Dai-Kou type conjugate gradient methods with a line search only using gradient.

PubMed

Huang, Yuanyuan; Liu, Changhe

2017-01-01

In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical tests and comparisons with the PRP+ conjugate gradient method only using gradient show that the methods are efficient.

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1989-01-01

The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.

Algorithms for accelerated convergence of adaptive PCA.

PubMed

Chatterjee, C; Kang, Z; Roychowdhury, V P

2000-01-01

We derive and discuss new adaptive algorithms for principal component analysis (PCA) that are shown to converge faster than the traditional PCA algorithms due to Oja, Sanger, and Xu. It is well known that traditional PCA algorithms that are derived by using gradient descent on an objective function are slow to converge. Furthermore, the convergence of these algorithms depends on appropriate choices of the gain sequences. Since online applications demand faster convergence and an automatic selection of gains, we present new adaptive algorithms to solve these problems. We first present an unconstrained objective function, which can be minimized to obtain the principal components. We derive adaptive algorithms from this objective function by using: 1) gradient descent; 2) steepest descent; 3) conjugate direction; and 4) Newton-Raphson methods. Although gradient descent produces Xu's LMSER algorithm, the steepest descent, conjugate direction, and Newton-Raphson methods produce new adaptive algorithms for PCA. We also provide a discussion on the landscape of the objective function, and present a global convergence proof of the adaptive gradient descent PCA algorithm using stochastic approximation theory. Extensive experiments with stationary and nonstationary multidimensional Gaussian sequences show faster convergence of the new algorithms over the traditional gradient descent methods.We also compare the steepest descent adaptive algorithm with state-of-the-art methods on stationary and nonstationary sequences.

Application of the conjugate-gradient method to ground-water models

USGS Publications Warehouse

Manteuffel, T.A.; Grove, D.B.; Konikow, Leonard F.

1984-01-01

The conjugate-gradient method can solve efficiently and accurately finite-difference approximations to the ground-water flow equation. An aquifer-simulation model using the conjugate-gradient method was applied to a problem of ground-water flow in an alluvial aquifer at the Rocky Mountain Arsenal, Denver, Colorado. For this application, the accuracy and efficiency of the conjugate-gradient method compared favorably with other available methods for steady-state flow. However, its efficiency relative to other available methods depends on the nature of the specific problem. The main advantage of the conjugate-gradient method is that it does not require the use of iteration parameters, thereby eliminating this partly subjective procedure. (USGS)

Automated Calibration For Numerical Models Of Riverflow

NASA Astrophysics Data System (ADS)

Fernandez, Betsaida; Kopmann, Rebekka; Oladyshkin, Sergey

2017-04-01

Calibration of numerical models is fundamental since the beginning of all types of hydro system modeling, to approximate the parameters that can mimic the overall system behavior. Thus, an assessment of different deterministic and stochastic optimization methods is undertaken to compare their robustness, computational feasibility, and global search capacity. Also, the uncertainty of the most suitable methods is analyzed. These optimization methods minimize the objective function that comprises synthetic measurements and simulated data. Synthetic measurement data replace the observed data set to guarantee an existing parameter solution. The input data for the objective function derivate from a hydro-morphological dynamics numerical model which represents an 180-degree bend channel. The hydro- morphological numerical model shows a high level of ill-posedness in the mathematical problem. The minimization of the objective function by different candidate methods for optimization indicates a failure in some of the gradient-based methods as Newton Conjugated and BFGS. Others reveal partial convergence, such as Nelder-Mead, Polak und Ribieri, L-BFGS-B, Truncated Newton Conjugated, and Trust-Region Newton Conjugated Gradient. Further ones indicate parameter solutions that range outside the physical limits, such as Levenberg-Marquardt and LeastSquareRoot. Moreover, there is a significant computational demand for genetic optimization methods, such as Differential Evolution and Basin-Hopping, as well as for Brute Force methods. The Deterministic Sequential Least Square Programming and the scholastic Bayes Inference theory methods present the optimal optimization results. keywords: Automated calibration of hydro-morphological dynamic numerical model, Bayesian inference theory, deterministic optimization 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.

Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.

PubMed

Temel, Burcin; Mills, Greg; Metiu, Horia

2008-03-27

We describe and test an implementation, using a basis set of Chebyshev polynomials, of a variational method for solving scattering problems in quantum mechanics. This minimum error method (MEM) determines the wave function Psi by minimizing the least-squares error in the function (H Psi - E Psi), where E is the desired scattering energy. We compare the MEM to an alternative, the Kohn variational principle (KVP), by solving the Secrest-Johnson model of two-dimensional inelastic scattering, which has been studied previously using the KVP and for which other numerical solutions are available. We use a conjugate gradient (CG) method to minimize the error, and by preconditioning the CG search, we are able to greatly reduce the number of iterations necessary; the method is thus faster and more stable than a matrix inversion, as is required in the KVP. Also, we avoid errors due to scattering off of the boundaries, which presents substantial problems for other methods, by matching the wave function in the interaction region to the correct asymptotic states at the specified energy; the use of Chebyshev polynomials allows this boundary condition to be implemented accurately. The use of Chebyshev polynomials allows for a rapid and accurate evaluation of the kinetic energy. This basis set is as efficient as plane waves but does not impose an artificial periodicity on the system. There are problems in surface science and molecular electronics which cannot be solved if periodicity is imposed, and the Chebyshev basis set is a good alternative in such situations.

A technique for accelerating the convergence of restarted GMRES

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

Baker, A H; Jessup, E R; Manteuffel, T

2004-03-09

We have observed that the residual vectors at the end of each restart cycle of restarted GMRES often alternate direction in a cyclic fashion, thereby slowing convergence. We present a new technique for accelerating the convergence of restarted GMRES by disrupting this alternating pattern. The new algorithm resembles a full conjugate gradient method with polynomial preconditioning, and its implementation requires minimal changes to the standard restarted GMRES algorithm.

Estimation of the zeta potential and the dielectric constant using velocity measurements in the electroosmotic flows.

PubMed

Park, H M; Hong, S M

2006-12-15

In this paper we develop a method for the determination of the zeta potential zeta and the dielectric constant epsilon by exploiting velocity measurements of the electroosmotic flow in microchannels. The inverse problem is solved through the minimization of a performance function utilizing the conjugate gradient method. The present method is found to estimate zeta and epsilon with reasonable accuracy even with noisy velocity measurements.

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.

Quantifying the Energy Efficiency of Object Recognition and Optical Flow

DTIC Science & Technology

2014-03-28

other linear solvers, such as conjugate- gradient (CG), preconditioned conjugate-gradient (PCG), and red-black Gauss Seidel (RB). We have also... Seidel , and conjugate gradient solvers. We are interested in the energy it takes to get a given solution quality. In Figure 6, we plot the quality of...in terms of Joules. Conversely, our implementation of red-black Gauss Seidel proves to be very inefficient when we consider Joules instead of just

A three-term conjugate gradient method under the strong-Wolfe line search

NASA Astrophysics Data System (ADS)

Khadijah, Wan; Rivaie, Mohd; Mamat, Mustafa

2017-08-01

Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison.

SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method.

PubMed

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.

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).

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.

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

NASA Technical Reports Server (NTRS)

Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

1993-01-01

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

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

PubMed

Vogel, Curtis R; Yang, Qiang

2006-08-21

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

Comparison of genetic algorithms with conjugate gradient methods

NASA Technical Reports Server (NTRS)

Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.

1972-01-01

Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.

Iterative methods for elliptic finite element equations on general meshes

NASA Technical Reports Server (NTRS)

Nicolaides, R. A.; Choudhury, Shenaz

1986-01-01

Iterative methods for arbitrary mesh discretizations of elliptic partial differential equations are surveyed. The methods discussed are preconditioned conjugate gradients, algebraic multigrid, deflated conjugate gradients, an element-by-element techniques, and domain decomposition. Computational results are included.

Orderings for conjugate gradient preconditionings

NASA Technical Reports Server (NTRS)

Ortega, James M.

1991-01-01

The effect of orderings on the rate of convergence of the conjugate gradient method with SSOR or incomplete Cholesky preconditioning is examined. Some results also are presented that help to explain why red/black ordering gives an inferior rate of convergence.

Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method

NASA Astrophysics Data System (ADS)

Sun, Yong; Meng, Zhaohai; Li, Fengting

2018-03-01

Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.

SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method

PubMed Central

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller’s scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller’s algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller’s algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller’s algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data. PMID:26958442

Iterative solution of the inverse Cauchy problem for an elliptic equation by the conjugate gradient method

NASA Astrophysics Data System (ADS)

Vasil'ev, V. I.; Kardashevsky, A. M.; Popov, V. V.; Prokopev, G. A.

2017-10-01

This article presents results of computational experiment carried out using a finite-difference method for solving the inverse Cauchy problem for a two-dimensional elliptic equation. The computational algorithm involves an iterative determination of the missing boundary condition from the override condition using the conjugate gradient method. The results of calculations are carried out on the examples with exact solutions as well as at specifying an additional condition with random errors are presented. Results showed a high efficiency of the iterative method of conjugate gradients for numerical solution

A feasible DY conjugate gradient method for linear equality constraints

NASA Astrophysics Data System (ADS)

LI, Can

2017-09-01

In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.

Non-preconditioned conjugate gradient on cell and FPGA based hybrid supercomputer nodes

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

Dubois, David H; Dubois, Andrew J; Boorman, Thomas M

2009-01-01

This work presents a detailed implementation of a double precision, non-preconditioned, Conjugate Gradient algorithm on a Roadrunner heterogeneous supercomputer node. These nodes utilize the Cell Broadband Engine Architecture{sup TM} in conjunction with x86 Opteron{sup TM} processors from AMD. We implement a common Conjugate Gradient algorithm, on a variety of systems, to compare and contrast performance. Implementation results are presented for the Roadrunner hybrid supercomputer, SRC Computers, Inc. MAPStation SRC-6 FPGA enhanced hybrid supercomputer, and AMD Opteron only. In all hybrid implementations wall clock time is measured, including all transfer overhead and compute timings.

Non-preconditioned conjugate gradient on cell and FPCA-based hybrid supercomputer nodes

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

Dubois, David H; Dubois, Andrew J; Boorman, Thomas M

2009-03-10

This work presents a detailed implementation of a double precision, Non-Preconditioned, Conjugate Gradient algorithm on a Roadrunner heterogeneous supercomputer node. These nodes utilize the Cell Broadband Engine Architecture{trademark} in conjunction with x86 Opteron{trademark} processors from AMD. We implement a common Conjugate Gradient algorithm, on a variety of systems, to compare and contrast performance. Implementation results are presented for the Roadrunner hybrid supercomputer, SRC Computers, Inc. MAPStation SRC-6 FPGA enhanced hybrid supercomputer, and AMD Opteron only. In all hybrid implementations wall clock time is measured, including all transfer overhead and compute timings.

Comparing direct and iterative equation solvers in a large structural analysis software system

NASA Technical Reports Server (NTRS)

Poole, E. L.

1991-01-01

Two direct Choleski equation solvers and two iterative preconditioned conjugate gradient (PCG) equation solvers used in a large structural analysis software system are described. The two direct solvers are implementations of the Choleski method for variable-band matrix storage and sparse matrix storage. The two iterative PCG solvers include the Jacobi conjugate gradient method and an incomplete Choleski conjugate gradient method. The performance of the direct and iterative solvers is compared by solving several representative structural analysis problems. Some key factors affecting the performance of the iterative solvers relative to the direct solvers are identified.

A modified form of conjugate gradient method for unconstrained optimization problems

NASA Astrophysics Data System (ADS)

Ghani, Nur Hamizah Abdul; Rivaie, Mohd.; Mamat, Mustafa

2016-06-01

Conjugate gradient (CG) methods have been recognized as an interesting technique to solve optimization problems, due to the numerical efficiency, simplicity and low memory requirements. In this paper, we propose a new CG method based on the study of Rivaie et al. [7] (Comparative study of conjugate gradient coefficient for unconstrained Optimization, Aus. J. Bas. Appl. Sci. 5(2011) 947-951). Then, we show that our method satisfies sufficient descent condition and converges globally with exact line search. Numerical results show that our proposed method is efficient for given standard test problems, compare to other existing CG methods.

Gradient optimization and nonlinear control

NASA Technical Reports Server (NTRS)

Hasdorff, L.

1976-01-01

The book represents an introduction to computation in control by an iterative, gradient, numerical method, where linearity is not assumed. The general language and approach used are those of elementary functional analysis. The particular gradient method that is emphasized and used is conjugate gradient descent, a well known method exhibiting quadratic convergence while requiring very little more computation than simple steepest descent. Constraints are not dealt with directly, but rather the approach is to introduce them as penalty terms in the criterion. General conjugate gradient descent methods are developed and applied to problems in control.

Experiments with conjugate gradient algorithms for homotopy curve tracking

NASA Technical Reports Server (NTRS)

Irani, Kashmira M.; Ribbens, Calvin J.; Watson, Layne T.; Kamat, Manohar P.; Walker, Homer F.

1991-01-01

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

Conjugate gradient minimisation approach to generating holographic traps for ultracold atoms.

PubMed

Harte, Tiffany; Bruce, Graham D; Keeling, Jonathan; Cassettari, Donatella

2014-11-03

Direct minimisation of a cost function can in principle provide a versatile and highly controllable route to computational hologram generation. Here we show that the careful design of cost functions, combined with numerically efficient conjugate gradient minimisation, establishes a practical method for the generation of holograms for a wide range of target light distributions. This results in a guided optimisation process, with a crucial advantage illustrated by the ability to circumvent optical vortex formation during hologram calculation. We demonstrate the implementation of the conjugate gradient method for both discrete and continuous intensity distributions and discuss its applicability to optical trapping of ultracold atoms.

Conjugate gradient filtering of instantaneous normal modes, saddles on the energy landscape, and diffusion in liquids.

PubMed

Chowdhary, J; Keyes, T

2002-02-01

Instantaneous normal modes (INM's) are calculated during a conjugate-gradient (CG) descent of the potential energy landscape, starting from an equilibrium configuration of a liquid or crystal. A small number (approximately equal to 4) of CG steps removes all the Im-omega modes in the crystal and leaves the liquid with diffusive Im-omega which accurately represent the self-diffusion constant D. Conjugate gradient filtering appears to be a promising method, applicable to any system, of obtaining diffusive modes and facilitating INM theory of D. The relation of the CG-step dependent INM quantities to the landscape and its saddles is discussed.

Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.

PubMed

Yang, Qiang; Vogel, Curtis R; Ellerbroek, Brent L

2006-07-20

By 'atmospheric tomography' we mean the estimation of a layered atmospheric turbulence profile from measurements of the pupil-plane phase (or phase gradients) corresponding to several different guide star directions. We introduce what we believe to be a new Fourier domain preconditioned conjugate gradient (FD-PCG) algorithm for atmospheric tomography, and we compare its performance against an existing multigrid preconditioned conjugate gradient (MG-PCG) approach. Numerical results indicate that on conventional serial computers, FD-PCG is as accurate and robust as MG-PCG, but it is from one to two orders of magnitude faster for atmospheric tomography on 30 m class telescopes. Simulations are carried out for both natural guide stars and for a combination of finite-altitude laser guide stars and natural guide stars to resolve tip-tilt uncertainty.

Conjugate Gradient Algorithms For Manipulator Simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1991-01-01

Report discusses applicability of conjugate-gradient algorithms to computation of forward dynamics of robotic manipulators. Rapid computation of forward dynamics essential to teleoperation and other advanced robotic applications. Part of continuing effort to find algorithms meeting requirements for increased computational efficiency and speed. Method used for iterative solution of systems of linear equations.

Momentum-weighted conjugate gradient descent algorithm for gradient coil optimization.

PubMed

Lu, Hanbing; Jesmanowicz, Andrzej; Li, Shi-Jiang; Hyde, James S

2004-01-01

MRI gradient coil design is a type of nonlinear constrained optimization. A practical problem in transverse gradient coil design using the conjugate gradient descent (CGD) method is that wire elements move at different rates along orthogonal directions (r, phi, z), and tend to cross, breaking the constraints. A momentum-weighted conjugate gradient descent (MW-CGD) method is presented to overcome this problem. This method takes advantage of the efficiency of the CGD method combined with momentum weighting, which is also an intrinsic property of the Levenberg-Marquardt algorithm, to adjust step sizes along the three orthogonal directions. A water-cooled, 12.8 cm inner diameter, three axis torque-balanced gradient coil for rat imaging was developed based on this method, with an efficiency of 2.13, 2.08, and 4.12 mT.m(-1).A(-1) along X, Y, and Z, respectively. Experimental data demonstrate that this method can improve efficiency by 40% and field uniformity by 27%. This method has also been applied to the design of a gradient coil for the human brain, employing remote current return paths. The benefits of this design include improved gradient field uniformity and efficiency, with a shorter length than gradient coil designs using coaxial return paths. Copyright 2003 Wiley-Liss, Inc.

