 04143 matrices reveal the mixing process of matrix minerals prior to the accretion of the CV3 chondrite parent body. The mixing degrees of matrix minerals might be different between these two matrices. Because solid materials would be mixed over time according to the radial diffusion model of a turbulent disk, the matrix minerals consisting of LAP 02206 and RBT 04143 matrices might be incorporated into their parent body with different timing.

Actomyosin tension as a determinant of metastatic cancer mechanical tropism

NASA Astrophysics Data System (ADS)

McGrail, Daniel J.; Kieu, Quang Minh N.; Iandoli, Jason A.; Dawson, Michelle R.

2015-04-01

Despite major advances in the characterization of molecular regulators of cancer growth and metastasis, patient survival rates have largely stagnated. Recent studies have shown that mechanical cues from the extracellular matrix can drive the transition to a malignant phenotype. Moreover, it is also known that the metastatic process, which results in over 90% of cancer-related deaths, is governed by intracellular mechanical forces. To better understand these processes, we identified metastatic tumor cells originating from different locations which undergo inverse responses to altered matrix elasticity: MDA-MB-231 breast cancer cells that prefer rigid matrices and SKOV-3 ovarian cancer cells that prefer compliant matrices as characterized by parameters such as tumor cell proliferation, chemoresistance, and migration. Transcriptomic analysis revealed higher expression of genes associated with cytoskeletal tension and contractility in cells that prefer stiff environments, both when comparing MDA-MB-231 to SKOV-3 cells as well as when comparing bone-metastatic to lung-metastatic MDA-MB-231 subclones. Using small molecule inhibitors, we found that blocking the activity of these pathways mitigated rigidity-dependent behavior in both cell lines. Probing the physical forces exerted by cells on the underlying substrates revealed that though force magnitude may not directly correlate with functional outcomes, other parameters such as force polarization do correlate directly with cell motility. Finally, this biophysical analysis demonstrates that intrinsic levels of cell contractility determine the matrix rigidity for maximal cell function, possibly influencing tissue sites for metastatic cancer cell engraftment during dissemination. By increasing our understanding of the physical interactions of cancer cells with their microenvironment, these studies may help develop novel therapeutic strategies.

Analysing generator matrices G of similar state but varying minimum determinants

NASA Astrophysics Data System (ADS)

Harun, H.; Razali, M. F.; Rahman, N. A. Abdul

2016-10-01

Since Tarokh discovered Space-Time Trellis Code (STTC) in 1998, a considerable effort has been done to improve the performance of the original STTC. One way of achieving enhancement is by focusing on the generator matrix G, which represents the encoder structure for STTC. Until now, researchers have only concentrated on STTCs of different states in analyzing the performance of generator matrix G. No effort has been made on different generator matrices G of similar state. The reason being, it is difficult to produce a wide variety of generator matrices G with diverse minimum determinants. In this paper a number of generator matrices G with minimum determinant of four (4), eight (8) and sixteen (16) of the same state (i.e., 4-PSK) have been successfully produced. The performance of different generator matrices G in term of their bit error rate and signal-to-noise ratio for a Rayleigh fading environment are compared and evaluated. It is found from the MATLAB simulation that at low SNR (<8), the BER of generator matrices G with smaller minimum determinant is comparatively lower than those of higher minimum determinant. However, at high SNR (>14) there is no significant difference between the BER of these generator matrices G.

The method of similar operators in the study of the spectra of the adjacency matrices of graphs

NASA Astrophysics Data System (ADS)

Kozlukov, Serge

2018-03-01

The method of similar operators [1, 2, 3] is used to investigate spectral properties of a certain class of matrices in the context of graphs [4, 5]. Specifically, we consider the adjacency matrix of an “almost-complete graph”. Then we generalize the result to allow the matrices obtained as combinations of the Kronecker products [6, 7] and the small-norm perturbations. We derive the estimates of the spectra and the eigenvectors of such matrices.

Extraction Methodological Contributions Toward Ultra-Performance Liquid ChromatographyTime-of-Flight Mass Spectrometry: Quantification of Free GB from Various Food Matrices

DTIC Science & Technology

2016-02-01

SPECTROMETRY: QUANTIFICATION OF FREE GB FROM VARIOUS FOOD MATRICES ECBC-TR-1351 Sue Y. Bae Mark D. Winemiller RESEARCH AND TECHNOLOGY DIRECTORATE...Flight Mass Spectrometry: Quantification of Free GB from Various Food Matrices 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...methylphosphonofluoridate (sarin, GB) in various food matrices. The development of a solid-phase extraction method using a normal-phase silica gel column for

Bunch-Kaufman factorization for real symmetric indefinite banded matrices

NASA Technical Reports Server (NTRS)

Jones, Mark T.; Patrick, Merrell L.

1989-01-01

The Bunch-Kaufman algorithm for factoring symmetric indefinite matrices was rejected for banded matrices because it destroys the banded structure of the matrix. Herein, it is shown that for a subclass of real symmetric matrices which arise in solving the generalized eigenvalue problem using Lanczos's method, the Bunch-Kaufman algorithm does not result in major destruction of the bandwidth. Space time complexities of the algorithm are given and used to show that the Bunch-Kaufman algorithm is a significant improvement over LU factorization.

EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

PubMed

Smolinska, Karolina; Pacholczyk, Marcin

2017-08-01

Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high-throughput methods such as, e.g., ChiP-seq the need to provide unbiased models of binding events has been made apparent. We present EMQIT a modification to the approach introduced by Alamanova et al. and later implemented as 3DTF server. We observed that tuning of Boltzmann factor weights, used for conversion of calculated energies to nucleotide probabilities, has a significant impact on the quality of the associated PWM matrix. Consequently, we proposed to use receiver operator characteristics curves and the 10-fold cross-validation to learn best weights using experimentally verified data from TRANSFAC database. We applied our method to data available for various TFs. We verified the efficiency of detecting TF binding sites by the 3DTF matrices improved with our technique using experimental data from the TRANSFAC database. The comparison showed a significant similarity and comparable performance between the improved and the experimental matrices (TRANSFAC). Improved 3DTF matrices achieved significantly higher AUC values than the original 3DTF matrices (at least by 0.1) and, at the same time, detected notably more experimentally verified TFBSs. The resulting new improved PWM matrices for analyzed factors show similarity to TRANSFAC matrices. Matrices had comparable predictive capabilities. Moreover, improved PWMs achieve better results than matrices downloaded from 3DTF server. Presented approach is general and applicable to any energy-based matrices. EMQIT is available online at http://biosolvers.polsl.pl:3838/emqit . This article was reviewed by Oliviero Carugo, Marek Kimmel and István Simon.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

The performance of probiotic fermented sheep milk and ice cream sheep milk in inhibiting enamel mineral loss.

PubMed

Nadelman, P; Frazão, J V; Vieira, T I; Balthazar, C F; Andrade, M M; Alexandria, A K; Cruz, A G; Fonseca-Gonçalves, A; Maia, L C

2017-07-01

The study aimed to evaluate the effects of two different sheep milk-based food matrices - fermented sheep milk and ice cream - with added probiotic bacteria (Lactobacillus casei 431) on dental enamel subjected to an in vitro highly cariogenic challenge. Sixty enamel blocks were selected and randomly allocated into five treatment groups (n=12): conventional fermented sheep milk (CFSM), probiotic fermented sheep milk (PFSM), conventional sheep milk ice cream (CSMIC), probiotic sheep milk ice cream (PSMIC) and control using deionized water. The blocks were subjected to highly cariogenic pH cycling and the products were applied (5min), in a blinded way, once a day to simulate a daily use for 8 consecutive days. A microhardness test was performed before and after the treatment to estimate the percentage of microhardness surface loss (% SML). Scanning electronic microscopy (SEM) was performed to confirm the mineral loss. All groups had lost microhardness after the experiment. However, CFSM and PFSM exhibited the most positive findings when compared to the control in both ice creams. Scanning electron microscopy showed less mineral loss in CFSM and PFSM compared with CSMIC, PSMIC and control after the cariogenic challenge. Overall, fermented milk decreased mineral loss from enamel subjected to a highly cariogenic challenge, regardless of the presence of probiotics in their composition, which had a higher efficacy compared to ice cream. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cognitive Performance and Iron Status are Negatively Associated with Hookworm Infection in Cambodian Schoolchildren.

PubMed

Kuong, Khov; Fiorentino, Marion; Perignon, Marlene; Chamnan, Chhoun; Berger, Jacques; Sinuon, Muth; Molyden, Vann; Burja, Kurt; Parker, Megan; Ly, Sou Chheng; Friis, Henrik; Roos, Nanna; Wieringa, Frank T

2016-10-05

Soil-transmitted helminth (STH) infection has been associated with lower cognitive performance of schoolchildren. To identify pathways through which STH infection might affect school performance, baseline data from a large rice-fortification trial in Cambodian schoolchildren were used to investigate associations between STH infection, micronutrient status, anemia, and cognitive performance. Complete data on anthropometry, cognitive performance, and micronutrient status were available for 1,760 schoolchildren, 6-16 years of age. STH infection was identified using Kato-Katz, whereas cognitive performance was assessed using Raven's Colored Progressive Matrices (RCPM), block design, and picture completion. STH infection was found in 18% of the children; almost exclusively hookwork infection. After adjusting for age and gender, raw cognitive test scores were significantly lower in hookworm-infected children (-0.65; -0.78; -2.03 points for picture completion, RCPM, and block design, respectively; P < 0.05 for all). Hookworm infection was associated with iron status (total body iron), but not with vitamin A and zinc status, nor with inflammation or anthropometry. Body iron was negatively associated with increased intensity of hookworm infection (R = 0.22, P < 0.001). Hookworm infection in Cambodian schoolchildren was associated with lower cognitive performance, an effect most likely mediated through lower body iron. Interventions that are more effective against hookworm infection are needed to contribute to better health and improvement of cognitive performance. © The American Society of Tropical Medicine and Hygiene.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-12-01

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-08-24

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Biodegradable organic acid-crosslinked alkali-treated gelatins with anti-thrombogenic and endothelialization properties

PubMed Central

Inoue, Motoki; Sasaki, Makoto; Taguchi, Tetsushi

2012-01-01

Gelatins were crosslinked with organic acids and treated with alkali to impart to them endothelialization and anti-thrombogenic properties. These matrices were characterized by biochemical and physicochemical techniques. The amounts of residual amino groups in the matrices decreased with increasing crosslinker concentration. The matrices with the highest crosslinking densities showed excellent endothelial cell adhesion and proliferation. In addition, the adhesion of platelets and formation of fibrin networks on the matrices were suppressed with increasing crosslinker concentration. The matrices also exhibited excellent biodegradability, and the degradation rate decreased with increasing crosslinking density. All the organic acid-crosslinked alkali-treated gelatins showed excellent anti-thrombogenic and endothelialization properties, superior to those of glutaraldehyde-crosslinked alkali-treated gelatins. PMID:27877542