Targeting the 5T4 oncofetal glycoprotein with an antibody drug conjugate (A1mcMMAF) improves survival in patient-derived xenograft models of acute lymphoblastic leukemia.

PubMed

McGinn, Owen J; Krishnan, Shekhar; Bourquin, Jean-Pierre; Sapra, Puja; Dempsey, Clare; Saha, Vaskar; Stern, Peter L

2017-06-01

Outcome in childhood acute lymphoblastic leukemia is prognosticated from levels of minimal residual disease after remission induction therapy. Higher levels of minimal residual disease are associated with inferior results even with intensification of therapy, thus suggesting that identification and targeting of minimal residual disease cells could be a therapeutic strategy. Here we identify high expression of 5T4 in subclonal populations of patient-derived xenografts from patients with high, post-induction levels of minimal residual disease. 5T4-positive cells showed preferential ability to overcome the NOD- scid IL2Rγ null mouse xenograft barrier, migrated in vitro on a CXCL12 gradient, preferentially localized to bone marrow in vivo and displayed the ability to reconstitute the original clonal composition on limited dilution engraftment. Treatment with A1mcMMAF (a 5T4-antibody drug conjugate) significantly improved survival without overt toxicity in mice engrafted with a 5T4-positive acute lymphoblastic leukemia cell line. Mice engrafted with 5T4-positive patient-derived xenograft cells were treated with combination chemotherapy or dexamethasone alone and then given A1mcMMAF in the minimal residual disease setting. Combination chemotherapy was toxic to NOD- scid IL2Rγ null mice. While dexamethasone or A1mcMMAF alone improved outcomes, the sequential administration of dexamethasone and A1mcMMAF significantly improved survival ( P =0.0006) over either monotherapy. These data show that specifically targeting minimal residual disease cells improved outcomes and support further investigation of A1mcMMAF in patients with high-risk B-cell precursor acute lymphoblastic leukemia identified by 5T4 expression at diagnosis. Copyright© Ferrata Storti Foundation.

Targeting the 5T4 oncofetal glycoprotein with an antibody drug conjugate (A1mcMMAF) improves survival in patient-derived xenograft models of acute lymphoblastic leukemia

PubMed Central

McGinn, Owen J.; Krishnan, Shekhar; Bourquin, Jean-Pierre; Sapra, Puja; Dempsey, Clare; Saha, Vaskar; Stern, Peter L.

2017-01-01

Outcome in childhood acute lymphoblastic leukemia is prognosticated from levels of minimal residual disease after remission induction therapy. Higher levels of minimal residual disease are associated with inferior results even with intensification of therapy, thus suggesting that identification and targeting of minimal residual disease cells could be a therapeutic strategy. Here we identify high expression of 5T4 in subclonal populations of patient-derived xenografts from patients with high, post-induction levels of minimal residual disease. 5T4-positive cells showed preferential ability to overcome the NOD-scidIL2Rγnull mouse xenograft barrier, migrated in vitro on a CXCL12 gradient, preferentially localized to bone marrow in vivo and displayed the ability to reconstitute the original clonal composition on limited dilution engraftment. Treatment with A1mcMMAF (a 5T4-antibody drug conjugate) significantly improved survival without overt toxicity in mice engrafted with a 5T4-positive acute lymphoblastic leukemia cell line. Mice engrafted with 5T4-positive patient-derived xenograft cells were treated with combination chemotherapy or dexamethasone alone and then given A1mcMMAF in the minimal residual disease setting. Combination chemotherapy was toxic to NOD-scidIL2Rγnull mice. While dexamethasone or A1mcMMAF alone improved outcomes, the sequential administration of dexamethasone and A1mcMMAF significantly improved survival (P=0.0006) over either monotherapy. These data show that specifically targeting minimal residual disease cells improved outcomes and support further investigation of A1mcMMAF in patients with high-risk B-cell precursor acute lymphoblastic leukemia identified by 5T4 expression at diagnosis. PMID:28341731

ILUBCG2-11: Solution of 11-banded nonsymmetric linear equation systems by a preconditioned biconjugate gradient routine

NASA Astrophysics Data System (ADS)

Chen, Y.-M.; Koniges, A. E.; Anderson, D. V.

1989-10-01

The biconjugate gradient method (BCG) provides an attractive alternative to the usual conjugate gradient algorithms for the solution of sparse systems of linear equations with nonsymmetric and indefinite matrix operators. A preconditioned algorithm is given, whose form resembles the incomplete L-U conjugate gradient scheme (ILUCG2) previously presented. Although the BCG scheme requires the storage of two additional vectors, it converges in a significantly lesser number of iterations (often half), while the number of calculations per iteration remains essentially the same.

A different approach to estimate nonlinear regression model using numerical methods

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard [1] discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth [2]. Hans Georg Bock et.al [10] proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al [11], Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al [12].

Performance comparison of a new hybrid conjugate gradient method under exact and inexact line searches

NASA Astrophysics Data System (ADS)

Ghani, N. H. A.; Mohamed, N. S.; Zull, N.; Shoid, S.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is one of iterative techniques prominently used in solving unconstrained optimization problems due to its simplicity, low memory storage, and good convergence analysis. This paper presents a new hybrid conjugate gradient method, named NRM1 method. The method is analyzed under the exact and inexact line searches in given conditions. Theoretically, proofs show that the NRM1 method satisfies the sufficient descent condition with both line searches. The computational result indicates that NRM1 method is capable in solving the standard unconstrained optimization problems used. On the other hand, the NRM1 method performs better under inexact line search compared with exact line search.

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient

PubMed Central

Feng, Shuo

2014-01-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns. PMID:24834420

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2014-04-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

NASA Technical Reports Server (NTRS)

Seidel, R. C.

1975-01-01

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

Algorithms for parallel and vector computations

NASA Technical Reports Server (NTRS)

Ortega, James M.

1995-01-01

This is a final report on work performed under NASA grant NAG-1-1112-FOP during the period March, 1990 through February 1995. Four major topics are covered: (1) solution of nonlinear poisson-type equations; (2) parallel reduced system conjugate gradient method; (3) orderings for conjugate gradient preconditioners, and (4) SOR as a preconditioner.

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

PubMed

Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A

1999-12-01

A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.

Conjugate-Gradient Algorithms For Dynamics Of Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1993-01-01

Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.

An M-step preconditioned conjugate gradient method for parallel computation

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.

Conjugate gradient heat bath for ill-conditioned actions.

PubMed

Ceriotti, Michele; Bussi, Giovanni; Parrinello, Michele

2007-08-01

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

Objective analysis of pseudostress over the Indian Ocean using a direct-minimization approach

NASA Technical Reports Server (NTRS)

Legler, David M.; Navon, I. M.; O'Brien, James J.

1989-01-01

A technique not previously used in objective analysis of meteorological data is used here to produce monthly average surface pseudostress data over the Indian Ocean. An initial guess field is derived and a cost functional is constructed with five terms: approximation to initial guess, approximation to climatology, a smoothness parameter, and two kinematic terms. The functional is minimized using a conjugate-gradient technique, and the weight for the climatology term controls the overall balance of influence between the climatology and the initial guess. Results from various weight combinations are presented for January and July 1984. Quantitative and qualitative comparisons to the subject analysis are made to find which weight combination provides the best results. The weight on the approximation to climatology is found to balance the influence of the original field and climatology.

Frequency-domain beamformers using conjugate gradient techniques for speech enhancement.

PubMed

Zhao, Shengkui; Jones, Douglas L; Khoo, Suiyang; Man, Zhihong

2014-09-01

A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.

Moving force identification based on modified preconditioned conjugate gradient method

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Comparing implementations of penalized weighted least-squares sinogram restoration.

PubMed

Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick

2010-11-01

A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors' previous penalized-likelihood implementation. Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes.

Comparison of SIRT and SQS for Regularized Weighted Least Squares Image Reconstruction

PubMed Central

Gregor, Jens; Fessler, Jeffrey A.

2015-01-01

Tomographic image reconstruction is often formulated as a regularized weighted least squares (RWLS) problem optimized by iterative algorithms that are either inherently algebraic or derived from a statistical point of view. This paper compares a modified version of SIRT (Simultaneous Iterative Reconstruction Technique), which is of the former type, with a version of SQS (Separable Quadratic Surrogates), which is of the latter type. We show that the two algorithms minimize the same criterion function using similar forms of preconditioned gradient descent. We present near-optimal relaxation for both based on eigenvalue bounds and include a heuristic extension for use with ordered subsets. We provide empirical evidence that SIRT and SQS converge at the same rate for all intents and purposes. For context, we compare their performance with an implementation of preconditioned conjugate gradient. The illustrative application is X-ray CT of luggage for aviation security. PMID:26478906

Conjugate gradient based projection - A new explicit methodology for frictional contact

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; Li, Maocheng; Sha, Desong

1993-01-01

With special attention towards the applicability to parallel computation or vectorization, a new and effective explicit approach for linear complementary formulations involving a conjugate gradient based projection methodology is proposed in this study for contact problems with Coulomb friction. The overall objectives are focussed towards providing an explicit methodology of computation for the complete contact problem with friction. In this regard, the primary idea for solving the linear complementary formulations stems from an established search direction which is projected to a feasible region determined by the non-negative constraint condition; this direction is then applied to the Fletcher-Reeves conjugate gradient method resulting in a powerful explicit methodology which possesses high accuracy, excellent convergence characteristics, fast computational speed and is relatively simple to implement for contact problems involving Coulomb friction.

Deterministic and stochastic algorithms for resolving the flow fields in ducts and networks using energy minimization

NASA Astrophysics Data System (ADS)

Sochi, Taha

2016-09-01

Several deterministic and stochastic multi-variable global optimization algorithms (Conjugate Gradient, Nelder-Mead, Quasi-Newton and global) are investigated in conjunction with energy minimization principle to resolve the pressure and volumetric flow rate fields in single ducts and networks of interconnected ducts. The algorithms are tested with seven types of fluid: Newtonian, power law, Bingham, Herschel-Bulkley, Ellis, Ree-Eyring and Casson. The results obtained from all those algorithms for all these types of fluid agree very well with the analytically derived solutions as obtained from the traditional methods which are based on the conservation principles and fluid constitutive relations. The results confirm and generalize the findings of our previous investigations that the energy minimization principle is at the heart of the flow dynamics systems. The investigation also enriches the methods of computational fluid dynamics for solving the flow fields in tubes and networks for various types of Newtonian and non-Newtonian fluids.

Neural network diagnosis of avascular necrosis from magnetic resonance images

NASA Astrophysics Data System (ADS)

Manduca, Armando; Christy, Paul S.; Ehman, Richard L.

1993-09-01

We have explored the use of artificial neural networks to diagnose avascular necrosis (AVN) of the femoral head from magnetic resonance images. We have developed multi-layer perceptron networks, trained with conjugate gradient optimization, which diagnose AVN from single sagittal images of the femoral head with 100% accuracy on the training data and 97% accuracy on test data. These networks use only the raw image as input (with minimal preprocessing to average the images down to 32 X 32 size and to scale the input data values) and learn to extract their own features for the diagnosis decision. Various experiments with these networks are described.

M-step preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems of linear equations are described. Necessary and sufficient conditions are given for when these preconditioners can be used and an analysis of their effectiveness is given. Efficient computer implementations of these methods are discussed and results on the CYBER 203 and the Finite Element Machine under construction at NASA Langley Research Center are included.

Improving Maritime Domain Awareness Using Neural Networks for Target of Interest Classification

DTIC Science & Technology

2015-03-01

spreading SCG scaled conjugate gradient xv THIS PAGE INTENTIONALLY LEFT BLANK xvi EXECUTIVE SUMMARY The research detailed in this thesis is a...algorithms were explored for training the neural networks: resilient backpropagation (RP) and scaled conjugate gradient backpropagation ( SCG ). The...results of the neural network training performance are presented using mean squared error convergence plots. In all implementations, the SCG learning

Application of Conjugate Gradient methods to tidal simulation

USGS Publications Warehouse

Barragy, E.; Carey, G.F.; Walters, R.A.

1993-01-01

A harmonic decomposition technique is applied to the shallow water equations to yield a complex, nonsymmetric, nonlinear, Helmholtz type problem for the sea surface and an accompanying complex, nonlinear diagonal problem for the velocities. The equation for the sea surface is linearized using successive approximation and then discretized with linear, triangular finite elements. The study focuses on applying iterative methods to solve the resulting complex linear systems. The comparative evaluation includes both standard iterative methods for the real subsystems and complex versions of the well known Bi-Conjugate Gradient and Bi-Conjugate Gradient Squared methods. Several Incomplete LU type preconditioners are discussed, and the effects of node ordering, rejection strategy, domain geometry and Coriolis parameter (affecting asymmetry) are investigated. Implementation details for the complex case are discussed. Performance studies are presented and comparisons made with a frontal solver. ?? 1993.

On the electromagnetic scattering from infinite rectangular grids with finite conductivity

NASA Technical Reports Server (NTRS)

Christodoulou, C. G.; Kauffman, J. F.

1986-01-01

A variety of methods can be used in constructing solutions to the problem of mesh scattering. However, each of these methods has certain drawbacks. The present paper is concerned with a new technique which is valid for all spacings. The new method involved, called the fast Fourier transform-conjugate gradient method (FFT-CGM), represents an iterative technique which employs the conjugate gradient method to improve upon each iterate, utilizing the fast Fourier transform. The FFT-CGM method provides a new accurate model which can be extended and applied to the more difficult problems of woven mesh surfaces. The formulation of the FFT-conjugate gradient method for aperture fields and current densities for a planar periodic structure is considered along with singular operators, the formulation of the FFT-CG method for thin wires with finite conductivity, and reflection coefficients.

ONRASIA Scientific Information Bulletin. Volume 8, Number 3, July- September 1993

DTIC Science & Technology

1993-09-01

the Ninth Symposium on Preconditioned Conjugate Dr. Steven F. Ashby Gradient Methods , which he organized. Computing Sciences Department Computing...ditioned Conjugate Gradient Methods , held at Keio chines and is currently a topic of considerable University (Yokohama). During this meeting, I interest...in the United States. In Japan, on the other discussed iterative methods for linear systems with hand, this technique does not appear to be too well

The U.S. Geological Survey Modular Ground-Water Model - PCGN: A Preconditioned Conjugate Gradient Solver with Improved Nonlinear Control

USGS Publications Warehouse

Naff, Richard L.; Banta, Edward R.

2008-01-01

The preconditioned conjugate gradient with improved nonlinear control (PCGN) package provides addi-tional means by which the solution of nonlinear ground-water flow problems can be controlled as compared to existing solver packages for MODFLOW. Picard iteration is used to solve nonlinear ground-water flow equations by iteratively solving a linear approximation of the nonlinear equations. The linear solution is provided by means of the preconditioned conjugate gradient algorithm where preconditioning is provided by the modi-fied incomplete Cholesky algorithm. The incomplete Cholesky scheme incorporates two levels of fill, 0 and 1, in which the pivots can be modified so that the row sums of the preconditioning matrix and the original matrix are approximately equal. A relaxation factor is used to implement the modified pivots, which determines the degree of modification allowed. The effects of fill level and degree of pivot modification are briefly explored by means of a synthetic, heterogeneous finite-difference matrix; results are reported in the final section of this report. The preconditioned conjugate gradient method is coupled with Picard iteration so as to efficiently solve the nonlinear equations associated with many ground-water flow problems. The description of this coupling of the linear solver with Picard iteration is a primary concern of this document.

Parallel processors and nonlinear structural dynamics algorithms and software

NASA Technical Reports Server (NTRS)

Belytschko, Ted

1990-01-01

Techniques are discussed for the implementation and improvement of vectorization and concurrency in nonlinear explicit structural finite element codes. In explicit integration methods, the computation of the element internal force vector consumes the bulk of the computer time. The program can be efficiently vectorized by subdividing the elements into blocks and executing all computations in vector mode. The structuring of elements into blocks also provides a convenient way to implement concurrency by creating tasks which can be assigned to available processors for evaluation. The techniques were implemented in a 3-D nonlinear program with one-point quadrature shell elements. Concurrency and vectorization were first implemented in a single time step version of the program. Techniques were developed to minimize processor idle time and to select the optimal vector length. A comparison of run times between the program executed in scalar, serial mode and the fully vectorized code executed concurrently using eight processors shows speed-ups of over 25. Conjugate gradient methods for solving nonlinear algebraic equations are also readily adapted to a parallel environment. A new technique for improving convergence properties of conjugate gradients in nonlinear problems is developed in conjunction with other techniques such as diagonal scaling. A significant reduction in the number of iterations required for convergence is shown for a statically loaded rigid bar suspended by three equally spaced springs.

A family of conjugate gradient methods for large-scale nonlinear equations.

PubMed

Feng, Dexiang; Sun, Min; Wang, Xueyong

2017-01-01

In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.

High-performance conjugate-gradient benchmark: A new metric for ranking high-performance computing systems

DOE PAGES

Dongarra, Jack; Heroux, Michael A.; Luszczek, Piotr

2015-08-17

Here, we describe a new high-performance conjugate-gradient (HPCG) benchmark. HPCG is composed of computations and data-access patterns commonly found in scientific applications. HPCG strives for a better correlation to existing codes from the computational science domain and to be representative of their performance. Furthermore, HPCG is meant to help drive the computer system design and implementation in directions that will better impact future performance improvement.

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

USGS Publications Warehouse

Hill, Mary C.

1990-01-01

This report documents PCG2 : a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model . PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options : modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers . Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.

Unusual Domain Structure and Filamentary Superfluidity for 2D Hard-Core Bosons in Insulating Charge-Ordered Phase

NASA Astrophysics Data System (ADS)

Panov, Yu. D.; Moskvin, A. S.; Rybakov, F. N.; Borisov, A. B.

2016-12-01

We made use of a special algorithm for compute unified device architecture for NVIDIA graphics cards, a nonlinear conjugate-gradient method to minimize energy functional, and Monte-Carlo technique to directly observe the forming of the ground state configuration for the 2D hard-core bosons by lowering the temperature and its evolution with deviation away from half-filling. The novel technique allowed us to examine earlier implications and uncover novel features of the phase transitions, in particular, look upon the nucleation of the odd domain structure, emergence of filamentary superfluidity nucleated at the antiphase domain walls of the charge-ordered phase, and nucleation and evolution of different topological structures.

Comparing implementations of penalized weighted least-squares sinogram restoration

PubMed Central

Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick

2010-01-01

Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. Results: All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors’ previous penalized-likelihood implementation. Conclusions: Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes. PMID:21158306

Analysis and diagnosis of basal cell carcinoma (BCC) via infrared imaging

NASA Astrophysics Data System (ADS)

Flores-Sahagun, J. H.; Vargas, J. V. C.; Mulinari-Brenner, F. A.

2011-09-01

In this work, a structured methodology is proposed and tested through infrared imaging temperature measurements of a healthy control group to establish expected normality ranges and of basal cell carcinoma patients (a type of skin cancer) previously diagnosed through biopsies of the affected regions. A method of conjugated gradients is proposed to compare measured dimensionless temperature difference values (Δ θ) between two symmetric regions of the patient's body, that takes into account the skin, the surrounding ambient and the individual core temperatures and doing so, the limitation of the results interpretation for different individuals become simple and nonsubjective. The range of normal temperatures in different regions of the body for seven healthy individuals was determined, and admitting that the human skin exhibits a unimodal normal distribution, the normal range for each region was considered to be the mean dimensionless temperature difference plus/minus twice the standard deviation of the measurements (Δθ±2σ) in order to represent 95% of the population. Eleven patients with previously diagnosed basal cell carcinoma through biopsies were examined with the method, which was capable of detecting skin abnormalities in all cases. Therefore, the conjugated gradients method was considered effective in the identification of the basal cell carcinoma through infrared imaging even with the use of a low optical resolution camera (160 × 120 pixels) and a thermal resolution of 0.1 °C. The method could also be used to scan a larger area around the lesion in order to detect the presence of other lesions still not perceptible in the clinical exam. However, it is necessary that a temperature differences mesh-like mapping of the healthy human body skin is produced, so that the comparison of the patient Δ θ could be made with the exact region of such mapping in order to possibly make a more effective diagnosis. Finally, the infrared image analyzed through the conjugated gradients method could be useful in the definition of a better safety margin in the surgery for the removal of the lesion, both minimizing esthetics damage to the patient and possibly avoiding basal cell carcinoma recurrence.

Experimental study of stochastic noise propagation in SPECT images reconstructed using the conjugate gradient algorithm.

PubMed

Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M

2003-01-01

Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.

Conjugate gradient optimization programs for shuttle reentry

NASA Technical Reports Server (NTRS)

Powers, W. F.; Jacobson, R. A.; Leonard, D. A.

1972-01-01

Two computer programs for shuttle reentry trajectory optimization are listed and described. Both programs use the conjugate gradient method as the optimization procedure. The Phase 1 Program is developed in cartesian coordinates for a rotating spherical earth, and crossrange, downrange, maximum deceleration, total heating, and terminal speed, altitude, and flight path angle are included in the performance index. The programs make extensive use of subroutines so that they may be easily adapted to other atmospheric trajectory optimization problems.

A new family of Polak-Ribiere-Polyak conjugate gradient method with the strong-Wolfe line search

NASA Astrophysics Data System (ADS)

Ghani, Nur Hamizah Abdul; Mamat, Mustafa; Rivaie, Mohd

2017-08-01

Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods.

Hessian-based norm regularization for image restoration with biomedical applications.

PubMed

Lefkimmiatis, Stamatios; Bourquard, Aurélien; Unser, Michael

2012-03-01

We present nonquadratic Hessian-based regularization methods that can be effectively used for image restoration problems in a variational framework. Motivated by the great success of the total-variation (TV) functional, we extend it to also include second-order differential operators. Specifically, we derive second-order regularizers that involve matrix norms of the Hessian operator. The definition of these functionals is based on an alternative interpretation of TV that relies on mixed norms of directional derivatives. We show that the resulting regularizers retain some of the most favorable properties of TV, i.e., convexity, homogeneity, rotation, and translation invariance, while dealing effectively with the staircase effect. We further develop an efficient minimization scheme for the corresponding objective functions. The proposed algorithm is of the iteratively reweighted least-square type and results from a majorization-minimization approach. It relies on a problem-specific preconditioned conjugate gradient method, which makes the overall minimization scheme very attractive since it can be applied effectively to large images in a reasonable computational time. We validate the overall proposed regularization framework through deblurring experiments under additive Gaussian noise on standard and biomedical images.

Reconstruction of electrical impedance tomography (EIT) images based on the expectation maximum (EM) method.

PubMed

Wang, Qi; Wang, Huaxiang; Cui, Ziqiang; Yang, Chengyi

2012-11-01

Electrical impedance tomography (EIT) calculates the internal conductivity distribution within a body using electrical contact measurements. The image reconstruction for EIT is an inverse problem, which is both non-linear and ill-posed. The traditional regularization method cannot avoid introducing negative values in the solution. The negativity of the solution produces artifacts in reconstructed images in presence of noise. A statistical method, namely, the expectation maximization (EM) method, is used to solve the inverse problem for EIT in this paper. The mathematical model of EIT is transformed to the non-negatively constrained likelihood minimization problem. The solution is obtained by the gradient projection-reduced Newton (GPRN) iteration method. This paper also discusses the strategies of choosing parameters. Simulation and experimental results indicate that the reconstructed images with higher quality can be obtained by the EM method, compared with the traditional Tikhonov and conjugate gradient (CG) methods, even with non-negative processing. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Speed and convergence properties of gradient algorithms for optimization of IMRT.

PubMed

Zhang, Xiaodong; Liu, Helen; Wang, Xiaochun; Dong, Lei; Wu, Qiuwen; Mohan, Radhe

2004-05-01

Gradient algorithms are the most commonly employed search methods in the routine optimization of IMRT plans. It is well known that local minima can exist for dose-volume-based and biology-based objective functions. The purpose of this paper is to compare the relative speed of different gradient algorithms, to investigate the strategies for accelerating the optimization process, to assess the validity of these strategies, and to study the convergence properties of these algorithms for dose-volume and biological objective functions. With these aims in mind, we implemented Newton's, conjugate gradient (CG), and the steepest decent (SD) algorithms for dose-volume- and EUD-based objective functions. Our implementation of Newton's algorithm approximates the second derivative matrix (Hessian) by its diagonal. The standard SD algorithm and the CG algorithm with "line minimization" were also implemented. In addition, we investigated the use of a variation of the CG algorithm, called the "scaled conjugate gradient" (SCG) algorithm. To accelerate the optimization process, we investigated the validity of the use of a "hybrid optimization" strategy, in which approximations to calculated dose distributions are used during most of the iterations. Published studies have indicated that getting trapped in local minima is not a significant problem. To investigate this issue further, we first obtained, by trial and error, and starting with uniform intensity distributions, the parameters of the dose-volume- or EUD-based objective functions which produced IMRT plans that satisfied the clinical requirements. Using the resulting optimized intensity distributions as the initial guess, we investigated the possibility of getting trapped in a local minimum. For most of the results presented, we used a lung cancer case. To illustrate the generality of our methods, the results for a prostate case are also presented. For both dose-volume and EUD based objective functions, Newton's method far outperforms other algorithms in terms of speed. The SCG algorithm, which avoids expensive "line minimization," can speed up the standard CG algorithm by at least a factor of 2. For the same initial conditions, all algorithms converge essentially to the same plan. However, we demonstrate that for any of the algorithms studied, starting with previously optimized intensity distributions as the initial guess but for different objective function parameters, the solution frequently gets trapped in local minima. We found that the initial intensity distribution obtained from IMRT optimization utilizing objective function parameters, which favor a specific anatomic structure, would lead to a local minimum corresponding to that structure. Our results indicate that from among the gradient algorithms tested, Newton's method appears to be the fastest by far. Different gradient algorithms have the same convergence properties for dose-volume- and EUD-based objective functions. The hybrid dose calculation strategy is valid and can significantly accelerate the optimization process. The degree of acceleration achieved depends on the type of optimization problem being addressed (e.g., IMRT optimization, intensity modulated beam configuration optimization, or objective function parameter optimization). Under special conditions, gradient algorithms will get trapped in local minima, and reoptimization, starting with the results of previous optimization, will lead to solutions that are generally not significantly different from the local minimum.

Conjugate gradient method for phase retrieval based on the Wirtinger derivative.

PubMed

Wei, Zhun; Chen, Wen; Qiu, Cheng-Wei; Chen, Xudong

2017-05-01

A conjugate gradient Wirtinger flow (CG-WF) algorithm for phase retrieval is proposed in this paper. It is shown that, compared with recently reported Wirtinger flow and its modified methods, the proposed CG-WF algorithm is able to dramatically accelerate the convergence rate while keeping the dominant computational cost of each iteration unchanged. We numerically illustrate the effectiveness of our method in recovering 1D Gaussian signals and 2D natural color images under both Gaussian and coded diffraction pattern models.

Reconstruction for limited-projection fluorescence molecular tomography based on projected restarted conjugate gradient normal residual.

PubMed

Cao, Xu; Zhang, Bin; Liu, Fei; Wang, Xin; Bai, Jing

2011-12-01

Limited-projection fluorescence molecular tomography (FMT) can greatly reduce the acquisition time, which is suitable for resolving fast biology processes in vivo but suffers from severe ill-posedness because of the reconstruction using only limited projections. To overcome the severe ill-posedness, we report a reconstruction method based on the projected restarted conjugate gradient normal residual. The reconstruction results of two phantom experiments demonstrate that the proposed method is feasible for limited-projection FMT. © 2011 Optical Society of America

Steepest descent with momentum for quadratic functions is a version of the conjugate gradient method.

PubMed

Bhaya, Amit; Kaszkurewicz, Eugenius

2004-01-01

It is pointed out that the so called momentum method, much used in the neural network literature as an acceleration of the backpropagation method, is a stationary version of the conjugate gradient method. Connections with the continuous optimization method known as heavy ball with friction are also made. In both cases, adaptive (dynamic) choices of the so called learning rate and momentum parameters are obtained using a control Liapunov function analysis of the system.

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.

Validation of Left Ventricular Ejection Fraction with the IQ•SPECT System in Small-Heart Patients.

PubMed

Yoneyama, Hiroto; Shibutani, Takayuki; Konishi, Takahiro; Mizutani, Asuka; Hashimoto, Ryosuke; Onoguchi, Masahisa; Okuda, Koichi; Matsuo, Shinro; Nakajima, Kenichi; Kinuya, Seigo

2017-09-01

The IQ•SPECT system, which is equipped with multifocal collimators ( SMART ZOOM) and uses ordered-subset conjugate gradient minimization as the reconstruction algorithm, reduces the acquisition time of myocardial perfusion imaging compared with conventional SPECT systems equipped with low-energy high-resolution collimators. We compared the IQ•SPECT system with a conventional SPECT system for estimating left ventricular ejection fraction (LVEF) in patients with a small heart (end-systolic volume < 20 mL). Methods: The study consisted of 98 consecutive patients who underwent a 1-d stress-rest myocardial perfusion imaging study with a 99m Tc-labeled agent for preoperative risk assessment. Data were reconstructed using filtered backprojection for conventional SPECT and ordered-subset conjugate gradient minimization for IQ•SPECT. End-systolic volume, end-diastolic volume, and LVEF were calculated using quantitative gated SPECT (QGS) and cardioREPO software. We compared the LVEF from gated myocardial perfusion SPECT to that from echocardiographic measurements. Results: End-diastolic volume, end-systolic volume, and LVEF as obtained from conventional SPECT, IQ•SPECT, and echocardiography showed a good to excellent correlation regardless of whether they were calculated using QGS or using cardioREPO. Although LVEF calculated using QGS significantly differed between conventional SPECT and IQ•SPECT (65.4% ± 13.8% vs. 68.4% ± 15.2%) ( P = 0.0002), LVEF calculated using cardioREPO did not (69.5% ± 10.6% vs. 69.5% ± 11.0%). Likewise, although LVEF calculated using QGS significantly differed between conventional SPECT and IQ•SPECT (75.0 ± 9.6 vs. 79.5 ± 8.3) ( P = 0.0005), LVEF calculated using cardioREPO did not (72.3% ± 9.0% vs. 74.3% ± 8.3%). Conclusion: In small-heart patients, the difference in LVEF between IQ•SPECT and conventional SPECT was less when calculated using cardioREPO than when calculated using QGS. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

A Block Preconditioned Conjugate Gradient-type Iterative Solver for Linear Systems in Thermal Reservoir Simulation

NASA Astrophysics Data System (ADS)

Betté, Srinivas; Diaz, Julio C.; Jines, William R.; Steihaug, Trond

1986-11-01

A preconditioned residual-norm-reducing iterative solver is described. Based on a truncated form of the generalized-conjugate-gradient method for nonsymmetric systems of linear equations, the iterative scheme is very effective for linear systems generated in reservoir simulation of thermal oil recovery processes. As a consequence of employing an adaptive implicit finite-difference scheme to solve the model equations, the number of variables per cell-block varies dynamically over the grid. The data structure allows for 5- and 9-point operators in the areal model, 5-point in the cross-sectional model, and 7- and 11-point operators in the three-dimensional model. Block-diagonal-scaling of the linear system, done prior to iteration, is found to have a significant effect on the rate of convergence. Block-incomplete-LU-decomposition (BILU) and block-symmetric-Gauss-Seidel (BSGS) methods, which result in no fill-in, are used as preconditioning procedures. A full factorization is done on the well terms, and the cells are ordered in a manner which minimizes the fill-in in the well-column due to this factorization. The convergence criterion for the linear (inner) iteration is linked to that of the nonlinear (Newton) iteration, thereby enhancing the efficiency of the computation. The algorithm, with both BILU and BSGS preconditioners, is evaluated in the context of a variety of thermal simulation problems. The solver is robust and can be used with little or no user intervention.

The multigrid preconditioned conjugate gradient method

NASA Technical Reports Server (NTRS)

Tatebe, Osamu

1993-01-01

A multigrid preconditioned conjugate gradient method (MGCG method), which uses the multigrid method as a preconditioner of the PCG method, is proposed. The multigrid method has inherent high parallelism and improves convergence of long wavelength components, which is important in iterative methods. By using this method as a preconditioner of the PCG method, an efficient method with high parallelism and fast convergence is obtained. First, it is considered a necessary condition of the multigrid preconditioner in order to satisfy requirements of a preconditioner of the PCG method. Next numerical experiments show a behavior of the MGCG method and that the MGCG method is superior to both the ICCG method and the multigrid method in point of fast convergence and high parallelism. This fast convergence is understood in terms of the eigenvalue analysis of the preconditioned matrix. From this observation of the multigrid preconditioner, it is realized that the MGCG method converges in very few iterations and the multigrid preconditioner is a desirable preconditioner of the conjugate gradient method.

GPU computing with Kaczmarz’s and other iterative algorithms for linear systems

PubMed Central

Elble, Joseph M.; Sahinidis, Nikolaos V.; Vouzis, Panagiotis

2009-01-01

The graphics processing unit (GPU) is used to solve large linear systems derived from partial differential equations. The differential equations studied are strongly convection-dominated, of various sizes, and common to many fields, including computational fluid dynamics, heat transfer, and structural mechanics. The paper presents comparisons between GPU and CPU implementations of several well-known iterative methods, including Kaczmarz’s, Cimmino’s, component averaging, conjugate gradient normal residual (CGNR), symmetric successive overrelaxation-preconditioned conjugate gradient, and conjugate-gradient-accelerated component-averaged row projections (CARP-CG). Computations are preformed with dense as well as general banded systems. The results demonstrate that our GPU implementation outperforms CPU implementations of these algorithms, as well as previously studied parallel implementations on Linux clusters and shared memory systems. While the CGNR method had begun to fall out of favor for solving such problems, for the problems studied in this paper, the CGNR method implemented on the GPU performed better than the other methods, including a cluster implementation of the CARP-CG method. PMID:20526446

Optimization of non-linear gradient in hydrophobic interaction chromatography for the analytical characterization of antibody-drug conjugates.