La structure de Jordan des matrices de transfert des modeles de boucles et la relation avec les hamiltoniens XXZ

NASA Astrophysics Data System (ADS)

Morin-Duchesne, Alexi

Lattice models such as percolation, the Ising model and the Potts model are useful for the description of phase transitions in two dimensions. Finding analytical solutions is done by calculating the partition function, which in turn requires finding eigenvalues of transfer matrices. At the critical point, the two dimensional statistical models are invariant under conformal transformations and the construction of rational conformal field theories, as the continuum limit of these lattice models, allows one to compute the partition function at the critical point. Many researchers think however that the paradigm of rational conformal conformal field theories can be extended to include models with non diagonalizable transfer matrices. These models would then be described, in the scaling limit, by logarithmic conformal field theories and the representations of the Virasoro algebra coming into play would be indecomposable. We recall the construction of the double-row transfer matrix DN (λ, u) of the Fortuin-Kasteleyn model, seen as an element of the Temperley-Lieb algebra. This transfer matrix comes into play in physical theories through its representation in link modules (or standard modules). The vector space on which this representation acts decomposes into sectors labelled by a physical parameter d, the number of defects, which remains constant or decreases in the link representations. This thesis is devoted to the identification of the Jordan structure of DN(λ, u) in the link representations. The parameter β = 2 cos λ = -(q + q-1) fixes the theory : for instance β = 1 for percolation and 2 for the Ising model. On the geometry of the strip with open boundary conditions, we show that DN(λ, u) has the same Jordan blocks as its highest Fourier coefficient, FN. We study the non-diagonalizability of FN through the divergences of some of the eigenstates of ρ(F N) that appear at the critical values of λ. The Jordan cells we find in ρ(DN(λ, u)) have rank 2 and couple sectors d and d' when specific constraints on λ, d, d' and N are satisfied. For the model of critical dense polymers (β = 0) on the strip, the eigenvalues of ρ(DN(λ, u)) were known, but their degeneracies only conjectured. By constructing an isomorphism between the link modules on the strip and a subspace of spin modules of the XXZ model at q = i, we prove this conjecture. We also show that the restriction of the Hamiltonian to any sector d is diagonalizable, and that the XX Hamiltonian has rank 2 Jordan cells when N is even. Finally, we study the Jordan structure of the transfer matrix T N(λ, ν) for periodic boundary conditions. When λ = πa/b and a, b ∈ Z× , the matrix TN(λ, ν) has Jordan blocks between sectors, but also within sectors. The approach using FN admits a generalization to the present case and allows us to probe the Jordan cells that tie different sectors. The rank of these cells exceeds 2 in some cases and can grow indefinitely with N. For the Jordan blocks within a sector, we show that the link modules on the cylinder and the XXZ spin modules are isomorphic except for specific curves in the (q, ν) plane. By using the behavior of the transformation ĩd N in a neighborhood of the critical values (qc, ν c), we explicitly build Jordan partners of rank 2 and discuss the existence of Jordan cells with higher rank. Keywords : phase transitions, Ising model, Potts model, Fortuin-Kasteleyn model, transfer matrix method, XXZ Hamiltonian, logarithmic conformal field theory, Jordan structure.

The food matrix affects the anthocyanin profile of fortified egg and dairy matrices during processing and in vitro digestion.

PubMed

Pineda-Vadillo, Carlos; Nau, Françoise; Guerin-Dubiard, Catherin; Jardin, Julien; Lechevalier, Valérie; Sanz-Buenhombre, Marisa; Guadarrama, Alberto; Tóth, Tamás; Csavajda, Éva; Hingyi, Hajnalka; Karakaya, Sibel; Sibakov, Juhani; Capozzi, Francesco; Bordoni, Alessandra; Dupont, Didier

2017-01-01

The aim of the present study was to understand to what extent the inclusion of anthocyanins into dairy and egg matrices could affect their stability after processing and their release and solubility during digestion. For this purpose, individual and total anthocyanin content of four different enriched matrices, namely custard dessert, milkshake, pancake and omelettete, was determined after their manufacturing and during in vitro digestion. Results showed that anthocyanin recovery after processing largely varied among matrices, mainly due to the treatments applied and the interactions developed with other food components. In terms of digestion, the present study showed that the inclusion of anthocyanins into food matrices could be an effective way to protect them against intestinal degradation, and also the incorporation of anthocyanins into matrices with different compositions and structures could represent an interesting and effective method to control the delivery of anthocyanins within the different compartments of the digestive tract. Copyright © 2016 Elsevier Ltd. All rights reserved.

Time series, correlation matrices and random matrix models

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

Vinayak; Seligman, Thomas H.

2014-01-08

In this set of five lectures the authors have presented techniques to analyze open classical and quantum systems using correlation matrices. For diverse reasons we shall see that random matrices play an important role to describe a null hypothesis or a minimum information hypothesis for the description of a quantum system or subsystem. In the former case various forms of correlation matrices of time series associated with the classical observables of some system. The fact that such series are necessarily finite, inevitably introduces noise and this finite time influence lead to a random or stochastic component in these time series.more » By consequence random correlation matrices have a random component, and corresponding ensembles are used. In the latter we use random matrices to describe high temperature environment or uncontrolled perturbations, ensembles of differing chaotic systems etc. The common theme of the lectures is thus the importance of random matrix theory in a wide range of fields in and around physics.« less

RGD peptide-displaying M13 bacteriophage/PLGA nanofibers as cell-adhesive matrices for smooth muscle cells

NASA Astrophysics Data System (ADS)

Shin, Yong Cheol; Lee, Jong Ho; Jin, Oh Seong; Lee, Eun Ji; Jin, Lin Hua; Kim, Chang-Seok; Hong, Suck Won; Han, Dong-Wook; Kim, Chuntae; Oh, Jin-Woo

2015-01-01

Extracellular matrices (ECMs) are network structures that play an essential role in regulating cellular growth and differentiation. In this study, novel nanofibrous matrices were fabricated by electrospinning M13 bacteriophage and poly(lactic- co-glycolic acid) (PLGA) and were shown to be structurally and functionally similar to natural ECMs. A genetically-engineered M13 bacteriophage was constructed to display Arg-Gly-Asp (RGD) peptides on its surface. The physicochemical properties of RGD peptide-displaying M13 bacteriophage (RGD-M13 phage)/PLGA nanofibers were characterized by using scanning electron microscopy and Fourier-transform infrared spectroscopy. We used immunofluorescence staining to confirm that M13 bacteriophages were homogenously distributed in RGD-M13 phage/PLGA matrices. Furthermore, RGD-M13 phage/PLGA nanofibrous matrices, having excellent biocompatibility, can enhance the behaviors of vascular smooth muscle cells. This result suggests that RGD-M13 phage/PLGA nanofibrous matrices have potentials to serve as tissue engineering scaffolds.

Reductions in finite-dimensional integrable systems and special points of classical r-matrices

NASA Astrophysics Data System (ADS)

Skrypnyk, T.

2016-12-01

For a given 𝔤 ⊗ 𝔤-valued non-skew-symmetric non-dynamical classical r-matrices r(u, v) with spectral parameters, we construct the general form of 𝔤-valued Lax matrices of finite-dimensional integrable systems satisfying linear r-matrix algebra. We show that the reduction in the corresponding finite-dimensional integrable systems is connected with "the special points" of the classical r-matrices in which they become degenerated. We also propose a systematic way of the construction of additional integrals of the Lax-integrable systems associated with the symmetries of the corresponding r-matrices. We consider examples of the Lax matrices and integrable systems that are obtained in the framework of the general scheme. Among them there are such physically important systems as generalized Gaudin systems in an external magnetic field, ultimate integrable generalization of Toda-type chains (including "modified" or "deformed" Toda chains), generalized integrable Jaynes-Cummings-Dicke models, integrable boson models generalizing Bose-Hubbard dimer models, etc.

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.

The asymptotic spectra of banded Toeplitz and quasi-Toeplitz matrices

NASA Technical Reports Server (NTRS)

Beam, Richard M.; Warming, Robert F.

1991-01-01

Toeplitz matrices occur in many mathematical, as well as, scientific and engineering investigations. This paper considers the spectra of banded Toeplitz and quasi-Toeplitz matrices with emphasis on non-normal matrices of arbitrarily large order and relatively small bandwidth. These are the type of matrices that appear in the investigation of stability and convergence of difference approximations to partial differential equations. Quasi-Toeplitz matrices are the result of non-Dirichlet boundary conditions for the difference approximations. The eigenvalue problem for a banded Toeplitz or quasi-Toeplitz matrix of large order is, in general, analytically intractable and (for non-normal matrices) numerically unreliable. An asymptotic (matrix order approaches infinity) approach partitions the eigenvalue analysis of a quasi-Toeplitz matrix into two parts, namely the analysis for the boundary condition independent spectrum and the analysis for the boundary condition dependent spectrum. The boundary condition independent spectrum is the same as the pure Toeplitz matrix spectrum. Algorithms for computing both parts of the spectrum are presented. Examples are used to demonstrate the utility of the algorithms, to present some interesting spectra, and to point out some of the numerical difficulties encountered when conventional matrix eigenvalue routines are employed for non-normal matrices of large order. The analysis for the Toeplitz spectrum also leads to a diagonal similarity transformation that improves conventional numerical eigenvalue computations. Finally, the algorithm for the asymptotic spectrum is extended to the Toeplitz generalized eigenvalue problem which occurs, for example, in the stability of Pade type difference approximations to differential equations.

Fibronectin alters the rate of formation and structure of the fibrin matrix.