PubMed

Bobály, Balázs; Randazzo, Giuseppe Marco; Rudaz, Serge; Guillarme, Davy; Fekete, Szabolcs

2017-01-20

The goal of this work was to evaluate the potential of non-linear gradients in hydrophobic interaction chromatography (HIC), to improve the separation between the different homologous species (drug-to-antibody, DAR) of commercial antibody-drug conjugates (ADC). The selectivities between Brentuximab Vedotin species were measured using three different gradient profiles, namely linear, power function based and logarithmic ones. The logarithmic gradient provides the most equidistant retention distribution for the DAR species and offers the best overall separation of cysteine linked ADC in HIC. Another important advantage of the logarithmic gradient, is its peak focusing effect for the DAR0 species, which is particularly useful to improve the quantitation limit of DAR0. Finally, the logarithmic behavior of DAR species of ADC in HIC was modelled using two different approaches, based on i) the linear solvent strength theory (LSS) and two scouting linear gradients and ii) a new derived equation and two logarithmic scouting gradients. In both cases, the retention predictions were excellent and systematically below 3% compared to the experimental values. Copyright © 2016 Elsevier B.V. All rights reserved.

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Iterative and multigrid methods in the finite element solution of incompressible and turbulent fluid flow

NASA Astrophysics Data System (ADS)

Lavery, N.; Taylor, C.

1999-07-01

Multigrid and iterative methods are used to reduce the solution time of the matrix equations which arise from the finite element (FE) discretisation of the time-independent equations of motion of the incompressible fluid in turbulent motion. Incompressible flow is solved by using the method of reduce interpolation for the pressure to satisfy the Brezzi-Babuska condition. The k-l model is used to complete the turbulence closure problem. The non-symmetric iterative matrix methods examined are the methods of least squares conjugate gradient (LSCG), biconjugate gradient (BCG), conjugate gradient squared (CGS), and the biconjugate gradient squared stabilised (BCGSTAB). The multigrid algorithm applied is based on the FAS algorithm of Brandt, and uses two and three levels of grids with a V-cycling schedule. These methods are all compared to the non-symmetric frontal solver. Copyright

Two-dimensional frequency-domain acoustic full-waveform inversion with rugged topography

NASA Astrophysics Data System (ADS)

Zhang, Qian-Jiang; Dai, Shi-Kun; Chen, Long-Wei; Li, Kun; Zhao, Dong-Dong; Huang, Xing-Xing

2015-09-01

We studied finite-element-method-based two-dimensional frequency-domain acoustic FWI under rugged topography conditions. The exponential attenuation boundary condition suitable for rugged topography is proposed to solve the cutoff boundary problem as well as to consider the requirement of using the same subdivision grid in joint multifrequency inversion. The proposed method introduces the attenuation factor, and by adjusting it, acoustic waves are sufficiently attenuated in the attenuation layer to minimize the cutoff boundary effect. Based on the law of exponential attenuation, expressions for computing the attenuation factor and the thickness of attenuation layers are derived for different frequencies. In multifrequency-domain FWI, the conjugate gradient method is used to solve equations in the Gauss-Newton algorithm and thus minimize the computation cost in calculating the Hessian matrix. In addition, the effect of initial model selection and frequency combination on FWI is analyzed. Examples using numerical simulations and FWI calculations are used to verify the efficiency of the proposed method.

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

Suryanarayana, Phanish, E-mail: phanish.suryanarayana@ce.gatech.edu; Phanish, Deepa

We present an Augmented Lagrangian formulation and its real-space implementation for non-periodic Orbital-Free Density Functional Theory (OF-DFT) calculations. In particular, we rewrite the constrained minimization problem of OF-DFT as a sequence of minimization problems without any constraint, thereby making it amenable to powerful unconstrained optimization algorithms. Further, we develop a parallel implementation of this approach for the Thomas–Fermi–von Weizsacker (TFW) kinetic energy functional in the framework of higher-order finite-differences and the conjugate gradient method. With this implementation, we establish that the Augmented Lagrangian approach is highly competitive compared to the penalty and Lagrange multiplier methods. Additionally, we show that higher-ordermore » finite-differences represent a computationally efficient discretization for performing OF-DFT simulations. Overall, we demonstrate that the proposed formulation and implementation are both efficient and robust by studying selected examples, including systems consisting of thousands of atoms. We validate the accuracy of the computed energies and forces by comparing them with those obtained by existing plane-wave methods.« less

Finite elements and the method of conjugate gradients on a concurrent processor

NASA Technical Reports Server (NTRS)

Lyzenga, G. A.; Raefsky, A.; Hager, G. H.

1985-01-01

An algorithm for the iterative solution of finite element problems on a concurrent processor is presented. The method of conjugate gradients is used to solve the system of matrix equations, which is distributed among the processors of a MIMD computer according to an element-based spatial decomposition. This algorithm is implemented in a two-dimensional elastostatics program on the Caltech Hypercube concurrent processor. The results of tests on up to 32 processors show nearly linear concurrent speedup, with efficiencies over 90 percent for sufficiently large problems.

Hybrid DFP-CG method for solving unconstrained optimization problems

NASA Astrophysics Data System (ADS)

Osman, Wan Farah Hanan Wan; Asrul Hery Ibrahim, Mohd; Mamat, Mustafa

2017-09-01

The conjugate gradient (CG) method and quasi-Newton method are both well known method for solving unconstrained optimization method. In this paper, we proposed a new method by combining the search direction between conjugate gradient method and quasi-Newton method based on BFGS-CG method developed by Ibrahim et al. The Davidon-Fletcher-Powell (DFP) update formula is used as an approximation of Hessian for this new hybrid algorithm. Numerical result showed that the new algorithm perform well than the ordinary DFP method and proven to posses both sufficient descent and global convergence properties.

Finite elements and the method of conjugate gradients on a concurrent processor

NASA Technical Reports Server (NTRS)

Lyzenga, G. A.; Raefsky, A.; Hager, B. H.

1984-01-01

An algorithm for the iterative solution of finite element problems on a concurrent processor is presented. The method of conjugate gradients is used to solve the system of matrix equations, which is distributed among the processors of a MIMD computer according to an element-based spatial decomposition. This algorithm is implemented in a two-dimensional elastostatics program on the Caltech Hypercube concurrent processor. The results of tests on up to 32 processors show nearly linear concurrent speedup, with efficiencies over 90% for sufficiently large problems.

Geometrical optics analysis of the structural imperfection of retroreflection corner cubes with a nonlinear conjugate gradient method.

PubMed

Kim, Hwi; Min, Sung-Wook; Lee, Byoungho

2008-12-01

Geometrical optics analysis of the structural imperfection of retroreflection corner cubes is described. In the analysis, a geometrical optics model of six-beam reflection patterns generated by an imperfect retroreflection corner cube is developed, and its structural error extraction is formulated as a nonlinear optimization problem. The nonlinear conjugate gradient method is employed for solving the nonlinear optimization problem, and its detailed implementation is described. The proposed method of analysis is a mathematical basis for the nondestructive optical inspection of imperfectly fabricated retroreflection corner cubes.

Projection methods for line radiative transfer in spherical media.

NASA Astrophysics Data System (ADS)

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

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

Optimization of neural network architecture for classification of radar jamming FM signals

NASA Astrophysics Data System (ADS)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

The truncated conjugate gradient (TCG), a non-iterative/fixed-cost strategy for computing polarization in molecular dynamics: Fast evaluation of analytical forces

NASA Astrophysics Data System (ADS)

Aviat, Félix; Lagardère, Louis; Piquemal, Jean-Philip

2017-10-01

In a recent paper [F. Aviat et al., J. Chem. Theory Comput. 13, 180-190 (2017)], we proposed the Truncated Conjugate Gradient (TCG) approach to compute the polarization energy and forces in polarizable molecular simulations. The method consists in truncating the conjugate gradient algorithm at a fixed predetermined order leading to a fixed computational cost and can thus be considered "non-iterative." This gives the possibility to derive analytical forces avoiding the usual energy conservation (i.e., drifts) issues occurring with iterative approaches. A key point concerns the evaluation of the analytical gradients, which is more complex than that with a usual solver. In this paper, after reviewing the present state of the art of polarization solvers, we detail a viable strategy for the efficient implementation of the TCG calculation. The complete cost of the approach is then measured as it is tested using a multi-time step scheme and compared to timings using usual iterative approaches. We show that the TCG methods are more efficient than traditional techniques, making it a method of choice for future long molecular dynamics simulations using polarizable force fields where energy conservation matters. We detail the various steps required for the implementation of the complete method by software developers.

The truncated conjugate gradient (TCG), a non-iterative/fixed-cost strategy for computing polarization in molecular dynamics: Fast evaluation of analytical forces.

PubMed

Aviat, Félix; Lagardère, Louis; Piquemal, Jean-Philip

2017-10-28

In a recent paper [F. Aviat et al., J. Chem. Theory Comput. 13, 180-190 (2017)], we proposed the Truncated Conjugate Gradient (TCG) approach to compute the polarization energy and forces in polarizable molecular simulations. The method consists in truncating the conjugate gradient algorithm at a fixed predetermined order leading to a fixed computational cost and can thus be considered "non-iterative." This gives the possibility to derive analytical forces avoiding the usual energy conservation (i.e., drifts) issues occurring with iterative approaches. A key point concerns the evaluation of the analytical gradients, which is more complex than that with a usual solver. In this paper, after reviewing the present state of the art of polarization solvers, we detail a viable strategy for the efficient implementation of the TCG calculation. The complete cost of the approach is then measured as it is tested using a multi-time step scheme and compared to timings using usual iterative approaches. We show that the TCG methods are more efficient than traditional techniques, making it a method of choice for future long molecular dynamics simulations using polarizable force fields where energy conservation matters. We detail the various steps required for the implementation of the complete method by software developers.

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

DOE PAGES

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

2015-02-25

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

Nonlinear transient analysis by energy minimization: A theoretical basis for the ACTION computer code. [predicting the response of a lightweight aircraft during a crash

NASA Technical Reports Server (NTRS)

Kamat, M. P.

1980-01-01

The formulation basis for establishing the static or dynamic equilibrium configurations of finite element models of structures which may behave in the nonlinear range are provided. With both geometric and time independent material nonlinearities included, the development is restricted to simple one and two dimensional finite elements which are regarded as being the basic elements for modeling full aircraft-like structures under crash conditions. Representations of a rigid link and an impenetrable contact plane are added to the deformation model so that any number of nodes of the finite element model may be connected by a rigid link or may contact the plane. Equilibrium configurations are derived as the stationary conditions of a potential function of the generalized nodal variables of the model. Minimization of the nonlinear potential function is achieved by using the best current variable metric update formula for use in unconstrained minimization. Powell's conjugate gradient algorithm, which offers very low storage requirements at some slight increase in the total number of calculations, is the other alternative algorithm to be used for extremely large scale problems.

Conjugate gradient coupled with multigrid for an indefinite problem

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

PubMed

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

A fast pulse design for parallel excitation with gridding conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2013-01-01

Parallel excitation (pTx) is recognized as a crucial technique in high field MRI to address the transmit field inhomogeneity problem. However, it can be time consuming to design pTx pulses which is not desirable. In this work, we propose a pulse design with gridding conjugate gradient (CG) based on the small-tip-angle approximation. The two major time consuming matrix-vector multiplications are substituted by two operators which involves with FFT and gridding only. Simulation results have shown that the proposed method is 3 times faster than conventional method and the memory cost is reduced by 1000 times.

A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization

PubMed Central

Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang

2015-01-01

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence—with at most a linear convergence rate—because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method. PMID:26381742

A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization.

PubMed

Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang

2015-01-01

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.

Constraint treatment techniques and parallel algorithms for multibody dynamic analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chiou, Jin-Chern

1990-01-01

Computational procedures for kinematic and dynamic analysis of three-dimensional multibody dynamic (MBD) systems are developed from the differential-algebraic equations (DAE's) viewpoint. Constraint violations during the time integration process are minimized and penalty constraint stabilization techniques and partitioning schemes are developed. The governing equations of motion, a two-stage staggered explicit-implicit numerical algorithm, are treated which takes advantage of a partitioned solution procedure. A robust and parallelizable integration algorithm is developed. This algorithm uses a two-stage staggered central difference algorithm to integrate the translational coordinates and the angular velocities. The angular orientations of bodies in MBD systems are then obtained by using an implicit algorithm via the kinematic relationship between Euler parameters and angular velocities. It is shown that the combination of the present solution procedures yields a computationally more accurate solution. To speed up the computational procedures, parallel implementation of the present constraint treatment techniques, the two-stage staggered explicit-implicit numerical algorithm was efficiently carried out. The DAE's and the constraint treatment techniques were transformed into arrowhead matrices to which Schur complement form was derived. By fully exploiting the sparse matrix structural analysis techniques, a parallel preconditioned conjugate gradient numerical algorithm is used to solve the systems equations written in Schur complement form. A software testbed was designed and implemented in both sequential and parallel computers. This testbed was used to demonstrate the robustness and efficiency of the constraint treatment techniques, the accuracy of the two-stage staggered explicit-implicit numerical algorithm, and the speed up of the Schur-complement-based parallel preconditioned conjugate gradient algorithm on a parallel computer.

Multisource least-squares reverse-time migration with structure-oriented filtering

NASA Astrophysics Data System (ADS)

Fan, Jing-Wen; Li, Zhen-Chun; Zhang, Kai; Zhang, Min; Liu, Xue-Tong

2016-09-01

The technology of simultaneous-source acquisition of seismic data excited by several sources can significantly improve the data collection efficiency. However, direct imaging of simultaneous-source data or blended data may introduce crosstalk noise and affect the imaging quality. To address this problem, we introduce a structure-oriented filtering operator as preconditioner into the multisource least-squares reverse-time migration (LSRTM). The structure-oriented filtering operator is a nonstationary filter along structural trends that suppresses crosstalk noise while maintaining structural information. The proposed method uses the conjugate-gradient method to minimize the mismatch between predicted and observed data, while effectively attenuating the interference noise caused by exciting several sources simultaneously. Numerical experiments using synthetic data suggest that the proposed method can suppress the crosstalk noise and produce highly accurate images.

Fractional-order TV-L2 model for image denoising

NASA Astrophysics Data System (ADS)

Chen, Dali; Sun, Shenshen; Zhang, Congrong; Chen, YangQuan; Xue, Dingyu

2013-10-01

This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

History matching by spline approximation and regularization in single-phase areal reservoirs

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kravaris, C.; Seinfeld, J.

1986-01-01

An automatic history matching algorithm is developed based on bi-cubic spline approximations of permeability and porosity distributions and on the theory of regularization to estimate permeability or porosity in a single-phase, two-dimensional real reservoir from well pressure data. The regularization feature of the algorithm is used to convert the ill-posed history matching problem into a well-posed problem. The algorithm employs the conjugate gradient method as its core minimization method. A number of numerical experiments are carried out to evaluate the performance of the algorithm. Comparisons with conventional (non-regularized) automatic history matching algorithms indicate the superiority of the new algorithm with respect to the parameter estimates obtained. A quasioptimal regularization parameter is determined without requiring a priori information on the statistical properties of the observations.

Radiofrequency pulse design using nonlinear gradient magnetic fields.

PubMed

Kopanoglu, Emre; Constable, R Todd

2015-09-01

An iterative k-space trajectory and radiofrequency (RF) pulse design method is proposed for excitation using nonlinear gradient magnetic fields. The spatial encoding functions (SEFs) generated by nonlinear gradient fields are linearly dependent in Cartesian coordinates. Left uncorrected, this may lead to flip angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a matching pursuit algorithm, and the RF pulse is designed using a conjugate gradient algorithm. Three variants of the proposed approach are given: the full algorithm, a computationally cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. The method is compared with other iterative (matching pursuit and conjugate gradient) and noniterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity. An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. © 2014 Wiley Periodicals, Inc.

A look-ahead variant of the Lanczos algorithm and its application to the quasi-minimal residual method for non-Hermitian linear systems. Ph.D. Thesis - Massachusetts Inst. of Technology, Aug. 1991

NASA Technical Reports Server (NTRS)

Nachtigal, Noel M.

1991-01-01

The Lanczos algorithm can be used both for eigenvalue problems and to solve linear systems. However, when applied to non-Hermitian matrices, the classical Lanczos algorithm is susceptible to breakdowns and potential instabilities. In addition, the biconjugate gradient (BCG) algorithm, which is the natural generalization of the conjugate gradient algorithm to non-Hermitian linear systems, has a second source of breakdowns, independent of the Lanczos breakdowns. Here, we present two new results. We propose an implementation of a look-ahead variant of the Lanczos algorithm which overcomes the breakdowns by skipping over those steps where a breakdown or a near-breakdown would occur. The new algorithm can handle look-ahead steps of any length and requires the same number of matrix-vector products and inner products per step as the classical Lanczos algorithm without look-ahead. Based on the proposed look-ahead Lanczos algorithm, we then present a novel BCG-like approach, the quasi-minimal residual (QMR) method, which avoids the second source of breakdowns in the BCG algorithm. We present details of the new method and discuss some of its properties. In particular, we discuss the relationship between QMR and BCG, showing how one can recover the BCG iterates, when they exist, from the QMR iterates. We also present convergence results for QMR, showing the connection between QMR and the generalized minimal residual (GMRES) algorithm, the optimal method in this class of methods. Finally, we give some numerical examples, both for eigenvalue computations and for non-Hermitian linear systems.

Superlinear convergence estimates for a conjugate gradient method for the biharmonic equation

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

Chan, R.H.; Delillo, T.K.; Horn, M.A.

1998-01-01

The method of Muskhelishvili for solving the biharmonic equation using conformal mapping is investigated. In [R.H. Chan, T.K. DeLillo, and M.A. Horn, SIAM J. Sci. Comput., 18 (1997), pp. 1571--1582] it was shown, using the Hankel structure, that the linear system in [N.I. Muskhelishvili, Some Basic Problems of the Mathematical Theory of Elasticity, Noordhoff, Groningen, the Netherlands] is the discretization of the identity plus a compact operator, and therefore the conjugate gradient method will converge superlinearly. Estimates are given here of the superlinear convergence in the cases when the boundary curve is analytic or in a Hoelder class.

Comparison of Conjugate Gradient Density Matrix Search and Chebyshev Expansion Methods for Avoiding Diagonalization in Large-Scale Electronic Structure Calculations

NASA Technical Reports Server (NTRS)

Bates, Kevin R.; Daniels, Andrew D.; Scuseria, Gustavo E.

1998-01-01

We report a comparison of two linear-scaling methods which avoid the diagonalization bottleneck of traditional electronic structure algorithms. The Chebyshev expansion method (CEM) is implemented for carbon tight-binding calculations of large systems and its memory and timing requirements compared to those of our previously implemented conjugate gradient density matrix search (CG-DMS). Benchmark calculations are carried out on icosahedral fullerenes from C60 to C8640 and the linear scaling memory and CPU requirements of the CEM demonstrated. We show that the CPU requisites of the CEM and CG-DMS are similar for calculations with comparable accuracy.

Inverse solutions for electrical impedance tomography based on conjugate gradients methods

NASA Astrophysics Data System (ADS)

Wang, M.

2002-01-01

A multistep inverse solution for two-dimensional electric field distribution is developed to deal with the nonlinear inverse problem of electric field distribution in relation to its boundary condition and the problem of divergence due to errors introduced by the ill-conditioned sensitivity matrix and the noise produced by electrode modelling and instruments. This solution is based on a normalized linear approximation method where the change in mutual impedance is derived from the sensitivity theorem and a method of error vector decomposition. This paper presents an algebraic solution of the linear equations at each inverse step, using a generalized conjugate gradients method. Limiting the number of iterations in the generalized conjugate gradients method controls the artificial errors introduced by the assumption of linearity and the ill-conditioned sensitivity matrix. The solution of the nonlinear problem is approached using a multistep inversion. This paper also reviews the mathematical and physical definitions of the sensitivity back-projection algorithm based on the sensitivity theorem. Simulations and discussion based on the multistep algorithm, the sensitivity coefficient back-projection method and the Newton-Raphson method are given. Examples of imaging gas-liquid mixing and a human hand in brine are presented.

Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves In The Predicting Process

NASA Astrophysics Data System (ADS)

Wanto, Anjar; Zarlis, Muhammad; Sawaluddin; Hartama, Dedy

2017-12-01

Backpropagation is a good artificial neural network algorithm used to predict, one of which is to predict the rate of Consumer Price Index (CPI) based on the foodstuff sector. While conjugate gradient fletcher reeves is a suitable optimization method when juxtaposed with backpropagation method, because this method can shorten iteration without reducing the quality of training and testing result. Consumer Price Index (CPI) data that will be predicted to come from the Central Statistics Agency (BPS) Pematangsiantar. The results of this study will be expected to contribute to the government in making policies to improve economic growth. In this study, the data obtained will be processed by conducting training and testing with artificial neural network backpropagation by using parameter learning rate 0,01 and target error minimum that is 0.001-0,09. The training network is built with binary and bipolar sigmoid activation functions. After the results with backpropagation are obtained, it will then be optimized using the conjugate gradient fletcher reeves method by conducting the same training and testing based on 5 predefined network architectures. The result, the method used can increase the speed and accuracy result.

Performance of Nonlinear Finite-Difference Poisson-Boltzmann Solvers

PubMed Central

Cai, Qin; Hsieh, Meng-Juei; Wang, Jun; Luo, Ray

2014-01-01

We implemented and optimized seven finite-difference solvers for the full nonlinear Poisson-Boltzmann equation in biomolecular applications, including four relaxation methods, one conjugate gradient method, and two inexact Newton methods. The performance of the seven solvers was extensively evaluated with a large number of nucleic acids and proteins. Worth noting is the inexact Newton method in our analysis. We investigated the role of linear solvers in its performance by incorporating the incomplete Cholesky conjugate gradient and the geometric multigrid into its inner linear loop. We tailored and optimized both linear solvers for faster convergence rate. In addition, we explored strategies to optimize the successive over-relaxation method to reduce its convergence failures without too much sacrifice in its convergence rate. Specifically we attempted to adaptively change the relaxation parameter and to utilize the damping strategy from the inexact Newton method to improve the successive over-relaxation method. Our analysis shows that the nonlinear methods accompanied with a functional-assisted strategy, such as the conjugate gradient method and the inexact Newton method, can guarantee convergence in the tested molecules. Especially the inexact Newton method exhibits impressive performance when it is combined with highly efficient linear solvers that are tailored for its special requirement. PMID:24723843

Panel flutter optimization by gradient projection

NASA Technical Reports Server (NTRS)

Pierson, B. L.

1975-01-01

A gradient projection optimal control algorithm incorporating conjugate gradient directions of search is described and applied to several minimum weight panel design problems subject to a flutter speed constraint. New numerical solutions are obtained for both simply-supported and clamped homogeneous panels of infinite span for various levels of inplane loading and minimum thickness. The minimum thickness inequality constraint is enforced by a simple transformation of variables.

Three-dimensional Gravity Inversion with a New Gradient Scheme on Unstructured Grids

NASA Astrophysics Data System (ADS)

Sun, S.; Yin, C.; Gao, X.; Liu, Y.; Zhang, B.

2017-12-01

Stabilized gradient-based methods have been proved to be efficient for inverse problems. Based on these methods, setting gradient close to zero can effectively minimize the objective function. Thus the gradient of objective function determines the inversion results. By analyzing the cause of poor resolution on depth in gradient-based gravity inversion methods, we find that imposing depth weighting functional in conventional gradient can improve the depth resolution to some extent. However, the improvement is affected by the regularization parameter and the effect of the regularization term becomes smaller with increasing depth (shown as Figure 1 (a)). In this paper, we propose a new gradient scheme for gravity inversion by introducing a weighted model vector. The new gradient can improve the depth resolution more efficiently, which is independent of the regularization parameter, and the effect of regularization term will not be weakened when depth increases. Besides, fuzzy c-means clustering method and smooth operator are both used as regularization terms to yield an internal consecutive inverse model with sharp boundaries (Sun and Li, 2015). We have tested our new gradient scheme with unstructured grids on synthetic data to illustrate the effectiveness of the algorithm. Gravity forward modeling with unstructured grids is based on the algorithm proposed by Okbe (1979). We use a linear conjugate gradient inversion scheme to solve the inversion problem. The numerical experiments show a great improvement in depth resolution compared with regular gradient scheme, and the inverse model is compact at all depths (shown as Figure 1 (b)). AcknowledgeThis research is supported by Key Program of National Natural Science Foundation of China (41530320), China Natural Science Foundation for Young Scientists (41404093), and Key National Research Project of China (2016YFC0303100, 2017YFC0601900). ReferencesSun J, Li Y. 2015. Multidomain petrophysically constrained inversion and geology differentiation using guided fuzzy c-means clustering. Geophysics, 80(4): ID1-ID18. Okabe M. 1979. Analytical expressions for gravity anomalies due to homogeneous polyhedral bodies and translations into magnetic anomalies. Geophysics, 44(4), 730-741.

Improved Synthesis and In Vitro Evaluation of an Aptamer Ribosomal Toxin Conjugate

PubMed Central

Kelly, Linsley; Kratschmer, Christina; Maier, Keith E.; Yan, Amy C.

2016-01-01

Delivery of toxins, such as the ricin A chain, Pseudomonas exotoxin, and gelonin, using antibodies has had some success in inducing specific toxicity in cancer treatments. However, these antibody-toxin conjugates, called immunotoxins, can be bulky, difficult to express, and may induce an immune response upon in vivo administration. We previously reported delivery of a recombinant variant of gelonin (rGel) by the full-length prostate-specific membrane antigen (PSMA) binding aptamer, A9, to potentially circumvent some of these problems. Here, we report a streamlined approach to generating aptamer-rGel conjugates utilizing a chemically synthesized minimized form of the A9 aptamer. Unlike the full-length A9 aptamer, this minimized variant can be chemically synthesized with a 5′ terminal thiol. This facilitates the large scale synthesis and generation of aptamer toxin conjugates linked by a reducible disulfide linkage. Using this approach, we generated aptamer-toxin conjugates and evaluated their binding specificity and toxicity. On PSMA(+) LNCaP prostate cancer cells, the A9.min-rGel conjugate demonstrated an IC50 of ∼60 nM. Additionally, we performed a stability analysis of this conjugate in mouse serum where the conjugate displayed a t1/2 of ∼4 h, paving the way for future in vivo experiments. PMID:27228412

River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal

2012-06-01

Estimating sediment volume carried by a river is an important issue in water resources engineering. This paper compares the accuracy of three different soft computing methods, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gene Expression Programming (GEP), in estimating daily suspended sediment concentration on rivers by using hydro-meteorological data. The daily rainfall, streamflow and suspended sediment concentration data from Eel River near Dos Rios, at California, USA are used as a case study. The comparison results indicate that the GEP model performs better than the other models in daily suspended sediment concentration estimation for the particular data sets used in this study. Levenberg-Marquardt, conjugate gradient and gradient descent training algorithms were used for the ANN models. Out of three algorithms, the Conjugate gradient algorithm was found to be better than the others.

RF Pulse Design using Nonlinear Gradient Magnetic Fields

PubMed Central

Kopanoglu, Emre; Constable, R. Todd

2014-01-01

Purpose An iterative k-space trajectory and radio-frequency (RF) pulse design method is proposed for Excitation using Nonlinear Gradient Magnetic fields (ENiGMa). Theory and Methods The spatial encoding functions (SEFs) generated by nonlinear gradient fields (NLGFs) are linearly dependent in Cartesian-coordinates. Left uncorrected, this may lead to flip-angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a Matching-Pursuit algorithm, and the RF pulse is designed using a Conjugate-Gradient algorithm. Three variants of the proposed approach are given: the full-algorithm, a computationally-cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. Results The method is compared to other iterative (Matching-Pursuit and Conjugate Gradient) and non-iterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity significantly. Conclusion An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. PMID:25203286

Wideband dichroic-filter design for LED-phosphor beam-combining

DOEpatents

Falicoff, Waqidi

2010-12-28

A general method is disclosed of designing two-component dichroic short-pass filters operable for incidence angle distributions over the 0-30.degree. range, and specific preferred embodiments are listed. The method is based on computer optimization algorithms for an N-layer design, specifically the N-dimensional conjugate-gradient minimization of a merit function based on difference from a target transmission spectrum, as well as subsequent cycles of needle synthesis for increasing N. A key feature of the method is the initial filter design, upon which the algorithm proceeds to iterate successive design candidates with smaller merit functions. This initial design, with high-index material H and low-index L, is (0.75 H, 0.5 L, 0.75 H)^m, denoting m (20-30) repetitions of a three-layer motif, giving rise to a filter with N=2 m+1.

First Applications of the New Parallel Krylov Solver for MODFLOW on a National and Global Scale

NASA Astrophysics Data System (ADS)

Verkaik, J.; Hughes, J. D.; Sutanudjaja, E.; van Walsum, P.

2016-12-01

Integrated high-resolution hydrologic models are increasingly being used for evaluating water management measures at field scale. Their drawbacks are large memory requirements and long run times. Examples of such models are The Netherlands Hydrological Instrument (NHI) model and the PCRaster Global Water Balance (PCR-GLOBWB) model. Typical simulation periods are 30-100 years with daily timesteps. The NHI model predicts water demands in periods of drought, supporting operational and long-term water-supply decisions. The NHI is a state-of-the-art coupling of several models: a 7-layer MODFLOW groundwater model ( 6.5M 250m cells), a MetaSWAP model for the unsaturated zone (Richards emulator of 0.5M cells), and a surface water model (MOZART-DM). The PCR-GLOBWB model provides a grid-based representation of global terrestrial hydrology and this work uses the version that includes a 2-layer MODFLOW groundwater model ( 4.5M 10km cells). The Parallel Krylov Solver (PKS) speeds up computation by both distributed memory parallelization (Message Passing Interface) and shared memory parallelization (Open Multi-Processing). PKS includes conjugate gradient, bi-conjugate gradient stabilized, and generalized minimal residual linear accelerators that use an overlapping additive Schwarz domain decomposition preconditioner. PKS can be used for both structured and unstructured grids and has been fully integrated in MODFLOW-USG using METIS partitioning and in iMODFLOW using RCB partitioning. iMODFLOW is an accelerated version of MODFLOW-2005 that is implicitly and online coupled to MetaSWAP. Results for benchmarks carried out on the Cartesius Dutch supercomputer (https://userinfo.surfsara.nl/systems/cartesius) for the PCRGLOB-WB model and on a 2x16 core Windows machine for the NHI model show speedups up to 10-20 and 5-10, respectively.

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

New hybrid conjugate gradient methods with the generalized Wolfe line search.

PubMed

Xu, Xiao; Kong, Fan-Yu

2016-01-01

The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.

Noise effect in an improved conjugate gradient algorithm to invert particle size distribution and the algorithm amendment.

PubMed

Wei, Yongjie; Ge, Baozhen; Wei, Yaolin

2009-03-20

In general, model-independent algorithms are sensitive to noise during laser particle size measurement. An improved conjugate gradient algorithm (ICGA) that can be used to invert particle size distribution (PSD) from diffraction data is presented. By use of the ICGA to invert simulated data with multiplicative or additive noise, we determined that additive noise is the main factor that induces distorted results. Thus the ICGA is amended by introduction of an iteration step-adjusting parameter and is used experimentally on simulated data and some samples. The experimental results show that the sensitivity of the ICGA to noise is reduced and the inverted results are in accord with the real PSD.

Preconditioned conjugate gradient methods for the compressible Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.

1990-01-01

The compressible Navier-Stokes equations are solved for a variety of two-dimensional inviscid and viscous problems by preconditioned conjugate gradient-like algorithms. Roe's flux difference splitting technique is used to discretize the inviscid fluxes. The viscous terms are discretized by using central differences. An algebraic turbulence model is also incorporated. The system of linear equations which arises out of the linearization of a fully implicit scheme is solved iteratively by the well known methods of GMRES (Generalized Minimum Residual technique) and Chebyschev iteration. Incomplete LU factorization and block diagonal factorization are used as preconditioners. The resulting algorithm is competitive with the best current schemes, but has wide applications in parallel computing and unstructured mesh computations.

A conjugate gradient method with descent properties under strong Wolfe line search

NASA Astrophysics Data System (ADS)

Zull, N.; ‘Aini, N.; Shoid, S.; Ghani, N. H. A.; Mohamed, N. S.; Rivaie, M.; Mamat, M.

2017-09-01

The conjugate gradient (CG) method is one of the optimization methods that are often used in practical applications. The continuous and numerous studies conducted on the CG method have led to vast improvements in its convergence properties and efficiency. In this paper, a new CG method possessing the sufficient descent and global convergence properties is proposed. The efficiency of the new CG algorithm relative to the existing CG methods is evaluated by testing them all on a set of test functions using MATLAB. The tests are measured in terms of iteration numbers and CPU time under strong Wolfe line search. Overall, this new method performs efficiently and comparable to the other famous methods.

A new nonlinear conjugate gradient coefficient under strong Wolfe-Powell line search

NASA Astrophysics Data System (ADS)

Mohamed, Nur Syarafina; Mamat, Mustafa; Rivaie, Mohd

2017-08-01

A nonlinear conjugate gradient method (CG) plays an important role in solving a large-scale unconstrained optimization problem. This method is widely used due to its simplicity. The method is known to possess sufficient descend condition and global convergence properties. In this paper, a new nonlinear of CG coefficient βk is presented by employing the Strong Wolfe-Powell inexact line search. The new βk performance is tested based on number of iterations and central processing unit (CPU) time by using MATLAB software with Intel Core i7-3470 CPU processor. Numerical experimental results show that the new βk converge rapidly compared to other classical CG method.