PubMed

Ramanathan, Anand; Karuri, Nancy

2014-01-10

Plasma fibronectin is a vital component of the fibrin clot; however its role on clot structure is not clearly understood. The goal of this study was to examine the influence of fibronectin on the kinetics of formation, structural characteristics and composition of reconstituted fibrin clots or fibrin matrices. Fibrin matrices were formed by adding thrombin to 1, 2 or 4 mg/ml fibrinogen supplemented with 0-0.4 mg/ml fibronectin. The rate of fibrin matrix formation was then monitored by measuring light absorbance properties at different time points. Confocal microscopy of fluorescein conjugated fibrinogen was used to visualize the structural characteristics of fibrin matrices. The amount of fibronectin in fibrin matrices was determined through electrophoresis and immunoblotting of solubilized matrices. Fibronectin concentration positively correlated with the initial rate of fibrin matrix formation and with steady state light absorbance values of fibrin matrices. An increase in fibronectin concentration resulted in thinner and denser fibers in the fibrin matrices. Electrophoresis and immunoblotting showed that fibronectin was covalently and non-covalently bound to fibrin matrices and in the form of high molecular weight multimers. The formation of fibronectin multimers was attributed to cross-linking of fibronectin by trace amounts Factor XIIIa. These findings are novel because they link results from light absorbance studies to microcopy analyses and demonstrate an influence of fibronectin on fibrin matrix structural characteristics. This data is important in developing therapies that destabilize fibrin clots. Copyright © 2014. Published by Elsevier Inc.

The Modern Origin of Matrices and Their Applications

ERIC Educational Resources Information Center

Debnath, L.

2014-01-01

This paper deals with the modern development of matrices, linear transformations, quadratic forms and their applications to geometry and mechanics, eigenvalues, eigenvectors and characteristic equations with applications. Included are the representations of real and complex numbers, and quaternions by matrices, and isomorphism in order to show…

Enhancing Understanding of Transformation Matrices

ERIC Educational Resources Information Center

Dick, Jonathan; Childrey, Maria

2012-01-01

With the Common Core State Standards' emphasis on transformations, teachers need a variety of approaches to increase student understanding. Teaching matrix transformations by focusing on row vectors gives students tools to create matrices to perform transformations. This empowerment opens many doors: Students are able to create the matrices for…

Theory of quark mixing matrix and invariant functions of mass matrices

NASA Astrophysics Data System (ADS)

Jarloskog, C.

1987-10-01

The origin of the quark mixing matrix; super elementary theory of flavor projection operators; equivalences and invariances; the commutator formalism and CP violation; CP conditions for any number of families; the angle between the quark mass matrices; and application to Fritzsch and Stech mass matrices are discussed.

Analyzing Matrices of Meta-Analytic Correlations: Current Practices and Recommendations

ERIC Educational Resources Information Center

Sheng, Zitong; Kong, Wenmo; Cortina, Jose M.; Hou, Shuofei

2016-01-01

Researchers have become increasingly interested in conducting analyses on meta-analytic correlation matrices. Methodologists have provided guidance and recommended practices for the application of this technique. The purpose of this article is to review current practices regarding analyzing meta-analytic correlation matrices, to identify the gaps…

76 FR 31356 - Notice of Proposed Information Collection for Public Comment; Technical Assistance Experience...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-31

... Matrices AGENCY: Office of the Community Planning and Development. ACTION: Notice of proposed information..., Expertise, and Awards Received Matrices. Description of the need for the information proposed: The Technical Assistance Experience, Expertise, and Awards Received Matrices will allow the Office of Special Needs...

76 FR 35231 - Notice of Proposed Information Collection for Public Comment; McKinney-Vento Technical Assistance...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-16

... Information Collection for Public Comment; McKinney-Vento Technical Assistance Narrative, Matrices, and... Narrative, Matrices, and Reporting Requirements. Description of the need for the information proposed: McKinney- Vento Technical Assistance (MV-TA) Narrative, Matrices, and Reporting Requirements will allow the...

Random matrices with external source and the asymptotic behaviour of multiple orthogonal polynomials

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

Aptekarev, Alexander I; Lysov, Vladimir G; Tulyakov, Dmitrii N

2011-02-28

Ensembles of random Hermitian matrices with a distribution measure defined by an anharmonic potential perturbed by an external source are considered. The limiting characteristics of the eigenvalue distribution of the matrices in these ensembles are related to the asymptotic behaviour of a certain system of multiple orthogonal polynomials. Strong asymptotic formulae are derived for this system. As a consequence, for matrices in this ensemble the limit mean eigenvalue density is found, and a variational principle is proposed to characterize this density. Bibliography: 35 titles.

Use of Mueller and non-Mueller matrices to describe polarization properties of telescope-based polarimeters

NASA Astrophysics Data System (ADS)

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

1994-09-01

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

Estimation for the Linear Model With Uncertain Covariance Matrices

NASA Astrophysics Data System (ADS)

Zachariah, Dave; Shariati, Nafiseh; Bengtsson, Mats; Jansson, Magnus; Chatterjee, Saikat

2014-03-01

We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probabilistically by modeling the covariance matrices with prior inverse-Wishart distributions. The nonconvex problem of jointly estimating the signal of interest and the covariance matrices is tackled by a computationally efficient fixed-point iteration as well as an approximate variational Bayes solution. The statistical performance of estimators is compared numerically to state-of-the-art estimators from the literature and shown to perform favorably.

Schur Complement Inequalities for Covariance Matrices and Monogamy of Quantum Correlations

NASA Astrophysics Data System (ADS)

Lami, Ludovico; Hirche, Christoph; Adesso, Gerardo; Winter, Andreas

2016-11-01

We derive fundamental constraints for the Schur complement of positive matrices, which provide an operator strengthening to recently established information inequalities for quantum covariance matrices, including strong subadditivity. This allows us to prove general results on the monogamy of entanglement and steering quantifiers in continuous variable systems with an arbitrary number of modes per party. A powerful hierarchical relation for correlation measures based on the log-determinant of covariance matrices is further established for all Gaussian states, which has no counterpart among quantities based on the conventional von Neumann entropy.

Schur Complement Inequalities for Covariance Matrices and Monogamy of Quantum Correlations.

PubMed

Lami, Ludovico; Hirche, Christoph; Adesso, Gerardo; Winter, Andreas

2016-11-25

We derive fundamental constraints for the Schur complement of positive matrices, which provide an operator strengthening to recently established information inequalities for quantum covariance matrices, including strong subadditivity. This allows us to prove general results on the monogamy of entanglement and steering quantifiers in continuous variable systems with an arbitrary number of modes per party. A powerful hierarchical relation for correlation measures based on the log-determinant of covariance matrices is further established for all Gaussian states, which has no counterpart among quantities based on the conventional von Neumann entropy.

Fidelity under isospectral perturbations: a random matrix study

NASA Astrophysics Data System (ADS)

Leyvraz, F.; García, A.; Kohler, H.; Seligman, T. H.

2013-07-01

The set of Hamiltonians generated by all unitary transformations from a single Hamiltonian is the largest set of isospectral Hamiltonians we can form. Taking advantage of the fact that the unitary group can be generated from Hermitian matrices we can take the ones generated by the Gaussian unitary ensemble with a small parameter as small perturbations. Similarly, the transformations generated by Hermitian antisymmetric matrices from orthogonal matrices form isospectral transformations among symmetric matrices. Based on this concept we can obtain the fidelity decay of a system that decays under a random isospectral perturbation with well-defined properties regarding time-reversal invariance. If we choose the Hamiltonian itself also from a classical random matrix ensemble, then we obtain solutions in terms of form factors in the limit of large matrices.

Retrieval of the non-depolarizing components of depolarizing Mueller matrices by using symmetry conditions and least squares minimization

NASA Astrophysics Data System (ADS)

Kuntman, Ertan; Canillas, Adolf; Arteaga, Oriol

2017-11-01

Experimental Mueller matrices contain certain amount of uncertainty in their elements and these uncertainties can create difficulties for decomposition methods based on analytic solutions. In an earlier paper [1], we proposed a decomposition method for depolarizing Mueller matrices by using certain symmetry conditions. However, because of the experimental error, that method creates over-determined systems with non-unique solutions. Here we propose to use least squares minimization approach in order to improve the accuracy of our results. In this method, we are taking into account the number of independent parameters of the corresponding symmetry and the rank constraints on the component matrices to decide on our fitting model. This approach is illustrated with experimental Mueller matrices that include material media with different Mueller symmetries.

Angiogenic response induced by acellular femoral matrix in vivo

PubMed Central

Conconi, Maria Teresa; Nico, Beatrice; Rebuffat, Piera; Crivellato, Enrico; Parnigotto, Pier Paolo; Nussdorfer, Gastone G; Ribatti, Domenico

2005-01-01

We investigated the angiogenic response induced by acellular femoral matrices implanted in vivo on to the chick embryo chorioallantoic membrane (CAM), a useful model for such investigation. The results showed that acellular matrices were able to induce a strong angiogenic response, comparable with that of fibroblast growth factor-2 (FGF-2), a well-known angiogenic cytokine. The angiogenic response was further increased when exogenous FGF-2 or transforming growth factor beta-1 (TGF-β1) was added to the matrices and inhibited by the addition of anti-FGF-2 or anti-TGF-β1 antibodies. The response may be considered to be dependent on a direct angiogenic effect exerted by the matrices, and also in part by the presence of FGF-2 and TGF-β1 in the acellular matrices. PMID:16011546

Introduction of organic/hydro-organic matrices in inductively coupled plasma optical emission spectrometry and mass spectrometry: a tutorial review. Part I. Theoretical considerations.

PubMed

Leclercq, Amélie; Nonell, Anthony; Todolí Torró, José Luis; Bresson, Carole; Vio, Laurent; Vercouter, Thomas; Chartier, Frédéric

2015-07-23

Due to their outstanding analytical performances, inductively coupled plasma optical emission spectrometry (ICP-OES) and mass spectrometry (ICP-MS) are widely used for multi-elemental measurements and also for isotopic characterization in the case of ICP-MS. While most studies are carried out in aqueous matrices, applications involving organic/hydro-organic matrices become increasingly widespread. This kind of matrices is introduced in ICP based instruments when classical "matrix removal" approaches such as acid digestion or extraction procedures cannot be implemented. Due to the physico-chemical properties of organic/hydro-organic matrices and their associated effects on instrumentation and analytical performances, their introduction into ICP sources is particularly challenging and has become a full topic. In this framework, numerous theoretical and phenomenological studies of these effects have been performed in the past, mainly by ICP-OES, while recent literature is more focused on applications and associated instrumental developments. This tutorial review, divided in two parts, explores the rich literature related to the introduction of organic/hydro-organic matrices in ICP-OES and ICP-MS. The present Part I, provides theoretical considerations in connection with the physico-chemical properties of organic/hydro-organic matrices, in order to better understand the induced phenomena. This focal point is divided in four chapters highlighting: (i) the impact of organic/hydro-organic matrices from aerosol generation to atomization/excitation/ionization processes; (ii) the production of carbon molecular constituents and their spatial distribution in the plasma with respect to analytes repartition; (iii) the subsequent modifications of plasma fundamental properties; and (iv) the resulting spectroscopic and non spectroscopic interferences. This first part of this tutorial review is addressed either to beginners or to more experienced scientists who are interested in the analysis of organic/hydro-organic matrices by ICP sources and would like to consider the theoretical background of effects induced by such matrices. The second part of this tutorial review will be dedicated to more practical consideration on instrumentation, such as adapted introductions devices, as well as instrumental and operating parameters optimization. The analytical strategies for elemental quantification in such matrices will also be addressed. Copyright © 2015 Elsevier B.V. All rights reserved.