A modified conjugate gradient coefficient with inexact line search for unconstrained optimization

NASA Astrophysics Data System (ADS)

Aini, Nurul; Rivaie, Mohd; Mamat, Mustafa

2016-11-01

Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. Its low memory requirements and global convergence properties makes it one of the most preferred method in real life application such as in engineering and business. In this paper, we present a new CG method based on AMR* and CD method for solving unconstrained optimization functions. The resulting algorithm is proven to have both the sufficient descent and global convergence properties under inexact line search. Numerical tests are conducted to assess the effectiveness of the new method in comparison to some previous CG methods. The results obtained indicate that our method is indeed superior.

A feasibility study of a 3-D finite element solution scheme for aeroengine duct acoustics

NASA Technical Reports Server (NTRS)

Abrahamson, A. L.

1980-01-01

The advantage from development of a 3-D model of aeroengine duct acoustics is the ability to analyze axial and circumferential liner segmentation simultaneously. The feasibility of a 3-D duct acoustics model was investigated using Galerkin or least squares element formulations combined with Gaussian elimination, successive over-relaxation, or conjugate gradient solution algorithms on conventional scalar computers and on a vector machine. A least squares element formulation combined with a conjugate gradient solver on a CDC Star vector computer initially appeared to have great promise, but severe difficulties were encountered with matrix ill-conditioning. These difficulties in conditioning rendered this technique impractical for realistic problems.

Method to create gradient index in a polymer

DOEpatents

Dirk, Shawn M; Johnson, Ross Stefan; Boye, Robert; Descour, Michael R; Sweatt, William C; Wheeler, David R; Kaehr, Bryan James

2014-10-14

Novel photo-writable and thermally switchable polymeric materials exhibit a refractive index change of .DELTA.n.gtoreq.1.0 when exposed to UV light or heat. For example, lithography can be used to convert a non-conjugated precursor polymer to a conjugated polymer having a higher index-of-refraction. Further, two-photon lithography can be used to pattern high-spatial frequency structures.

$L_{0}$ Gradient Projection.

PubMed

Ono, Shunsuke

2017-04-01

Minimizing L 0 gradient, the number of the non-zero gradients of an image, together with a quadratic data-fidelity to an input image has been recognized as a powerful edge-preserving filtering method. However, the L 0 gradient minimization has an inherent difficulty: a user-given parameter controlling the degree of flatness does not have a physical meaning since the parameter just balances the relative importance of the L 0 gradient term to the quadratic data-fidelity term. As a result, the setting of the parameter is a troublesome work in the L 0 gradient minimization. To circumvent the difficulty, we propose a new edge-preserving filtering method with a novel use of the L 0 gradient. Our method is formulated as the minimization of the quadratic data-fidelity subject to the hard constraint that the L 0 gradient is less than a user-given parameter α . This strategy is much more intuitive than the L 0 gradient minimization because the parameter α has a clear meaning: the L 0 gradient value of the output image itself, so that one can directly impose a desired degree of flatness by α . We also provide an efficient algorithm based on the so-called alternating direction method of multipliers for computing an approximate solution of the nonconvex problem, where we decompose it into two subproblems and derive closed-form solutions to them. The advantages of our method are demonstrated through extensive experiments.

Primer vector theory and applications

NASA Technical Reports Server (NTRS)

Jezewski, D. J.

1975-01-01

A method developed to compute two-body, optimal, N-impulse trajectories was presented. The necessary conditions established define the gradient structure of the primer vector and its derivative for any set of boundary conditions and any number of impulses. Inequality constraints, a conjugate gradient iterator technique, and the use of a penalty function were also discussed.

Computational trigonometry

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

Gustafson, K.

1994-12-31

By means of the author`s earlier theory of antieigenvalues and antieigenvectors, a new computational approach to iterative methods is presented. This enables an explicit trigonometric understanding of iterative convergence and provides new insights into the sharpness of error bounds. Direct applications to Gradient descent, Conjugate gradient, GCR(k), Orthomin, CGN, GMRES, CGS, and other matrix iterative schemes will be given.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients.

PubMed

Chen, Weitian; Sica, Christopher T; Meyer, Craig H

2008-11-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method.

A forward model and conjugate gradient inversion technique for low-frequency ultrasonic imaging.

PubMed

van Dongen, Koen W A; Wright, William M D

2006-10-01

Emerging methods of hyperthermia cancer treatment require noninvasive temperature monitoring, and ultrasonic techniques show promise in this regard. Various tomographic algorithms are available that reconstruct sound speed or contrast profiles, which can be related to temperature distribution. The requirement of a high enough frequency for adequate spatial resolution and a low enough frequency for adequate tissue penetration is a difficult compromise. In this study, the feasibility of using low frequency ultrasound for imaging and temperature monitoring was investigated. The transient probing wave field had a bandwidth spanning the frequency range 2.5-320.5 kHz. The results from a forward model which computed the propagation and scattering of low-frequency acoustic pressure and velocity wave fields were used to compare three imaging methods formulated within the Born approximation, representing two main types of reconstruction. The first uses Fourier techniques to reconstruct sound-speed profiles from projection or Radon data based on optical ray theory, seen as an asymptotical limit for comparison. The second uses backpropagation and conjugate gradient inversion methods based on acoustical wave theory. The results show that the accuracy in localization was 2.5 mm or better when using low frequencies and the conjugate gradient inversion scheme, which could be used for temperature monitoring.

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

NASA Astrophysics Data System (ADS)

Wang, Tai-Han; Huang, Da-Nian; Ma, Guo-Qing; Meng, Zhao-Hai; Li, Ye

2017-06-01

With the continuous development of full tensor gradiometer (FTG) measurement techniques, three-dimensional (3D) inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit (GPU) and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation (SSOR) technique and the incomplete Choleksy decomposition conjugate gradient algorithm (ICCG). Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noisecontaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit (CPU). Real airborne gravity-gradiometry data from Vinton salt dome (southwest Louisiana, USA) are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

A conjugate gradient method for solving the non-LTE line radiation transfer problem

NASA Astrophysics Data System (ADS)

Paletou, F.; Anterrieu, E.

2009-12-01

This study concerns the fast and accurate solution of the line radiation transfer problem, under non-LTE conditions. We propose and evaluate an alternative iterative scheme to the classical ALI-Jacobi method, and to the more recently proposed Gauss-Seidel and successive over-relaxation (GS/SOR) schemes. Our study is indeed based on applying a preconditioned bi-conjugate gradient method (BiCG-P). Standard tests, in 1D plane parallel geometry and in the frame of the two-level atom model with monochromatic scattering are discussed. Rates of convergence between the previously mentioned iterative schemes are compared, as are their respective timing properties. The smoothing capability of the BiCG-P method is also demonstrated.

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

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

None, None

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

The DANTE Boltzmann transport solver: An unstructured mesh, 3-D, spherical harmonics algorithm compatible with parallel computer architectures

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

McGhee, J.M.; Roberts, R.M.; Morel, J.E.

1997-06-01

A spherical harmonics research code (DANTE) has been developed which is compatible with parallel computer architectures. DANTE provides 3-D, multi-material, deterministic, transport capabilities using an arbitrary finite element mesh. The linearized Boltzmann transport equation is solved in a second order self-adjoint form utilizing a Galerkin finite element spatial differencing scheme. The core solver utilizes a preconditioned conjugate gradient algorithm. Other distinguishing features of the code include options for discrete-ordinates and simplified spherical harmonics angular differencing, an exact Marshak boundary treatment for arbitrarily oriented boundary faces, in-line matrix construction techniques to minimize memory consumption, and an effective diffusion based preconditioner formore » scattering dominated problems. Algorithm efficiency is demonstrated for a massively parallel SIMD architecture (CM-5), and compatibility with MPP multiprocessor platforms or workstation clusters is anticipated.« less

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Exploring structural properties of small carbon clusters Cn (n = 1, 2, 3) using molecular mechanics and energy minimization

NASA Astrophysics Data System (ADS)

Miswan, M. A.; Gopir, G.; Anas, M. M.

2016-11-01

Geometry optimization is one of the most widely used methods to study in carbon cluster Cn to understand its structural properties. The total energy for each of the structures was calculated using Octopus software with conjugate gradient Broyden-Fletcher-Goldfarb-Shanno (CG-BFGS). Our calculation and other studies indicate that the linear forms are the most stable structures. However, the C3 isomers have equal probability to form, as the differences in our calculation of total energy are statistically insignificant. Despite there are two cohort of total energy, the calculations are acceptable due to the energy ratio between C3 to C2 and C2 to C1 are comparable to others work. Meanwhile, the bond properties of the C2 and C3 bonds also gives significant difference between our work and previous study.

Layout optimization with algebraic multigrid methods

NASA Technical Reports Server (NTRS)

Regler, Hans; Ruede, Ulrich

1993-01-01

Finding the optimal position for the individual cells (also called functional modules) on the chip surface is an important and difficult step in the design of integrated circuits. This paper deals with the problem of relative placement, that is the minimization of a quadratic functional with a large, sparse, positive definite system matrix. The basic optimization problem must be augmented by constraints to inhibit solutions where cells overlap. Besides classical iterative methods, based on conjugate gradients (CG), we show that algebraic multigrid methods (AMG) provide an interesting alternative. For moderately sized examples with about 10000 cells, AMG is already competitive with CG and is expected to be superior for larger problems. Besides the classical 'multiplicative' AMG algorithm where the levels are visited sequentially, we propose an 'additive' variant of AMG where levels may be treated in parallel and that is suitable as a preconditioner in the CG algorithm.

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

DOE PAGES

None, None

2016-11-21

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

CPDES3: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in three dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on three-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES3 allows each spatial operator to have 7, 15, 19, or 27 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect induces which is vectorizable on some of the newer scientific computers.

CPDES2: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in two dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on two-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES2 allows each spatial operator to have 5 or 9 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect indices which is vectorizable on some of the newer scientific computers.

Conjugation of gold nanoparticles and recombinant human endostatin modulates vascular normalization via interruption of anterior gradient 2-mediated angiogenesis.

PubMed

Pan, Fan; Yang, Wende; Li, Wei; Yang, Xiao-Yan; Liu, Shuhao; Li, Xin; Zhao, Xiaoxu; Ding, Hui; Qin, Li; Pan, Yunlong

2017-07-01

Several studies have revealed the potential of normalizing tumor vessels in anti-angiogenic treatment. Recombinant human endostatin is an anti-angiogenic agent which has been applied in clinical tumor treatment. Our previous research indicated that gold nanoparticles could be a nanoparticle carrier for recombinant human endostatin delivery. The recombinant human endostatin-gold nanoparticle conjugates normalized vessels, which improved chemotherapy. However, the mechanism of recombinant human endostatin-gold nanoparticle-induced vascular normalization has not been explored. Anterior gradient 2 has been reported to be over-expressed in many malignant tumors and involved in tumor angiogenesis. To date, the precise efficacy of recombinant human endostatin-gold nanoparticles on anterior gradient 2-mediated angiogenesis or anterior gradient 2-related signaling cohort remained unknown. In this study, we aimed to explore whether recombinant human endostatin-gold nanoparticles could normalize vessels in metastatic colorectal cancer xenografts, and we further elucidated whether recombinant human endostatin-gold nanoparticles could interrupt anterior gradient 2-induced angiogenesis. In vivo, it was indicated that recombinant human endostatin-gold nanoparticles increased pericyte expression while inhibit vascular endothelial growth factor receptor 2 and anterior gradient 2 expression in metastatic colorectal cancer xenografts. In vitro, we uncovered that recombinant human endostatin-gold nanoparticles reduced cell migration and tube formation induced by anterior gradient 2 in human umbilical vein endothelial cells. Treatment with recombinant human endostatin-gold nanoparticles attenuated anterior gradient 2-mediated activation of MMP2, cMyc, VE-cadherin, phosphorylation of p38, and extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) in human umbilical vein endothelial cells. Our findings demonstrated recombinant human endostatin-gold nanoparticles might normalize vessels by interfering anterior gradient 2-mediated angiogenesis in metastatic colorectal cancer.

Crystal growth and annealing for minimized residual stress

DOEpatents

Gianoulakis, Steven E.

2002-01-01

A method and apparatus for producing crystals that minimizes birefringence even at large crystal sizes, and is suitable for production of CaF.sub.2 crystals. The method of the present invention comprises annealing a crystal by maintaining a minimal temperature gradient in the crystal while slowly reducing the bulk temperature of the crystal. An apparatus according to the present invention includes a thermal control system added to a crystal growth and annealing apparatus, wherein the thermal control system allows a temperature gradient during crystal growth but minimizes the temperature gradient during crystal annealing.

Towards the minimization of thermodynamic irreversibility in an electrically actuated microflow of a viscoelastic fluid under electrical double layer phenomenon

NASA Astrophysics Data System (ADS)

Sarma, Rajkumar; Jain, Manish; Mondal, Pranab Kumar

2017-10-01

We discuss the entropy generation minimization for electro-osmotic flow of a viscoelastic fluid through a parallel plate microchannel under the combined influences of interfacial slip and conjugate transport of heat. We use in this study the simplified Phan-Thien-Tanner model to describe the rheological behavior of the viscoelastic fluid. Using Navier's slip law and thermal boundary conditions of the third kind, we solve the transport equations analytically and evaluate the global entropy generation rate of the system. We examine the influential role of the following parameters on the entropy generation rate of the system, viz., the viscoelastic parameter (ɛDe2), Debye-Hückel parameter ( κ ¯ ) , channel wall thickness (δ), thermal conductivity of the wall (γ), Biot number (Bi), Peclet number (Pe), and axial temperature gradient (B). This investigation finally establishes the optimum values of the abovementioned parameters, leading to the minimum entropy generation of the system. We believe that results of this analysis could be helpful in optimizing the second-law performance of microscale thermal management devices, including the micro-heat exchangers, micro-reactors, and micro-heat pipes.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients

PubMed Central

Chen, Weitian; Sica, Christopher T.; Meyer, Craig H.

2008-01-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method. PMID:18956462

Crystal growth and annealing method and apparatus

DOEpatents

Gianoulakis, Steven E.; Sparrow, Robert

2001-01-01

A method and apparatus for producing crystals that minimizes birefringence even at large crystal sizes, and is suitable for production of CaF.sub.2 crystals. The method of the present invention comprises annealing a crystal by maintaining a minimal temperature gradient in the crystal while slowly reducing the bulk temperature of the crystal. An apparatus according to the present invention includes a thermal control system added to a crystal growth and annealing apparatus, wherein the thermal control system allows a temperature gradient during crystal growth but minimizes the temperature gradient during crystal annealing. An embodiment of the present invention comprises a secondary heater incorporated into a conventional crystal growth and annealing apparatus. The secondary heater supplies heat to minimize the temperature gradients in the crystal during the annealing process. The secondary heater can mount near the bottom of the crucible to effectively maintain appropriate temperature gradients.

Truncated Conjugate Gradient: An Optimal Strategy for the Analytical Evaluation of the Many-Body Polarization Energy and Forces in Molecular Simulations.

PubMed

Aviat, Félix; Levitt, Antoine; Stamm, Benjamin; Maday, Yvon; Ren, Pengyu; Ponder, Jay W; Lagardère, Louis; Piquemal, Jean-Philip

2017-01-10

We introduce a new class of methods, denoted as Truncated Conjugate Gradient(TCG), to solve the many-body polarization energy and its associated forces in molecular simulations (i.e. molecular dynamics (MD) and Monte Carlo). The method consists in a fixed number of Conjugate Gradient (CG) iterations. TCG approaches provide a scalable solution to the polarization problem at a user-chosen cost and a corresponding optimal accuracy. The optimality of the CG-method guarantees that the number of the required matrix-vector products are reduced to a minimum compared to other iterative methods. This family of methods is non-empirical, fully adaptive, and provides analytical gradients, avoiding therefore any energy drift in MD as compared to popular iterative solvers. Besides speed, one great advantage of this class of approximate methods is that their accuracy is systematically improvable. Indeed, as the CG-method is a Krylov subspace method, the associated error is monotonically reduced at each iteration. On top of that, two improvements can be proposed at virtually no cost: (i) the use of preconditioners can be employed, which leads to the Truncated Preconditioned Conjugate Gradient (TPCG); (ii) since the residual of the final step of the CG-method is available, one additional Picard fixed point iteration ("peek"), equivalent to one step of Jacobi Over Relaxation (JOR) with relaxation parameter ω, can be made at almost no cost. This method is denoted by TCG-n(ω). Black-box adaptive methods to find good choices of ω are provided and discussed. Results show that TPCG-3(ω) is converged to high accuracy (a few kcal/mol) for various types of systems including proteins and highly charged systems at the fixed cost of four matrix-vector products: three CG iterations plus the initial CG descent direction. Alternatively, T(P)CG-2(ω) provides robust results at a reduced cost (three matrix-vector products) and offers new perspectives for long polarizable MD as a production algorithm. The T(P)CG-1(ω) level provides less accurate solutions for inhomogeneous systems, but its applicability to well-conditioned problems such as water is remarkable, with only two matrix-vector product evaluations.