Structure to function: Spider silk and human collagen

NASA Astrophysics Data System (ADS)

Rabotyagova, Olena S.

Nature has the ability to assemble a variety of simple molecules into complex functional structures with diverse properties. Collagens, silks and muscles fibers are some examples of fibrous proteins with self-assembling properties. One of the great challenges facing Science is to mimic these designs in Nature to find a way to construct molecules that are capable of organizing into functional supra-structures by self-assembly. In order to do so, a construction kit consisting of molecular building blocks along with a complete understanding on how to form functional materials is required. In this current research, the focus is on spider silk and collagen as fibrous protein-based biopolymers that can shed light on how to generate nanostructures through the complex process of self-assembly. Spider silk in fiber form offers a unique combination of high elasticity, toughness, and mechanical strength, along with biological compatibility and biodegrability. Spider silk is an example of a natural block copolymer, in which hydrophobic and hydrophilic blocks are linked together generating polymers that organize into functional materials with extraordinary properties. Since silks resemble synthetic block copolymer systems, we adopted the principles of block copolymer design from the synthetic polymer literature to build block copolymers based on spider silk sequences. Moreover, we consider spider silk to be an important model with which to study the relationships between structure and properties in our system. Thus, the first part of this work was dedicated to a novel family of spider silk block copolymers, where we generated a new family of functional spider silk-like block copolymers through recombinant DNA technology. To provide fundamental insight into relationships between peptide primary sequence, block composition, and block length and observed morphological and structural features, we used these bioengineered spider silk block copolymers to study secondary structure, morphological features and assembly. Aside from fundamental perspectives, we anticipate that these results will provide a blueprint for the design of precise materials for a range of potential applications such as controlled release devices, functional coatings, components of tissue regeneration materials and environmentally friendly polymers in future studies. In the second part of this work, human collagen type I was studied as another representative of the family of fibrous proteins. Collagen type I is the most abundant extracellular matrix protein in the human body, providing the basis for tissue structure and directing cellular functions. Collagen has a complex structural hierarchy, organized at different length scales, including the characteristic triple helical feature. In the present study we assessed the relationship between collagen structure (native vs. denatured) and sensitivity to UV radiation with a focus on changes in the primary structure, conformation, microstructure and material properties. Free radical reactions are involved in collagen degradation and a mechanism for UV-induced collagen degradation related to structure was proposed. The results from this study demonstrated the role of collagen supramolecular organization (triple helix) in the context of the effects of electromagnetic radiation on extracellular matrices. Owing to the fact that both silks and collagens are proteins that have found widespread interest for biomaterial related needs, we anticipate that the current studies will serve as a foundation for future biomaterial designs with controlled properties. Furthermore, fundamental insight into self-assembly and environmentally-2mediated degradation, will build a foundation for fundamental understanding of the remodeling and functions of these types of fibrous proteins in vivo and in vitro. This type of insight is essential for many areas of scientific inquiry, from drug delivery, to scaffolds for tissue engineering, and to the stability of materials in space.

Estimating soil matric potential in Owens Valley, California

USGS Publications Warehouse

Sorenson, Stephen K.; Miller, Reuben F.; Welch, Michael R.; Groeneveld, David P.; Branson, Farrel A.

1989-01-01

Much of the floor of Owens Valley, California, is covered with alkaline scrub and alkaline meadow plant communities, whose existence is dependent partly on precipitation and partly on water infiltrated into the rooting zone from the shallow water table. The extent to which these plant communities are capable of adapting to and surviving fluctuations in the water table depends on physiological adaptations of the plants and on the water content, matric potential characteristics of the soils. Two methods were used to estimate soil matric potential in test sites in Owens Valley. The first, the filter-paper method, uses water content of filter papers equilibrated to water content of soil samples taken with a hand auger. The previously published calibration relations used to estimate soil matric potential from the water content of the filter papers were modified on the basis of current laboratory data. The other method of estimating soil matric potential was a modeling approach based on data from this and previous investigations. These data indicate that the base-10 logarithm of soil matric potential is a linear function of gravimetric soil water content for a particular soil. The slope and intercepts of this function vary with the texture and saturation capacity of the soil. Estimates of soil water characteristic curves were made at two sites by averaging the gravimetric soil water content and soil matric potential values from multiple samples at 0.1-m depth intervals derived by using the hand auger and filter-paper method and entering these values in the soil water model. The characteristic curves then were used to estimate soil matric potential from estimates of volumetric soil water content derived from neutron-probe readings. Evaluation of the modeling technique at two study sites indicated that estimates of soil matric potential within 0.5 pF units of the soil matric potential value derived by using the filter-paper method could be obtained 90 to 95 percent of the time in soils where water content was less than field capacity. The greatest errors occurred at depths where there was a distinct transition between soils of different textures.

Linking the Congenital Heart Surgery Databases of the Society of Thoracic Surgeons and the Congenital Heart Surgeons’ Society: Part 1—Rationale and Methodology

PubMed Central

Jacobs, Jeffrey P.; Pasquali, Sara K.; Austin, Erle; Gaynor, J. William; Backer, Carl; Hirsch-Romano, Jennifer C.; Williams, William G.; Caldarone, Christopher A.; McCrindle, Brian W.; Graham, Karen E.; Dokholyan, Rachel S.; Shook, Gregory J.; Poteat, Jennifer; Baxi, Maulik V.; Karamlou, Tara; Blackstone, Eugene H.; Mavroudis, Constantine; Mayer, John E.; Jonas, Richard A.; Jacobs, Marshall L.

2014-01-01

Purpose The Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) is the largest Registry in the world of patients who have undergone congenital and pediatric cardiac surgical operations. The Congenital Heart Surgeons’ Society Database (CHSS-D) is an Academic Database designed for specialized detailed analyses of specific congenital cardiac malformations and related treatment strategies. The goal of this project was to create a link between the STS-CHSD and the CHSS-D in order to facilitate studies not possible using either individual database alone and to help identify patients who are potentially eligible for enrollment in CHSS studies. Methods Centers were classified on the basis of participation in the STS-CHSD, the CHSS-D, or both. Five matrices, based on CHSS inclusionary criteria and STS-CHSD codes, were created to facilitate the automated identification of patients in the STS-CHSD who meet eligibility criteria for the five active CHSS studies. The matrices were evaluated with a manual adjudication process and were iteratively refined. The sensitivity and specificity of the original matrices and the refined matrices were assessed. Results In January 2012, a total of 100 centers participated in the STS-CHSD and 74 centers participated in the CHSS. A total of 70 centers participate in both and 40 of these 70 agreed to participate in this linkage project. The manual adjudication process and the refinement of the matrices resulted in an increase in the sensitivity of the matrices from 93% to 100% and an increase in the specificity of the matrices from 94% to 98%. Conclusion Matrices were created to facilitate the automated identification of patients potentially eligible for the five active CHSS studies using the STS-CHSD. These matrices have a sensitivity of 100% and a specificity of 98%. In addition to facilitating identification of patients potentially eligible for enrollment in CHSS studies, these matrices will allow (1) estimation of the denominator of patients potentially eligible for CHSS studies and (2) comparison of eligible and enrolled patients to potentially eligible and not enrolled patients to assess the generalizability of CHSS studies. PMID:24668974

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

Graphene oxide-stimulated myogenic differentiation of C2C12 cells on PLGA/RGD peptide nanofiber matrices

NASA Astrophysics Data System (ADS)

Shin, Y. C.; Lee, J. H.; Kim, M. J.; Hong, S. W.; Oh, J.-W.; Kim, C.-S.; Kim, B.; Hyun, J. K.; Kim, Y.-J.; Han, D.-W.

2015-07-01

During the last decade, much attention has been paid to graphene-based nanomaterials because they are considered as potential candidates for biomedical applications such as scaffolds for tissue engineering and substrates for the differentiation of stem cells. Until now, electrospun matrices composed of various biodegradable copolymers have been extensively developed for tissue engineering and regeneration; however, their use in combination with graphene oxide (GO) is novel and challenging. In this study, nanofiber matrices composed of poly(lactic-co-glycolic acid, PLGA) and M13 phage with RGD peptide displayed on its surface (RGD peptide-M13 phage) were prepared as extracellular matrix (ECM)-mimicking substrates. RGD peptide is a tripeptide (Arg-Gly-Asp) found on ECM proteins that promotes various cellular behaviors. The physicochemical properties of PLGA and RGD peptide-M13 phage (PLGA/RGD peptide) nanofiber matrices were characterized by atomic force microscopy, Fourier-transform infrared spectroscopy and thermogravimetric analysis. In addition, the growth of C2C12 mouse myoblasts on the PLGA/RGD peptide matrices was examined by measuring the metabolic activity. Moreover, the differentiation of C2C12 mouse myoblasts on the matrices when treated with GO was evaluated. The cellular behaviors, including growth and differentiation of C2C12 mouse myoblasts, were substantially enhanced on the PLGA/RGD peptide nanofiber matrices when treated with GO. Overall, these findings suggest that the PLGA/RGD peptide nanofiber matrices can be used in combination with GO as a novel strategy for skeletal tissue regeneration.

Introduction to the QIAT Self-Evaluation Matrices

ERIC Educational Resources Information Center

Zabala, Joy Smiley; Carl, Diana F.

2004-01-01

The QIAT Self-Evaluation Matrices (QILT, 2001) were developed in response to formative evaluation data indicating a need for a model that could assist in the application of the Quality Indicators for Assistive Technology Services in Schools (Zabala, et al, 2000). The QIAT Matrices are based on the idea that change does not happen immediately, but…

Evaluation of an Approximate Method for Synthesizing Covariance Matrices for Use in Meta-Analytic SEM

ERIC Educational Resources Information Center

Beretvas, S. Natasha; Furlow, Carolyn F.