Truncated Conjugate Gradient: An Optimal Strategy for the Analytical Evaluation of the Many-Body Polarization Energy and Forces in Molecular Simulations

PubMed Central

2016-01-01

We introduce a new class of methods, denoted as Truncated Conjugate Gradient(TCG), to solve the many-body polarization energy and its associated forces in molecular simulations (i.e. molecular dynamics (MD) and Monte Carlo). The method consists in a fixed number of Conjugate Gradient (CG) iterations. TCG approaches provide a scalable solution to the polarization problem at a user-chosen cost and a corresponding optimal accuracy. The optimality of the CG-method guarantees that the number of the required matrix-vector products are reduced to a minimum compared to other iterative methods. This family of methods is non-empirical, fully adaptive, and provides analytical gradients, avoiding therefore any energy drift in MD as compared to popular iterative solvers. Besides speed, one great advantage of this class of approximate methods is that their accuracy is systematically improvable. Indeed, as the CG-method is a Krylov subspace method, the associated error is monotonically reduced at each iteration. On top of that, two improvements can be proposed at virtually no cost: (i) the use of preconditioners can be employed, which leads to the Truncated Preconditioned Conjugate Gradient (TPCG); (ii) since the residual of the final step of the CG-method is available, one additional Picard fixed point iteration (“peek”), equivalent to one step of Jacobi Over Relaxation (JOR) with relaxation parameter ω, can be made at almost no cost. This method is denoted by TCG-n(ω). Black-box adaptive methods to find good choices of ω are provided and discussed. Results show that TPCG-3(ω) is converged to high accuracy (a few kcal/mol) for various types of systems including proteins and highly charged systems at the fixed cost of four matrix-vector products: three CG iterations plus the initial CG descent direction. Alternatively, T(P)CG-2(ω) provides robust results at a reduced cost (three matrix-vector products) and offers new perspectives for long polarizable MD as a production algorithm. The T(P)CG-1(ω) level provides less accurate solutions for inhomogeneous systems, but its applicability to well-conditioned problems such as water is remarkable, with only two matrix-vector product evaluations. PMID:28068773

Conjugate-gradient optimization method for orbital-free density functional calculations.

PubMed

Jiang, Hong; Yang, Weitao

2004-08-01

Orbital-free density functional theory as an extension of traditional Thomas-Fermi theory has attracted a lot of interest in the past decade because of developments in both more accurate kinetic energy functionals and highly efficient numerical methodology. In this paper, we developed a conjugate-gradient method for the numerical solution of spin-dependent extended Thomas-Fermi equation by incorporating techniques previously used in Kohn-Sham calculations. The key ingredient of the method is an approximate line-search scheme and a collective treatment of two spin densities in the case of spin-dependent extended Thomas-Fermi problem. Test calculations for a quartic two-dimensional quantum dot system and a three-dimensional sodium cluster Na216 with a local pseudopotential demonstrate that the method is accurate and efficient. (c) 2004 American Institute of Physics.

An efficient impedance method for induced field evaluation based on a stabilized Bi-conjugate gradient algorithm.

PubMed

Wang, Hua; Liu, Feng; Xia, Ling; Crozier, Stuart

2008-11-21

This paper presents a stabilized Bi-conjugate gradient algorithm (BiCGstab) that can significantly improve the performance of the impedance method, which has been widely applied to model low-frequency field induction phenomena in voxel phantoms. The improved impedance method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional, successive over-relaxation (SOR)-based algorithm. The scheme has been validated against other numerical/analytical solutions on a lossy, multilayered sphere phantom excited by an ideal coil loop. To demonstrate the computational performance and application capability of the developed algorithm, the induced fields inside a human phantom due to a low-frequency hyperthermia device is evaluated. The simulation results show the numerical accuracy and superior performance of the method.

Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method.

PubMed

He, Xiaowei; Liang, Jimin; Wang, Xiaorui; Yu, Jingjing; Qu, Xiaochao; Wang, Xiaodong; Hou, Yanbin; Chen, Duofang; Liu, Fang; Tian, Jie

2010-11-22

In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.

High-fidelity phase and amplitude control of phase-only computer generated holograms using conjugate gradient minimisation.

PubMed

Bowman, D; Harte, T L; Chardonnet, V; De Groot, C; Denny, S J; Le Goc, G; Anderson, M; Ireland, P; Cassettari, D; Bruce, G D

2017-05-15

We demonstrate simultaneous control of both the phase and amplitude of light using a conjugate gradient minimisation-based hologram calculation technique and a single phase-only spatial light modulator (SLM). A cost function, which incorporates the inner product of the light field with a chosen target field within a defined measure region, is efficiently minimised to create high fidelity patterns in the Fourier plane of the SLM. A fidelity of F = 0.999997 is achieved for a pattern resembling an LG10 mode with a calculated light-usage efficiency of 41.5%. Possible applications of our method in optical trapping and ultracold atoms are presented and we show uncorrected experimental realisation of our patterns with F = 0.97 and 7.8% light efficiency.

In Vitro Structural and Functional Evaluation of Gold Nanoparticles Conjugated Antibiotics

NASA Astrophysics Data System (ADS)

Saha, Biswarup; Bhattacharya, Jaydeep; Mukherjee, Ananda; Ghosh, Anup Kumar; Santra, Chitta Ranjan; Dasgupta, Anjan K.; Karmakar, Parimal

2007-12-01

Bactericidal efficacy of gold nanoparticles conjugated with ampicillin, streptomycin and kanamycin were evaluated. Gold nanoparticles (Gnps) were conjugated with the antibiotics during the synthesis of nanoparticles utilizing the combined reducing property of antibiotics and sodium borohydride. The conjugation of nanoparticles was confirmed by dynamic light scattering (DLS) and electron microscopic (EM) studies. Such Gnps conjugated antibiotics showed greater bactericidal activity in standard agar well diffusion assay. The minimal inhibitory concentration (MIC) values of all the three antibiotics along with their Gnps conjugated forms were determined in three bacterial strains, Escherichia coli DH5α, Micrococcus luteus and Staphylococcus aureus. Among them, streptomycin and kanamycin showed significant reduction in MIC values in their Gnps conjugated form whereas; Gnps conjugated ampicillin showed slight decrement in the MIC value compared to its free form. On the other hand, all of them showed more heat stability in their Gnps conjugated forms. Thus, our findings indicated that Gnps conjugated antibiotics are more efficient and might have significant therapeutic implications.

LC-NMR Technique in the Analysis of Phytosterols in Natural Extracts

PubMed Central

Horník, Štěpán; Sajfrtová, Marie; Sýkora, Jan; Březinová, Anna; Wimmer, Zdeněk

2013-01-01

The ability of LC-NMR to detect simultaneously free and conjugated phytosterols in natural extracts was tested. The advantages and disadvantages of a gradient HPLC-NMR method were compared to the fast composition screening using SEC-NMR method. Fractions of free and conjugated phytosterols were isolated and analyzed by isocratic HPLC-NMR methods. The results of qualitative and quantitative analyses were in a good agreement with the literature data. PMID:24455424

Approximate solution of the p-median minimization problem

NASA Astrophysics Data System (ADS)

Il'ev, V. P.; Il'eva, S. D.; Navrotskaya, A. A.

2016-09-01

A version of the facility location problem (the well-known p-median minimization problem) and its generalization—the problem of minimizing a supermodular set function—is studied. These problems are NP-hard, and they are approximately solved by a gradient algorithm that is a discrete analog of the steepest descent algorithm. A priori bounds on the worst-case behavior of the gradient algorithm for the problems under consideration are obtained. As a consequence, a bound on the performance guarantee of the gradient algorithm for the p-median minimization problem in terms of the production and transportation cost matrix is obtained.

Finite-frequency tomography using adjoint methods-Methodology and examples using membrane surface waves

NASA Astrophysics Data System (ADS)

Tape, Carl; Liu, Qinya; Tromp, Jeroen

2007-03-01

We employ adjoint methods in a series of synthetic seismic tomography experiments to recover surface wave phase-speed models of southern California. Our approach involves computing the Fréchet derivative for tomographic inversions via the interaction between a forward wavefield, propagating from the source to the receivers, and an `adjoint' wavefield, propagating from the receivers back to the source. The forward wavefield is computed using a 2-D spectral-element method (SEM) and a phase-speed model for southern California. A `target' phase-speed model is used to generate the `data' at the receivers. We specify an objective or misfit function that defines a measure of misfit between data and synthetics. For a given receiver, the remaining differences between data and synthetics are time-reversed and used as the source of the adjoint wavefield. For each earthquake, the interaction between the regular and adjoint wavefields is used to construct finite-frequency sensitivity kernels, which we call event kernels. An event kernel may be thought of as a weighted sum of phase-specific (e.g. P) banana-doughnut kernels, with weights determined by the measurements. The overall sensitivity is simply the sum of event kernels, which defines the misfit kernel. The misfit kernel is multiplied by convenient orthonormal basis functions that are embedded in the SEM code, resulting in the gradient of the misfit function, that is, the Fréchet derivative. A non-linear conjugate gradient algorithm is used to iteratively improve the model while reducing the misfit function. We illustrate the construction of the gradient and the minimization algorithm, and consider various tomographic experiments, including source inversions, structural inversions and joint source-structure inversions. Finally, we draw connections between classical Hessian-based tomography and gradient-based adjoint tomography.

Distributed Memory Parallel Computing with SEAWAT

NASA Astrophysics Data System (ADS)

Verkaik, J.; Huizer, S.; van Engelen, J.; Oude Essink, G.; Ram, R.; Vuik, K.

2017-12-01

Fresh groundwater reserves in coastal aquifers are threatened by sea-level rise, extreme weather conditions, increasing urbanization and associated groundwater extraction rates. To counteract these threats, accurate high-resolution numerical models are required to optimize the management of these precious reserves. The major model drawbacks are long run times and large memory requirements, limiting the predictive power of these models. Distributed memory parallel computing is an efficient technique for reducing run times and memory requirements, where the problem is divided over multiple processor cores. A new Parallel Krylov Solver (PKS) for SEAWAT is presented. PKS has recently been applied to MODFLOW and includes Conjugate Gradient (CG) and Biconjugate Gradient Stabilized (BiCGSTAB) linear accelerators. Both accelerators are preconditioned by an overlapping additive Schwarz preconditioner in a way that: a) subdomains are partitioned using Recursive Coordinate Bisection (RCB) load balancing, b) each subdomain uses local memory only and communicates with other subdomains by Message Passing Interface (MPI) within the linear accelerator, c) it is fully integrated in SEAWAT. Within SEAWAT, the PKS-CG solver replaces the Preconditioned Conjugate Gradient (PCG) solver for solving the variable-density groundwater flow equation and the PKS-BiCGSTAB solver replaces the Generalized Conjugate Gradient (GCG) solver for solving the advection-diffusion equation. PKS supports the third-order Total Variation Diminishing (TVD) scheme for computing advection. Benchmarks were performed on the Dutch national supercomputer (https://userinfo.surfsara.nl/systems/cartesius) using up to 128 cores, for a synthetic 3D Henry model (100 million cells) and the real-life Sand Engine model ( 10 million cells). The Sand Engine model was used to investigate the potential effect of the long-term morphological evolution of a large sand replenishment and climate change on fresh groundwater resources. Speed-ups up to 40 were obtained with the new PKS solver.

Identifying Time Periods of Minimal Thermal Gradient for Temperature-Driven Structural Health Monitoring

PubMed Central

Reilly, John; Glisic, Branko

2018-01-01

Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature–deformation–displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University. PMID:29494496

Identifying Time Periods of Minimal Thermal Gradient for Temperature-Driven Structural Health Monitoring.

PubMed

Reilly, John; Glisic, Branko

2018-03-01

Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature-deformation-displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University.

Scintillation Reduction using Conjugate-Plane Imaging

NASA Astrophysics Data System (ADS)

Vander Haagen, Gary A.

2017-06-01

All observatories are plagued by atmospheric turbulence exhibited as star scintillation or "twinkle" whether a high altitude adaptive optics research or a 30 cm amateur telescope. It is well known that these disturbances are caused by wind and temperature driven refractive gradients in the atmosphere and limit the ultimate photometric resolution of land-based facilities. One approach identified by Fuchs (1998) for scintillation noise reduction was to create a conjugate image space at the telescope and focus on the dominant conjugate turbulent layer within that space. When focused on the turbulent layer little or no scintillation exists. This technique is described whereby noise reductions of 6 to 11/1 have been experienced with mathematical and optical bench simulations. Discussed is a proof-of-principle conjugate optical train design for an 80 mm, f-7 telescope.

Higher order reconstruction for MRI in the presence of spatiotemporal field perturbations.

PubMed

Wilm, Bertram J; Barmet, Christoph; Pavan, Matteo; Pruessmann, Klaas P

2011-06-01

Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k-space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third-order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate-gradient algorithm that uses explicit matrix-vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Copyright © 2011 Wiley-Liss, Inc.

Parallel Conjugate Gradient: Effects of Ordering Strategies, Programming Paradigms, and Architectural Platforms

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Heber, Gerd; Biswas, Rupak

2000-01-01

The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV) usually accounts for most of the floating-point operations within a CG iteration. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and SPMV using different programming paradigms and architectures. Results show that for this class of applications, ordering significantly improves overall performance, that cache reuse may be more important than reducing communication, and that it is possible to achieve message passing performance using shared memory constructs through careful data ordering and distribution. However, a multi-threaded implementation of CG on the Tera MTA does not require special ordering or partitioning to obtain high efficiency and scalability.

Using Elman recurrent neural networks with conjugate gradient algorithm in determining the anesthetic the amount of anesthetic medicine to be applied.

PubMed

Güntürkün, Rüştü

2010-08-01

In this study, Elman recurrent neural networks have been defined by using conjugate gradient algorithm in order to determine the depth of anesthesia in the continuation stage of the anesthesia and to estimate the amount of medicine to be applied at that moment. The feed forward neural networks are also used for comparison. The conjugate gradient algorithm is compared with back propagation (BP) for training of the neural Networks. The applied artificial neural network is composed of three layers, namely the input layer, the hidden layer and the output layer. The nonlinear activation function sigmoid (sigmoid function) has been used in the hidden layer and the output layer. EEG data has been recorded with Nihon Kohden 9200 brand 22-channel EEG device. The international 8-channel bipolar 10-20 montage system (8 TB-b system) has been used in assembling the recording electrodes. EEG data have been recorded by being sampled once in every 2 milliseconds. The artificial neural network has been designed so as to have 60 neurons in the input layer, 30 neurons in the hidden layer and 1 neuron in the output layer. The values of the power spectral density (PSD) of 10-second EEG segments which correspond to the 1-50 Hz frequency range; the ratio of the total power of PSD values of the EEG segment at that moment in the same range to the total of PSD values of EEG segment taken prior to the anesthesia.

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

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.

A conjugate gradients/trust regions algorithms for training multilayer perceptrons for nonlinear mapping

NASA Technical Reports Server (NTRS)

Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.

1992-01-01

This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.

Scintillation Reduction using Conjugate-Plane Imaging (Abstract)

NASA Astrophysics Data System (ADS)

Vander Haagen, G. A.

2017-12-01

(Abstract only) All observatories are plagued by atmospheric turbulence exhibited as star scintillation or "twinkle" whether a high altitude adaptive optics research or a 30-cm amateur telescope. It is well known that these disturbances are caused by wind and temperature-driven refractive gradients in the atmosphere and limit the ultimate photometric resolution of land-based facilities. One approach identified by Fuchs (1998) for scintillation noise reduction was to create a conjugate image space at the telescope and focus on the dominant conjugate turbulent layer within that space. When focused on the turbulent layer little or no scintillation exists. This technique is described whereby noise reductions of 6 to 11/1 have been experienced with mathematical and optical bench simulations. Discussed is a proof-of-principle conjugate optical train design for an 80-mm, f7 telescope.

Method of Conjugate Radii for Solving Linear and Nonlinear Systems

NASA Technical Reports Server (NTRS)

Nachtsheim, Philip R.

1999-01-01

This paper describes a method to solve a system of N linear equations in N steps. A quadratic form is developed involving the sum of the squares of the residuals of the equations. Equating the quadratic form to a constant yields a surface which is an ellipsoid. For different constants, a family of similar ellipsoids can be generated. Starting at an arbitrary point an orthogonal basis is constructed and the center of the family of similar ellipsoids is found in this basis by a sequence of projections. The coordinates of the center in this basis are the solution of linear system of equations. A quadratic form in N variables requires N projections. That is, the current method is an exact method. It is shown that the sequence of projections is equivalent to a special case of the Gram-Schmidt orthogonalization process. The current method enjoys an advantage not shared by the classic Method of Conjugate Gradients. The current method can be extended to nonlinear systems without modification. For nonlinear equations the Method of Conjugate Gradients has to be augmented with a line-search procedure. Results for linear and nonlinear problems are presented.