2006-01-01

Meta-analytic structural equation modeling (MA-SEM) is increasingly being used to assess model-fit for variables' interrelations synthesized across studies. MA-SEM researchers have analyzed synthesized correlation matrices using structural equation modeling (SEM) estimation that is designed for covariance matrices. This can produce incorrect…

An Alternative Method to Gauss-Jordan Elimination: Minimizing Fraction Arithmetic

ERIC Educational Resources Information Center

Smith, Luke; Powell, Joan

2011-01-01

When solving systems of equations by using matrices, many teachers present a Gauss-Jordan elimination approach to row reducing matrices that can involve painfully tedious operations with fractions (which I will call the traditional method). In this essay, I present an alternative method to row reduce matrices that does not introduce additional…

The Approximation of Two-Mode Proximity Matrices by Sums of Order-Constrained Matrices.

ERIC Educational Resources Information Center

Hubert, Lawrence; Arabie, Phipps

1995-01-01

A least-squares strategy is proposed for representing a two-mode proximity matrix as an approximate sum of a small number of matrices that satisfy certain simple order constraints on their entries. The primary class of constraints considered defines Q-forms for particular conditions in a two-mode matrix. (SLD)

Introduction to Matrix Algebra, Student's Text, Unit 23.

ERIC Educational Resources Information Center

Allen, Frank B.; And Others

Unit 23 in the SMSG secondary school mathematics series is a student text covering the following topics in matrix algebra: matrix operations, the algebra of 2 X 2 matrices, matrices and linear systems, representation of column matrices as geometric vectors, and transformations of the plane. Listed in the appendix are four research exercises in…

A Comparison between Element Salience versus Context as Item Difficulty Factors in Raven's Matrices

ERIC Educational Resources Information Center

Perez-Salas, Claudia P.; Streiner, David L.; Roberts, Maxwell J.

2012-01-01

The nature of contextual facilitation effects for items derived from Raven's Progressive Matrices was investigated in two experiments. For these, the original matrices were modified, creating either abstract versions with high element salience, or versions which comprised realistic entities set in familiar contexts. In order to replicate and…

Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation.

PubMed

Saito, Shota; Hirata, Yoshito; Sasahara, Kazutoshi; Suzuki, Hideyuki

2015-01-01

Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.

Calibration and temperature correction of heat dissipation matric potential sensors

USGS Publications Warehouse

Flint, A.L.; Campbell, G.S.; Ellett, K.M.; Calissendorff, C.

2002-01-01

This paper describes how heat dissipation sensors, used to measure soil water matric potential, were analyzed to develop a normalized calibration equation and a temperature correction method. Inference of soil matric potential depends on a correlation between the variable thermal conductance of the sensor's porous ceramic and matric poten-tial. Although this correlation varies among sensors, we demonstrate a normalizing procedure that produces a single calibration relationship. Using sensors from three sources and different calibration methods, the normalized calibration resulted in a mean absolute error of 23% over a matric potential range of -0.01 to -35 MPa. Because the thermal conductivity of variably saturated porous media is temperature dependent, a temperature correction is required for application of heat dissipation sensors in field soils. A temperature correction procedure is outlined that reduces temperature dependent errors by 10 times, which reduces the matric potential measurement errors by more than 30%. The temperature dependence is well described by a thermal conductivity model that allows for the correction of measurements at any temperature to measurements at the calibration temperature.

Chitosan-Based Matrices Prepared by Gamma Irradiation for Tissue Regeneration: Structural Properties vs. Preparation Method.

PubMed

Casimiro, Maria Helena; Lancastre, Joana J H; Rodrigues, Alexandra P; Gomes, Susana R; Rodrigues, Gabriela; Ferreira, Luís M

2017-02-01

In the last decade, new generations of biopolymer-based materials have attracted attention, aiming its application as scaffolds for tissue engineering. These engineered three-dimensional scaffolds are designed to improve or replace damaged, missing, or otherwise compromised tissues or organs. Despite the number of promising methods that can be used to generate 3D cell-instructive matrices, the innovative nature of the present work relies on the application of ionizing radiation technology to form and modify surfaces and matrices with advantage over more conventional technologies (room temperature reaction, absence of harmful initiators or solvents, high penetration through the bulk materials, etc.), and the possibility of preparation and sterilization in one single step. The current chapter summarizes the work done by the authors in the gamma radiation processing of biocompatible and biodegradable chitosan-based matrices for skin regeneration. Particular attention is given to the correlation between the different preparation conditions and the final polymeric matrices' properties. We therefore expect to demonstrate that instructive matrices produced and improved by radiation technology bring to the field of skin regenerative medicine a supplemental advantage over more conservative techniques.

Introducing capillary electrophoresis with laser-induced fluorescence (CE-LIF) as a potential analysis and quantification tool for galactooligosaccharides extracted from complex food matrices.

PubMed

Albrecht, Simone; Schols, Henk A; Klarenbeek, Bert; Voragen, Alphons G J; Gruppen, Harry

2010-03-10

The analysis and quantification of (galacto)oligosaccharides from food matrices demands both a reproducible extraction method as well as a sensitive and accurate analytical method. Three typical matrices, namely, infant formula, fruit juice, and a maltodextrin-rich preparation, to which a commercial galactooligosaccharide mixture was added in a product concentration range from 1.25 to 30%, served as model substrates. Solid-phase extraction on graphitized carbon material upon enzymatic amyloglucosidase pretreatment enabled a good recovery and a selective purification of the different galactooligosaccharide structures from the exceeding amounts of particularly lactose and maltodextrins. With the implementation of capillary electrophoresis in combination with laser-induced fluorescence (CE-LIF) detection, a new possibility facilitating a sensitive qualitative and quantitative determination of the galactooligosaccharide contents in the different food matrices is outlined. Simultaneous monitoring and quantifying prebiotic oligosaccharides embedded in food matrices presents a promising and important step toward an efficient monitoring of individual oligosaccharides and is of interest for research areas dealing with small quantities of oligosaccharides embedded in complex matrices, e.g., body liquids.

Synchronous correlation matrices and Connes’ embedding conjecture

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

Dykema, Kenneth J., E-mail: kdykema@math.tamu.edu; Paulsen, Vern, E-mail: vern@math.uh.edu

In the work of Paulsen et al. [J. Funct. Anal. (in press); preprint arXiv:1407.6918], the concept of synchronous quantum correlation matrices was introduced and these were shown to correspond to traces on certain C*-algebras. In particular, synchronous correlation matrices arose in their study of various versions of quantum chromatic numbers of graphs and other quantum versions of graph theoretic parameters. In this paper, we develop these ideas further, focusing on the relations between synchronous correlation matrices and microstates. We prove that Connes’ embedding conjecture is equivalent to the equality of two families of synchronous quantum correlation matrices. We prove thatmore » if Connes’ embedding conjecture has a positive answer, then the tracial rank and projective rank are equal for every graph. We then apply these results to more general non-local games.« less

Stabilization of chromium-bearing electroplating sludge with MSWI fly ash-based Friedel matrices.

PubMed

Qian, Guangren; Yang, Xiaoyan; Dong, Shixiang; Zhou, Jizhi; Sun, Ying; Xu, Yunfeng; Liu, Qiang

2009-06-15

This work investigated the feasibility and effectiveness of MSWI fly ash-based Friedel matrices on stabilizing/solidifying industrial chromium-bearing electroplating sludge using MSWI fly ash as the main raw material with a small addition of active aluminum. The compressive strength, leaching behavior and chemical speciation of heavy metals and hydration phases of matrices were characterized by TCLP, XRD, FTIR and other experimental methods. The results revealed that MSWI fly ash-based Friedel matrices could effectively stabilize chromium-bearing electroplating sludge, the formed ettringite and Friedel phases played a significant role in the fixation of heavy metals in electroplating sludge. The co-disposal of chromium-bearing electroplating sludge and MSWI fly ash-based Friedel matrices with a small addition of active aluminum is promising to be an effective way of stabilizing chromium-bearing electroplating sludge.

Performance Properties of Graphite Reinforced Composites with Advanced Resin Matrices

NASA Technical Reports Server (NTRS)

Kourtides, Demetrius A.

1980-01-01

This article looks at the effect of different resin matrices on thermal and mechanical properties of graphite composites, and relates the thermal and flammability properties to the anaerobic char yield of the resins. The processing parameters of graphite composites utilizing graphite fabric and epoxy or other advanced resins as matrices are presented. Thermoset resin matrices studied were: aminecured polyfunctional glycidyl aminetype epoxy (baseline), phenolicnovolac resin based on condensation of dihydroxymethyl-xylene and phenol cured with hexamine, two types of polydismaleimide resins, phenolic resin, and benzyl resin. The thermoplastic matrices studied were polyethersulfone and polyphenylenesulfone. Properties evaluated in the study included anaerobic char yield, limiting oxygen index, smoke evolution, moisture absorption, and mechanical properties at elevated temperatures including tensile, compressive, and short-beam shear strengths. Generally, it was determined that graphite composites with the highest char yield exhibited optimum fire-resistant properties.

Estimating soil matric potential in Owens Valley, California

USGS Publications Warehouse

Sorenson, Stephen K.; Miller, R.F.; Welch, M.R.; Groeneveld, D.P.; Branson, F.A.

1988-01-01

Much of the floor of the Owens Valley, California, is covered with alkaline scrub and alkaline meadow plant communities, whose existence is dependent partly on precipitation and partly on water infiltrated into the rooting zone from the shallow water table. The extent to which these plant communities are capable of adapting to and surviving fluctuations in the water table depends on physiological adaptations of the plants and on the water content, matric potential characteristics of the soils. Two methods were used to estimate soil matric potential in test sites in Owens Valley. The first was the filter-paper method, which uses water content of filter papers equilibrated to water content of soil samples taken with a hand auger. The other method of estimating soil matric potential was a modeling approach based on data from this and previous investigations. These data indicate that the base 10 logarithm of soil matric potential is a linear function of gravimetric soil water content for a particular soil. Estimates of soil water characteristic curves were made at two sites by averaging the gravimetric soil water content and soil matric potential values from multiple samples at 0.1 m depths derived by using the hand auger and filter paper method and entering these values in the soil water model. The characteristic curves then were used to estimate soil matric potential from estimates of volumetric soil water content derived from neutron-probe readings. Evaluation of the modeling technique at two study sites indicated that estimates of soil matric potential within 0.5 pF units of the soil matric potential value derived by using the filter paper method could be obtained 90 to 95% of the time in soils where water content was less than field capacity. The greatest errors occurred at depths where there was a distinct transition between soils of different textures. (Lantz-PTT)

Simple techniques for improving deep neural network outcomes on commodity hardware

NASA Astrophysics Data System (ADS)

Colina, Nicholas Christopher A.; Perez, Carlos E.; Paraan, Francis N. C.

2017-08-01

We benchmark improvements in the performance of deep neural networks (DNN) on the MNIST data test upon imple-menting two simple modifications to the algorithm that have little overhead computational cost. First is GPU parallelization on a commodity graphics card, and second is initializing the DNN with random orthogonal weight matrices prior to optimization. Eigenspectra analysis of the weight matrices reveal that the initially orthogonal matrices remain nearly orthogonal after training. The probability distributions from which these orthogonal matrices are drawn are also shown to significantly affect the performance of these deep neural networks.

Classical r-matrices for the generalised Chern–Simons formulation of 3d gravity

NASA Astrophysics Data System (ADS)

Osei, Prince K.; Schroers, Bernd J.

2018-04-01

We study the conditions for classical r-matrices to be compatible with the generalised Chern–Simons action for 3d gravity. Compatibility means solving the classical Yang–Baxter equations with a prescribed symmetric part for each of the real Lie algebras and bilinear pairings arising in the generalised Chern–Simons action. We give a new construction of r-matrices via a generalised complexification and derive a non-linear set of matrix equations determining the most general compatible r-matrix. We exhibit new families of solutions and show that they contain some known r-matrices for special parameter values.

Boundary reflection matrices for nonsimply laced affine Toda field theories

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

Kim, J.D.

The boundary reflection matrices for nonsimply laced affine Toda field theories defined on a half line with the Neumann boundary condition are investigated. The boundary reflection matrices for some pairs of the models are evaluated up to one loop order by perturbation theory. Then the exact boundary reflection matrices which are consistent with the one loop result are found under the assumption of {open_quote}{open_quote}duality{close_quote}{close_quote} and tested against algebraic consistency such as the boundary bootstrap equation and boundary crossing-unitarity relation. {copyright} {ital 1996 The American Physical Society.}

Central Limit Theorems for Linear Statistics of Heavy Tailed Random Matrices

NASA Astrophysics Data System (ADS)

Benaych-Georges, Florent; Guionnet, Alice; Male, Camille

2014-07-01

We show central limit theorems (CLT) for the linear statistics of symmetric matrices with independent heavy tailed entries, including entries in the domain of attraction of α-stable laws and entries with moments exploding with the dimension, as in the adjacency matrices of Erdös-Rényi graphs. For the second model, we also prove a central limit theorem of the moments of its empirical eigenvalues distribution. The limit laws are Gaussian, but unlike the case of standard Wigner matrices, the normalization is the one of the classical CLT for independent random variables.

Detection of Botulinum Neurotoxin Serotype A, B, and F Proteolytic Activity in Complex Matrices with Picomolar to Femtomolar Sensitivity

PubMed Central

Dunning, F. Mark; Ruge, Daniel R.; Piazza, Timothy M.; Stanker, Larry H.; Zeytin, Füsûn N.

2012-01-01

Rapid, high-throughput assays that detect and quantify botulinum neurotoxin (BoNT) activity in diverse matrices are required for environmental, clinical, pharmaceutical, and food testing. The current standard, the mouse bioassay, is sensitive but is low in throughput and precision. In this study, we present three biochemical assays for the detection and quantification of BoNT serotype A, B, and F proteolytic activities in complex matrices that offer picomolar to femtomolar sensitivity with small assay volumes and total assay times of less than 24 h. These assays consist of magnetic beads conjugated with BoNT serotype-specific antibodies that are used to purify BoNT from complex matrices before the quantification of bound BoNT proteolytic activity using the previously described BoTest reporter substrates. The matrices tested include human serum, whole milk, carrot juice, and baby food, as well as buffers containing common pharmaceutical excipients. The limits of detection were below 1 pM for BoNT/A and BoNT/F and below 10 pM for BoNT/B in most tested matrices using 200-μl samples and as low as 10 fM for BoNT/A with an increased sample volume. Together, these data describe rapid, robust, and high-throughput assays for BoNT detection that are compatible with a wide range of matrices. PMID:22923410

Influence of thermal annealing and radiation enhanced diffusion processes on surface plasmon resonance of gold implanted dielectric matrices

NASA Astrophysics Data System (ADS)

Devi, Ksh. Devarani; Ojha, Sunil; Singh, Fouran

2018-03-01

Gold nanoparticles (AuNPs) embedded in fused silica and sapphire dielectric matrices were synthesized by Au ion implantation. Systematic investigations were carried out to study the influence of implantation dose, post annealing temperature, swift heavy ion (SHI) irradiation and radiation enhanced diffusion (RED). Rutherford Backscattering Spectrometry (RBS) measurements were carried out to quantify concentration and depth profile of Au present in the host matrices. X-ray diffraction (XRD) was employed to characterize AuNPs formation. As-implanted and post-annealed films were irradiated using 100 MeV Ag ions to investigate the effect of electronic energy deposition on size and shape of NPs, which is estimated indirectly by the peak shape analysis of surface plasmon resonance (SPR). The effect of volume fraction of Au and their redistribution is also reported. A strong absorption in near infra red region is also noticed and understood by the formation of percolated NPs in dielectric matrices. It is quite clear from these results that the effect of RED assisted Oswald ripening is much more pronounced than the conventional Oswald ripening for the growth of NPs in the case of silica host matrices. However for sapphire matrices, it seems that growth of NPs already completed during implantation and it may be attributed to the high diffusivity of Au in sapphire matrices during implantation process.

The algebra of complex 2 × 2 matrices and a general closed Baker-Campbell-Hausdorff formula

NASA Astrophysics Data System (ADS)

Foulis, D. L.

2017-07-01

We derive a closed formula for the Baker-Campbell-Hausdorff series expansion in the case of complex 2×2 matrices. For arbitrary matrices A and B, and a matrix Z such that \\exp Z = \\exp A \\exp B , our result expresses Z as a linear combination of A and B, their commutator [A, B] , and the identity matrix I. The coefficients in this linear combination are functions of the traces and determinants of A and B, and the trace of their product. The derivation proceeds purely via algebraic manipulations of the given matrices and their products, making use of relations developed here, based on the Cayley-Hamilton theorem, as well as a characterization of the consequences of [A, B] and/or its determinant being zero or otherwise. As a corollary of our main result we also derive a closed formula for the Zassenhaus expansion. We apply our results to several special cases, most notably the parametrization of the product of two SU(2) matrices and a verification of the recent result of Van-Brunt and Visser (2015 J. Phys. A: Math. Theor. 48 225207) for complex 2×2 matrices, in this latter case deriving also the related Zassenhaus formula which turns out to be quite simple. We then show that this simple formula should be valid for all matrices and operators.

Component Identification and Item Difficulty of Raven's Matrices Items.

ERIC Educational Resources Information Center

Green, Kathy E.; Kluever, Raymond C.

Item components that might contribute to the difficulty of items on the Raven Colored Progressive Matrices (CPM) and the Standard Progressive Matrices (SPM) were studied. Subjects providing responses to CPM items were 269 children aged 2 years 9 months to 11 years 8 months, most of whom were referred for testing as potentially gifted. A second…

Graph-Theoretic Representations for Proximity Matrices through Strongly-Anti-Robinson or Circular Strongly-Anti-Robinson Matrices.

ERIC Educational Resources Information Center

Hubert, Lawrence; Arabie, Phipps; Meulman, Jacqueline

1998-01-01

Introduces a method for fitting order-constrained matrices that satisfy the strongly anti-Robinson restrictions (SAR). The method permits a representation of the fitted values in a (least-squares) SAR approximating matrix as lengths of paths in a graph. The approach is illustrated with a published proximity matrix. (SLD)

On r-circulant matrices with Fibonacci and Lucas numbers having arithmetic indices

NASA Astrophysics Data System (ADS)

Bueno, Aldous Cesar F.

2017-11-01

We investigate r-circulant matrices whose entries are Fibonacci and Lucas numbers having arithmetic indices. We then solve for the eigenvalues, determinant, Euclidean norm and the bounds for the spectral norm of the matrices. We also present some special cases and some results on identities and divisibility. Lastly, we present an open problem.

Skin Equivalent Tissue-Engineered Construct: Co-Cultured Fibroblasts/ Keratinocytes on 3D Matrices of Sericin Hope Cocoons

PubMed Central

Nayak, Sunita; Dey, Sancharika; Kundu, Subhas C.

2013-01-01

The development of effective and alternative tissue-engineered skin replacements to autografts, allografts and xenografts has became a clinical requirement due to the problems related to source of donor tissue and the perceived risk of disease transmission. In the present study 3D tissue engineered construct of sericin is developed using co-culture of keratinocytes on the upper surface of the fabricated matrices and with fibroblasts on lower surface. Sericin is obtained from “Sericin Hope” silkworm of Bombyx mori mutant and is extracted from cocoons by autoclave. Porous sericin matrices are prepared by freeze dried method using genipin as crosslinker. The matrices are characterized biochemically and biophysically. The cell proliferation and viability of co-cultured fibroblasts and keratinocytes on matrices for at least 28 days are observed by live/dead assay, Alamar blue assay, and by dual fluorescent staining. The growth of the fibroblasts and keratinocytes in co-culture is correlated with the expression level of TGF-β, b-FGF and IL-8 in the cultured supernatants by enzyme-linked immunosorbent assay. The histological analysis further demonstrates a multi-layered stratified epidermal layer of uninhibited keratinocytes in co-cultured constructs. Presence of involucrin, collagen IV and the fibroblast surface protein in immuno-histochemical stained sections of co-cultured matrices indicates the significance of paracrine signaling between keratinocytes and fibroblasts in the expression of extracellular matrix protein for dermal repair. No significant amount of pro inflammatory cytokines (TNF-α, IL-1β and nitric oxide) production are evidenced when macrophages grown on the sericin matrices. The results all together depict the potentiality of sericin 3D matrices as skin equivalent tissue engineered construct in wound repair. PMID:24058626

Skin equivalent tissue-engineered construct: co-cultured fibroblasts/ keratinocytes on 3D matrices of sericin hope cocoons.

PubMed

Nayak, Sunita; Dey, Sancharika; Kundu, Subhas C

2013-01-01

The development of effective and alternative tissue-engineered skin replacements to autografts, allografts and xenografts has became a clinical requirement due to the problems related to source of donor tissue and the perceived risk of disease transmission. In the present study 3D tissue engineered construct of sericin is developed using co-culture of keratinocytes on the upper surface of the fabricated matrices and with fibroblasts on lower surface. Sericin is obtained from "Sericin Hope" silkworm of Bombyx mori mutant and is extracted from cocoons by autoclave. Porous sericin matrices are prepared by freeze dried method using genipin as crosslinker. The matrices are characterized biochemically and biophysically. The cell proliferation and viability of co-cultured fibroblasts and keratinocytes on matrices for at least 28 days are observed by live/dead assay, Alamar blue assay, and by dual fluorescent staining. The growth of the fibroblasts and keratinocytes in co-culture is correlated with the expression level of TGF-β, b-FGF and IL-8 in the cultured supernatants by enzyme-linked immunosorbent assay. The histological analysis further demonstrates a multi-layered stratified epidermal layer of uninhibited keratinocytes in co-cultured constructs. Presence of involucrin, collagen IV and the fibroblast surface protein in immuno-histochemical stained sections of co-cultured matrices indicates the significance of paracrine signaling between keratinocytes and fibroblasts in the expression of extracellular matrix protein for dermal repair. No significant amount of pro inflammatory cytokines (TNF-α, IL-1β and nitric oxide) production are evidenced when macrophages grown on the sericin matrices. The results all together depict the potentiality of sericin 3D matrices as skin equivalent tissue engineered construct in wound repair.

Agricultural matrices affect ground ant assemblage composition inside forest fragments

PubMed Central

Dos Santos, Iracenir Andrade; Ramos, Flavio Nunes; Majer, Jonathan David; Vilela, Evaldo Ferreira

2018-01-01

The establishment of agricultural matrices generally involves deforestation, which leads to fragmentation of the remaining forest. This fragmentation can affect forest dynamics both positively and negatively. Since most animal species are affected, certain groups can be used to measure the impact of such fragmentation. This study aimed to measure the impacts of agricultural crops (matrices) on ant communities of adjacent lower montane Atlantic rainforest fragments. We sampled nine forest fragments at locations surrounded by different agricultural matrices, namely: coffee (3 replicates); sugarcane (3); and pasture (3). At each site we installed pitfall traps along a 500 m transect from the interior of the matrix to the interior of the fragment (20 pitfall traps ~25 m apart). Each transect was partitioned into four categories: interior of the matrix; edge of the matrix; edge of the fragment; and interior of the fragment. For each sample site, we measured ant species richness and ant community composition within each transect category. Ant richness and composition differed between fragments and matrices. Each sample location had a specific composition of ants, probably because of the influence of the nature and management of the agricultural matrices. Species composition in the coffee matrix had the highest similarity to its corresponding fragment. The variability in species composition within forest fragments surrounded by pasture was greatest when compared with forest fragments surrounded by sugarcane or, to a lesser extent, coffee. Functional guild composition differed between locations, but the most representative guild was ‘generalist’ both in the agricultural matrices and forest fragments. Our results are important for understanding how agricultural matrices act on ant communities, and also, how these isolated forest fragments could act as an island of biodiversity in an ‘ocean of crops’. PMID:29791493

Cell-Adhesive Matrices Composed of RGD Peptide-Displaying M13 Bacteriophage/Poly(lactic-co-glycolic acid) Nanofibers Beneficial to Myoblast Differentiation.

PubMed

Shin, Yong Cheol; Lee, Jong Ho; Jin, Linhua; Kim, Min Jeong; Kim, Chuntae; Hong, Suck Won; Oh, Jin Woo; Han, Dong-Wook

2015-10-01

Recently, there has been considerable effort to develop suitable scaffolds for tissue engineering applications. Cell adhesion is a prerequisite for cells to survive. In nature, the extracellular matrix (ECM) plays this role. Therefore, an ideal scaffold should be structurally similar to the natural ECM and have biocompatibility and biodegradability. In addition, the scaffold should have biofunctionality, which provides the potent ability to enhance the cellular behaviors, such as adhesion, proliferation and differentiation. This study concentrates on fabricating cell-adhesive matrices composed of RGD peptide-displaying M13 bacteriophage (RGD-M13 phage) and poly(lactic-co-glycolic acid, PLGA) nanofibers. Long rod-shaped M13 bacteriophages are non-toxic and can express many desired proteins on their surface. A genetically engineered M13 phage was constructed to display RGD peptides on its surface. PLGA is a biodegradable polymer with excellent biocompatibility and suitable physicochemical property for adhesive matrices. In this study, RGD-M13 phage/PLGA hybrid nanofiber matrices were fabricated by electrospinning. The physicochemical properties of these matrices were characterized by scanning electron microscopy, atomic force microscopy, Raman spectroscopy, and contact angle measurement. In addition, the cellular behaviors, such as the initial attachment, proliferation and differentiation, were analyzed by a CCK-8 assay and immunofluorescence staining to evaluate the potential application of these matrices to tissue engineering scaffolds. The RGD-M13 phage/PLGA nanofiber matrices could enhance the cellular behaviors and promote the differentiation of C2C12 myoblasts. These results suggest that the RGD-M13 phage/PLGA nanofiber matrices are beneficial to myoblast differentiation and can serve as effective tissue engineering scaffolds.

Agricultural matrices affect ground ant assemblage composition inside forest fragments.

PubMed

Assis, Diego Santana; Dos Santos, Iracenir Andrade; Ramos, Flavio Nunes; Barrios-Rojas, Katty Elena; Majer, Jonathan David; Vilela, Evaldo Ferreira

2018-01-01

The establishment of agricultural matrices generally involves deforestation, which leads to fragmentation of the remaining forest. This fragmentation can affect forest dynamics both positively and negatively. Since most animal species are affected, certain groups can be used to measure the impact of such fragmentation. This study aimed to measure the impacts of agricultural crops (matrices) on ant communities of adjacent lower montane Atlantic rainforest fragments. We sampled nine forest fragments at locations surrounded by different agricultural matrices, namely: coffee (3 replicates); sugarcane (3); and pasture (3). At each site we installed pitfall traps along a 500 m transect from the interior of the matrix to the interior of the fragment (20 pitfall traps ~25 m apart). Each transect was partitioned into four categories: interior of the matrix; edge of the matrix; edge of the fragment; and interior of the fragment. For each sample site, we measured ant species richness and ant community composition within each transect category. Ant richness and composition differed between fragments and matrices. Each sample location had a specific composition of ants, probably because of the influence of the nature and management of the agricultural matrices. Species composition in the coffee matrix had the highest similarity to its corresponding fragment. The variability in species composition within forest fragments surrounded by pasture was greatest when compared with forest fragments surrounded by sugarcane or, to a lesser extent, coffee. Functional guild composition differed between locations, but the most representative guild was 'generalist' both in the agricultural matrices and forest fragments. Our results are important for understanding how agricultural matrices act on ant communities, and also, how these isolated forest fragments could act as an island of biodiversity in an 'ocean of crops'.

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

Braunstein, Samuel L.; Ghosh, Sibasish; Severini, Simone

We reconsider density matrices of graphs as defined in quant-ph/0406165. The density matrix of a graph is the combinatorial Laplacian of the graph normalized to have unit trace. We describe a simple combinatorial condition (the 'degree condition') to test the separability of density matrices of graphs. The condition is directly related to the Peres-Horodecki partial transposition condition. We prove that the degree condition is necessary for separability, and we conjecture that it is also sufficient. We prove special cases of the conjecture involving nearest-point graphs and perfect matchings. We observe that the degree condition appears to have a value beyondmore » the density matrices of graphs. In fact, we point out that circulant density matrices and other matrices constructed from groups always satisfy the condition and indeed are separable with respect to any split. We isolate a number of problems and delineate further generalizations.« less

Tensor Sparse Coding for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikos

2013-08-02

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Tensor sparse coding for positive definite matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2014-03-01

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for example, image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

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.

Compound matrices

NASA Astrophysics Data System (ADS)

Kravvaritis, Christos; Mitrouli, Marilena

2009-02-01

This paper studies the possibility to calculate efficiently compounds of real matrices which have a special form or structure. The usefulness of such an effort lies in the fact that the computation of compound matrices, which is generally noneffective due to its high complexity, is encountered in several applications. A new approach for computing the Singular Value Decompositions (SVD's) of the compounds of a matrix is proposed by establishing the equality (up to a permutation) between the compounds of the SVD of a matrix and the SVD's of the compounds of the matrix. The superiority of the new idea over the standard method is demonstrated. Similar approaches with some limitations can be adopted for other matrix factorizations, too. Furthermore, formulas for the n - 1 compounds of Hadamard matrices are derived, which dodge the strenuous computations of the respective numerous large determinants. Finally, a combinatorial counting technique for finding the compounds of diagonal matrices is illustrated.

Three-dimensional polarization algebra.

PubMed

R Sheppard, Colin J; Castello, Marco; Diaspro, Alberto

2016-10-01

If light is focused or collected with a high numerical aperture lens, as may occur in imaging and optical encryption applications, polarization should be considered in three dimensions (3D). The matrix algebra of polarization behavior in 3D is discussed. It is useful to convert between the Mueller matrix and two different Hermitian matrices, representing an optical material or system, which are in the literature. Explicit transformation matrices for converting the column vector form of these different matrices are extended to the 3D case, where they are large (81×81) but can be generated using simple rules. It is found that there is some advantage in using a generalization of the Chandrasekhar phase matrix treatment, rather than that based on Gell-Mann matrices, as the resultant matrices are of simpler form and reduce to the two-dimensional case more easily. Explicit expressions are given for 3D complex field components in terms of Chandrasekhar-Stokes parameters.

Toward a better determination of dairy powders surface composition through XPS matrices development.

PubMed

Nikolova, Y; Petit, J; Sanders, C; Gianfrancesco, A; Scher, J; Gaiani, C

2015-01-01

The surface composition of dairy powders prepared by mixing various amounts of micellar casein (MC), whey proteins isolate (WPI), lactose, and anhydrous milk fat (AMF) was investigated by XPS measurements. The use of matrices are generally accepted to transform surface atomic composition (i.e., C, O, N contents) into surface component composition (i.e., lactose, proteins, lipids). These atomic-based matrices were revisited and two new matrices based on the surface bond composition were developed. Surface compositions obtained from atomic and bond-based matrices were compared. A successful matrix allowing good correlations between XPS predicted and theoretical surface composition for powders free from fat was identified. Nevertheless, samples containing milk fat were found to present a possible segregation of components owing to the AMF overrepresentation on the surface. Supplementary analyses (FTIR, SEM) were carried out in order to investigate the homogeneity of the mixtures. Copyright © 2014 Elsevier B.V. All rights reserved.

Unusual analyte-matrix adduct ions and mechanism of their formation in MALDI TOF MS of benzene-1,3,5-tricarboxamide and urea compounds.

PubMed

Lou, Xianwen; Fransen, Michel; Stals, Patrick J M; Mes, Tristan; Bovee, Ralf; van Dongen, Joost J L; Meijer, E W

2013-09-01

Analyte-matrix adducts are normally absent under typical matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS) conditions. Interestingly, though, in the analysis of several types of organic compounds synthesized in our laboratory, analyte-matrix adduct ion peaks were always recorded when common MALDI matrices such as 4-hydroxy-α-cyanocinnamic acid (CHCA) were used. These compounds are mainly those with a benzene-1,3,5-tricarboxamide (BTA) or urea moiety, which are important building blocks to make new functional supramolecular materials. The possible mechanism of the adduct formation was investigated. A shared feature of the compounds studied is that they can form intermolecular hydrogen bonding with matrices like CHCA. The intermolecular hydrogen bonding will make the association between analyte ions and matrix molecules stronger. As a result, the analyte ions and matrix molecules in MALDI clusters will become more difficult to be separated from each other. Furthermore, it was found that analyte ions were mainly adducted with matrix salts, which is probably due to the much lower volatility of the salts compared with that of their corresponding matrix acids. It seems that the analyte-matrix adduct formation for our compounds are caused by the incomplete evaporation of matrix molecules from the MALDI clusters because of the combined effects of enhanced intermolecular interaction between analyte-matrix and of the low volatility of matrix salts. Based on these findings, strategies to suppress the analyte-matrix adduction are briefly discussed. In return, the positive results of using these strategies support the proposed mechanism of the analyte-matrix adduct formation.

The Bioactivity of Cartilage Extracellular Matrix in Articular Cartilage Regeneration

PubMed Central

Sutherland, Amanda J.; Converse, Gabriel L.; Hopkins, Richard A.; Detamore, Michael S.

2014-01-01

Cartilage matrix is a particularly promising acellular material for cartilage regeneration given the evidence supporting its chondroinductive character. The ‘raw materials’ of cartilage matrix can serve as building blocks and signals for enhanced tissue regeneration. These matrices can be created by chemical or physical methods: physical methods disrupt cellular membranes and nuclei but may not fully remove all cell components and DNA, whereas chemical methods when combined with physical methods are particularly effective in fully decellularizing such materials. Critical endpoints include no detectable residual DNA or immunogenic antigens. It is important to first delineate between the sources of the cartilage matrix, i.e., derived from matrix produced by cells in vitro or from native tissue, and then to further characterize the cartilage matrix based on the processing method, i.e., decellularization or devitalization. With these distinctions, four types of cartilage matrices exist: decellularized native cartilage (DCC), devitalized native cartilage (DVC), decellularized cell derived matrix (DCCM), and devitalized cell derived matrix (DVCM). Delivery of cartilage matrix may be a straightforward approach without the need for additional cells or growth factors. Without additional biological additives, cartilage matrix may be attractive from a regulatory and commercialization standpoint. Source and delivery method are important considerations for clinical translation. Only one currently marketed cartilage matrix medical device is decellularized, although trends in filed patents suggest additional decellularized products may be available in the future. To choose the most relevant source and processing for cartilage matrix, qualifying testing needs to include targeting the desired application, optimizing delivery of the material, identify relevant FDA regulations, assess availability of raw materials, and immunogenic properties of the product. PMID:25044502

Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.

PubMed

Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I

2017-01-01

This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.

SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT

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

Modiri, A; Hagan, A; Gu, X

Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning systemmore » (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.« less

Research on numerical algorithms for large space structures

NASA Technical Reports Server (NTRS)

Denman, E. D.

1982-01-01

Numerical algorithms for large space structures were investigated with particular emphasis on decoupling method for analysis and design. Numerous aspects of the analysis of large systems ranging from the algebraic theory to lambda matrices to identification algorithms were considered. A general treatment of the algebraic theory of lambda matrices is presented and the theory is applied to second order lambda matrices.

SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

PubMed

Wassermann, Anne Mai; Haebel, Peter; Weskamp, Nils; Bajorath, Jürgen

2012-07-23

We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

Spectral density of mixtures of random density matrices for qubits

NASA Astrophysics Data System (ADS)

Zhang, Lin; Wang, Jiamei; Chen, Zhihua

2018-06-01

We derive the spectral density of the equiprobable mixture of two random density matrices of a two-level quantum system. We also work out the spectral density of mixture under the so-called quantum addition rule. We use the spectral densities to calculate the average entropy of mixtures of random density matrices, and show that the average entropy of the arithmetic-mean-state of n qubit density matrices randomly chosen from the Hilbert-Schmidt ensemble is never decreasing with the number n. We also get the exact value of the average squared fidelity. Some conjectures and open problems related to von Neumann entropy are also proposed.

Efficiency of fly ash belite cement and zeolite matrices for immobilizing cesium.

PubMed

Goñi, S; Guerrero, A; Lorenzo, M P

2006-10-11

The efficiency of innovative matrices for immobilizing cesium is presented in this work. The matrix formulation included the use of fly ash belite cement (FABC-2-W) and gismondine-type Na-P1 zeolite, both of which are synthesized from fly ash of coal combustion. The efficiency for immobilizing cesium is evaluated from the leaching test ANSI/ANS 16.1-1986 at the temperature of 40 degrees C, from which the apparent diffusion coefficient of cesium is obtained. Matrices with 100% of FABC-2-W are used as a reference. The integrity of matrices is evaluated by porosity and pore-size distribution from mercury intrusion porosimetry, X-ray diffraction and nitrogen adsorption analyses. Both matrices can be classified as good solidify systems for cesium, specially the FABC-2-W/zeolite matrix in which the replacement of 50% of belite cement by the gismondine-type Na-P1 zeolite caused a decrease of two orders of magnitude of cesium mean Effective Diffusion Coefficient (D(e)) (2.8e-09 cm(2)/s versus 2.2e-07 cm(2)/s, for FABC-2-W/zeolite and FABC-2-W matrices, respectively).

MALDI matrices for low molecular weight compounds: an endless story?

PubMed

Calvano, Cosima Damiana; Monopoli, Antonio; Cataldi, Tommaso R I; Palmisano, Francesco

2018-04-23

Since its introduction in the 1980s, matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) has gained a prominent role in the analysis of high molecular weight biomolecules such as proteins, peptides, oligonucleotides, and polysaccharides. Its application to low molecular weight compounds has remained for long time challenging due to the spectral interferences produced by conventional organic matrices in the low m/z window. To overcome this problem, specific sample preparation such as analyte/matrix derivatization, addition of dopants, or sophisticated deposition technique especially useful for imaging experiments, have been proposed. Alternative approaches based on second generation (rationally designed) organic matrices, ionic liquids, and inorganic matrices, including metallic nanoparticles, have been the object of intense and continuous research efforts. Definite evidences are now provided that MALDI MS represents a powerful and invaluable analytical tool also for small molecules, including their quantification, thus opening new, exciting applications in metabolomics and imaging mass spectrometry. This review is intended to offer a concise critical overview of the most recent achievements about MALDI matrices capable of specifically address the challenging issue of small molecules analysis. Graphical abstract An ideal Book of matrices for MALDI MS of small molecules.

Optimal implicit 2-D finite differences to model wave propagation in poroelastic media

NASA Astrophysics Data System (ADS)

Itzá, Reymundo; Iturrarán-Viveros, Ursula; Parra, Jorge O.

2016-08-01

Numerical modeling of seismic waves in heterogeneous porous reservoir rocks is an important tool for the interpretation of seismic surveys in reservoir engineering. We apply globally optimal implicit staggered-grid finite differences (FD) to model 2-D wave propagation in heterogeneous poroelastic media at a low-frequency range (<10 kHz). We validate the numerical solution by comparing it to an analytical-transient solution obtaining clear seismic wavefields including fast P and slow P and S waves (for a porous media saturated with fluid). The numerical dispersion and stability conditions are derived using von Neumann analysis, showing that over a wide range of porous materials the Courant condition governs the stability and this optimal implicit scheme improves the stability of explicit schemes. High-order explicit FD can be replaced by some lower order optimal implicit FD so computational cost will not be as expensive while maintaining the accuracy. Here, we compute weights for the optimal implicit FD scheme to attain an accuracy of γ = 10-8. The implicit spatial differentiation involves solving tridiagonal linear systems of equations through Thomas' algorithm.

Parallelization of elliptic solver for solving 1D Boussinesq model

NASA Astrophysics Data System (ADS)

Tarwidi, D.; Adytia, D.

2018-03-01

In this paper, a parallel implementation of an elliptic solver in solving 1D Boussinesq model is presented. Numerical solution of Boussinesq model is obtained by implementing a staggered grid scheme to continuity, momentum, and elliptic equation of Boussinesq model. Tridiagonal system emerging from numerical scheme of elliptic equation is solved by cyclic reduction algorithm. The parallel implementation of cyclic reduction is executed on multicore processors with shared memory architectures using OpenMP. To measure the performance of parallel program, large number of grids is varied from 28 to 214. Two test cases of numerical experiment, i.e. propagation of solitary and standing wave, are proposed to evaluate the parallel program. The numerical results are verified with analytical solution of solitary and standing wave. The best speedup of solitary and standing wave test cases is about 2.07 with 214 of grids and 1.86 with 213 of grids, respectively, which are executed by using 8 threads. Moreover, the best efficiency of parallel program is 76.2% and 73.5% for solitary and standing wave test cases, respectively.

Global synchronization algorithms for the Intel iPSC/860

NASA Technical Reports Server (NTRS)

Seidel, Steven R.; Davis, Mark A.

1992-01-01

In a distributed memory multicomputer that has no global clock, global processor synchronization can only be achieved through software. Global synchronization algorithms are used in tridiagonal systems solvers, CFD codes, sequence comparison algorithms, and sorting algorithms. They are also useful for event simulation, debugging, and for solving mutual exclusion problems. For the Intel iPSC/860 in particular, global synchronization can be used to ensure the most effective use of the communication network for operations such as the shift, where each processor in a one-dimensional array or ring concurrently sends a message to its right (or left) neighbor. Three global synchronization algorithms are considered for the iPSC/860: the gysnc() primitive provided by Intel, the PICL primitive sync0(), and a new recursive doubling synchronization (RDS) algorithm. The performance of these algorithms is compared to the performance predicted by communication models of both the long and forced message protocols. Measurements of the cost of shift operations preceded by global synchronization show that the RDS algorithm always synchronizes the nodes more precisely and costs only slightly more than the other two algorithms.