Affibody Molecules for In vivo Characterization of HER2-Positive Tumors by Near-Infrared Imaging

PubMed Central

Lee, Sang Bong; Hassan, Moinuddin; Fisher, Robert; Chertov, Oleg; Chernomordik, Victor; Kramer-Marek, Gabriela; Gandjbakhche, Amir; Capala, Jacek

2012-01-01

Purpose HER2 overexpression has been associated with a poor prognosis and resistance to therapy in breast cancer patients. We are developing molecular probes for in vivo quantitative imaging of HER2 receptors using near-infrared optical imaging. The goal is to provide probes that will minimally interfere with the studied system, i.e., whose binding does not interfere with the binding of the therapeutic agents, and whose effect on the target cells is minimal. Experimental Design We used three different types of HER2-specific Affibody molecules [monomer ZHER2:342, dimer (ZHER2:477)2, and albumin-binding domain-fused-(ZHER2:342)2] as targeting agents, and labeled them with Alexa Fluor dyes. Trastuzumab was also conjugated, using commercially available kits, as a standard control. The resulting conjugates were characterized in vitro by toxicity assays, Biacore affinity measurements, flow cytometry, and confocal microscopy. Semi-uantitative in vivo near-infrared optical imaging studies were carried out using mice with subcutaneous xenografts of HER2-positive tumors. Results The HER2-specific Affibody molecules were not toxic to HER2-overexpressing cells and their binding to HER2 did interfere with neither binding nor effectives of trastuzumab. The binding affinities and specificities of the Affibody-Alexa Fluor fluorescent conjugates to HER2 were unchanged or minimally affected by the modifications. Pharmacokinetics and biodistribution studies showed the albumin-binding domain-fused-(ZHER2:342)2-Alexa Fluor 750 conjugate to be an optimal probe for optical imaging of HER2 in vivo. Conclusion Our results suggest that Affibody-Alexa Fluor conjugates may be used as a specific near-infrared probe for the non-invasive semi-quantitative imaging of HER2 expression in vivo. PMID:18559604

Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Peters, Jeanne M.

1987-01-01

An efficient preconditioned conjugate gradient (PCG) technique and a computational procedure are presented for the analysis of symmetric anisotropic structures. The technique is based on selecting the preconditioning matrix as the orthotropic part of the global stiffness matrix of the structure, with all the nonorthotropic terms set equal to zero. This particular choice of the preconditioning matrix results in reducing the size of the analysis model of the anisotropic structure to that of the corresponding orthotropic structure. The similarities between the proposed PCG technique and a reduction technique previously presented by the authors are identified and exploited to generate from the PCG technique direct measures for the sensitivity of the different response quantities to the nonorthotropic (anisotropic) material coefficients of the structure. The effectiveness of the PCG technique is demonstrated by means of a numerical example of an anisotropic cylindrical panel.

Aerodynamic shape optimization using preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Burgreen, Greg W.; Baysal, Oktay

1993-01-01

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

On a concurrent element-by-element preconditioned conjugate gradient algorithm for multiple load cases

NASA Technical Reports Server (NTRS)

Watson, Brian; Kamat, M. P.

1990-01-01

Element-by-element preconditioned conjugate gradient (EBE-PCG) algorithms have been advocated for use in parallel/vector processing environments as being superior to the conventional LDL(exp T) decomposition algorithm for single load cases. Although there may be some advantages in using such algorithms for a single load case, when it comes to situations involving multiple load cases, the LDL(exp T) decomposition algorithm would appear to be decidedly more cost-effective. The authors have outlined an EBE-PCG algorithm suitable for multiple load cases and compared its effectiveness to the highly efficient LDL(exp T) decomposition scheme. The proposed algorithm offers almost no advantages over the LDL(exp T) algorithm for the linear problems investigated on the Alliant FX/8. However, there may be some merit in the algorithm in solving nonlinear problems with load incrementation, but that remains to be investigated.

A fast, preconditioned conjugate gradient Toeplitz solver

NASA Technical Reports Server (NTRS)

Pan, Victor; Schrieber, Robert

1989-01-01

A simple factorization is given of an arbitrary hermitian, positive definite matrix in which the factors are well-conditioned, hermitian, and positive definite. In fact, given knowledge of the extreme eigenvalues of the original matrix A, an optimal improvement can be achieved, making the condition numbers of each of the two factors equal to the square root of the condition number of A. This technique is to applied to the solution of hermitian, positive definite Toeplitz systems. Large linear systems with hermitian, positive definite Toeplitz matrices arise in some signal processing applications. A stable fast algorithm is given for solving these systems that is based on the preconditioned conjugate gradient method. The algorithm exploits Toeplitz structure to reduce the cost of an iteration to O(n log n) by applying the fast Fourier Transform to compute matrix-vector products. Matrix factorization is used as a preconditioner.

Rapid and accurate reversed-phase high-performance liquid chromatographic determination of conjugated bile acids in human bile for routine clinical applications. Therapeutic control during gallstone dissolution therapy.

PubMed

Swobodnik, W; Klüppelberg, U; Wechsler, J G; Volz, M; Normandin, G; Ditschuneit, H

1985-05-03

This paper introduces a new method to detect the taurine and glycine conjugates of five different bile acids (cholic acid, deoxycholic acid, chenodeoxycholic acid, ursodeoxycholic acid and lithocholic acid) in human bile. Advantages of this method are sufficient separation of compounds within a short period of time and a high rate of reproducibility. Using a mobile phase gradient of acetonitrile and water, modified with tetrabutylammonium hydrogen sulphate (0.0075 mol/l), we were able to maximize the differentiation between ursodeoxycholic acid and lithocholic acid, which is of primary interest during conservative gallstone dissolution therapy. Use of this gradient reduced analysis time to less than 0.5 h. Recovery rates for this modified method ranged from 94% to 100%, and reproducibility was 98%, sufficient for routine clinical applications.

Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images

NASA Astrophysics Data System (ADS)

Hu, K.; Huang, X.; You, H.

2017-09-01

Bundle adjustment with additional parameters is identified as a critical step for precise orthoimage generation and 3D reconstruction of Dunhuang wall paintings. Due to the introduction of self-calibration parameters and quasi-planar constraints, the structure of coefficient matrix of the reduced normal equation is banded-bordered, making the solving process of bundle adjustment complex. In this paper, Conjugate Gradient Bundle Adjustment (CGBA) method is deduced by calculus of variations. A preconditioning method based on improved incomplete Cholesky factorization is adopt to reduce the condition number of coefficient matrix, as well as to accelerate the iteration rate of CGBA. Both theoretical analysis and experimental results comparison with conventional method indicate that, the proposed method can effectively conquer the ill-conditioned problem of normal equation and improve the calculation efficiency of bundle adjustment with additional parameters considerably, while maintaining the actual accuracy.

A combined finite element-boundary element formulation for solution of two-dimensional problems via CGFFT

NASA Technical Reports Server (NTRS)

Collins, Jeffery D.; Jin, Jian-Ming; Volakis, John L.

1990-01-01

A method for the computation of electromagnetic scattering from arbitrary two-dimensional bodies is presented. The method combines the finite element and boundary element methods leading to a system for solution via the conjugate gradient Fast Fourier Transform (FFT) algorithm. Two forms of boundaries aimed at reducing the storage requirement of the boundary integral are investigated. It is shown that the boundary integral becomes convolutional when a circular enclosure is chosen, resulting in reduced storage requirement when the system is solved via the conjugate gradient FFT method. The same holds for the ogival enclosure, except that some of the boundary integrals are not convolutional and must be carefully treated to maintain O(N) memory requirement. Results for several circular and ogival structures are presented and shown to be in excellent agreement with those obtained by traditional methods.

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

NASA Astrophysics Data System (ADS)

Andrea, Caliciotti; Giovanni, Fasano; Massimo, Roma

2016-10-01

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

Low-memory iterative density fitting.

PubMed

Grajciar, Lukáš

2015-07-30

A new low-memory modification of the density fitting approximation based on a combination of a continuous fast multipole method (CFMM) and a preconditioned conjugate gradient solver is presented. Iterative conjugate gradient solver uses preconditioners formed from blocks of the Coulomb metric matrix that decrease the number of iterations needed for convergence by up to one order of magnitude. The matrix-vector products needed within the iterative algorithm are calculated using CFMM, which evaluates them with the linear scaling memory requirements only. Compared with the standard density fitting implementation, up to 15-fold reduction of the memory requirements is achieved for the most efficient preconditioner at a cost of only 25% increase in computational time. The potential of the method is demonstrated by performing density functional theory calculations for zeolite fragment with 2592 atoms and 121,248 auxiliary basis functions on a single 12-core CPU workstation. © 2015 Wiley Periodicals, Inc.

Gust alleviation for a STOL transport by using elevator, spoilers, and flaps

NASA Technical Reports Server (NTRS)

Lallman, F. J.

1974-01-01

Control laws were developed to investigate methods of alleviating the response of a STOL transport to gusty air. The transport considered in the study had triple-slotted, externally blown jet flaps and a large T-tail. The control devices used were the elevator, spoilers, and flaps. A hybrid computing system was used to simulate linearized longitudinal dynamics of the aircraft and to implement a conjugate gradient optimal search algorithm. The aircraft was simulated in the low-speed approach condition only. Feedback control matrices were found which minimized the average of a quadratic functional involving passenger compartment accelerations, pitch angle and rate, flight path angle and speed variations. The optimization was performed for artificially designed gust inputs in the form of predetermined rectangular waveforms. Results were obtained for elevator, spoilers, and flaps acting singly and in combination. Additional results were obtained for unit sinusoidal gust inputs by using the gain matrices computed for the artificial test gusts. Various sensor configurations were also investigated.

Density-functional theory simulation of large quantum dots

NASA Astrophysics Data System (ADS)

Jiang, Hong; Baranger, Harold U.; Yang, Weitao

2003-10-01

Kohn-Sham spin-density functional theory provides an efficient and accurate model to study electron-electron interaction effects in quantum dots, but its application to large systems is a challenge. Here an efficient method for the simulation of quantum dots using density-function theory is developed; it includes the particle-in-the-box representation of the Kohn-Sham orbitals, an efficient conjugate-gradient method to directly minimize the total energy, a Fourier convolution approach for the calculation of the Hartree potential, and a simplified multigrid technique to accelerate the convergence. We test the methodology in a two-dimensional model system and show that numerical studies of large quantum dots with several hundred electrons become computationally affordable. In the noninteracting limit, the classical dynamics of the system we study can be continuously varied from integrable to fully chaotic. The qualitative difference in the noninteracting classical dynamics has an effect on the quantum properties of the interacting system: integrable classical dynamics leads to higher-spin states and a broader distribution of spacing between Coulomb blockade peaks.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

PubMed

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

Effects of Gradient Coil Noise and Gradient Coil Replacement on the Reproducibility of Resting State Networks.

PubMed

Bagarinao, Epifanio; Tsuzuki, Erina; Yoshida, Yukina; Ozawa, Yohei; Kuzuya, Maki; Otani, Takashi; Koyama, Shuji; Isoda, Haruo; Watanabe, Hirohisa; Maesawa, Satoshi; Naganawa, Shinji; Sobue, Gen

2018-01-01

The stability of the MRI scanner throughout a given study is critical in minimizing hardware-induced variability in the acquired imaging data set. However, MRI scanners do malfunction at times, which could generate image artifacts and would require the replacement of a major component such as its gradient coil. In this article, we examined the effect of low intensity, randomly occurring hardware-related noise due to a faulty gradient coil on brain morphometric measures derived from T1-weighted images and resting state networks (RSNs) constructed from resting state functional MRI. We also introduced a method to detect and minimize the effect of the noise associated with a faulty gradient coil. Finally, we assessed the reproducibility of these morphometric measures and RSNs before and after gradient coil replacement. Our results showed that gradient coil noise, even at relatively low intensities, could introduce a large number of voxels exhibiting spurious significant connectivity changes in several RSNs. However, censoring the affected volumes during the analysis could minimize, if not completely eliminate, these spurious connectivity changes and could lead to reproducible RSNs even after gradient coil replacement.

Effects of Gradient Coil Noise and Gradient Coil Replacement on the Reproducibility of Resting State Networks

PubMed Central

Bagarinao, Epifanio; Tsuzuki, Erina; Yoshida, Yukina; Ozawa, Yohei; Kuzuya, Maki; Otani, Takashi; Koyama, Shuji; Isoda, Haruo; Watanabe, Hirohisa; Maesawa, Satoshi; Naganawa, Shinji; Sobue, Gen

2018-01-01

The stability of the MRI scanner throughout a given study is critical in minimizing hardware-induced variability in the acquired imaging data set. However, MRI scanners do malfunction at times, which could generate image artifacts and would require the replacement of a major component such as its gradient coil. In this article, we examined the effect of low intensity, randomly occurring hardware-related noise due to a faulty gradient coil on brain morphometric measures derived from T1-weighted images and resting state networks (RSNs) constructed from resting state functional MRI. We also introduced a method to detect and minimize the effect of the noise associated with a faulty gradient coil. Finally, we assessed the reproducibility of these morphometric measures and RSNs before and after gradient coil replacement. Our results showed that gradient coil noise, even at relatively low intensities, could introduce a large number of voxels exhibiting spurious significant connectivity changes in several RSNs. However, censoring the affected volumes during the analysis could minimize, if not completely eliminate, these spurious connectivity changes and could lead to reproducible RSNs even after gradient coil replacement. PMID:29725294

Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations

NASA Technical Reports Server (NTRS)

Elman, Howard C.

1996-01-01

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

Velocity Gradient Power Functional for Brownian Dynamics.

PubMed

de Las Heras, Daniel; Schmidt, Matthias

2018-01-12

We present an explicit and simple approximation for the superadiabatic excess (over ideal gas) free power functional, admitting the study of the nonequilibrium dynamics of overdamped Brownian many-body systems. The functional depends on the local velocity gradient and is systematically obtained from treating the microscopic stress distribution as a conjugate field. The resulting superadiabatic forces are beyond dynamical density functional theory and are of a viscous nature. Their high accuracy is demonstrated by comparison to simulation results.

Velocity Gradient Power Functional for Brownian Dynamics

NASA Astrophysics Data System (ADS)

de las Heras, Daniel; Schmidt, Matthias

2018-01-01

We present an explicit and simple approximation for the superadiabatic excess (over ideal gas) free power functional, admitting the study of the nonequilibrium dynamics of overdamped Brownian many-body systems. The functional depends on the local velocity gradient and is systematically obtained from treating the microscopic stress distribution as a conjugate field. The resulting superadiabatic forces are beyond dynamical density functional theory and are of a viscous nature. Their high accuracy is demonstrated by comparison to simulation results.

Conjugate gradient and cross-correlation based least-square reverse time migration and its application

NASA Astrophysics Data System (ADS)

Sun, Xiao-Dong; Ge, Zhong-Hui; Li, Zhen-Chun

2017-09-01

Although conventional reverse time migration can be perfectly applied to structural imaging it lacks the capability of enabling detailed delineation of a lithological reservoir due to irregular illumination. To obtain reliable reflectivity of the subsurface it is necessary to solve the imaging problem using inversion. The least-square reverse time migration (LSRTM) (also known as linearized reflectivity inversion) aims to obtain relatively high-resolution amplitude preserving imaging by including the inverse of the Hessian matrix. In practice, the conjugate gradient algorithm is proven to be an efficient iterative method for enabling use of LSRTM. The velocity gradient can be derived from a cross-correlation between observed data and simulated data, making LSRTM independent of wavelet signature and thus more robust in practice. Tests on synthetic and marine data show that LSRTM has good potential for use in reservoir description and four-dimensional (4D) seismic images compared to traditional RTM and Fourier finite difference (FFD) migration. This paper investigates the first order approximation of LSRTM, which is also known as the linear Born approximation. However, for more complex geological structures a higher order approximation should be considered to improve imaging quality.

Radialenes are minimally conjugated cyclic π-systems

NASA Astrophysics Data System (ADS)

Dias, Jerry Ray

2017-03-01

Conjugation energy (CE) in benzene is larger than its aromatic stabilisation energy (ASE). A far-reaching conclusion offered by this work is that per π-electron, CE is energetically larger than aromaticity. If a diene has a doubly degenerate HOMO, then its Diels-Alder reaction will be kinetically faster than a similar diene with a nondegenerate HOMO. The topological conjugation energy (TCE) for the radialene, monocyclic, dendralene, and linear polyene series has quite different trends. Radialenes are minimally conjugated cyclic systems with the TCE/No. π-bond = 0.432 β; the members of the dendralene series approach this same value from smaller values with increasing size. With increasing size, the members of the monocyclic and linear polyene series have, respectively, decreasing and increasing TCE/No. π-bond values approaching 0.547 β. Topological resonance energy (TRE) for radialenes, dendralenes, and linear polyenes all have TRE = 0, and the TRE/π-electron for monocyclic polyenes has alternating declining values between antiaromatic (-0.3066 β, -0.07435 β, -0.03287 β, …) and aromatic (0.04543 β, 0.01594 β, 0.00807 β, …). For benzene, TRE/No. π-bond = 0.0909 β and TCE/No. π-bond = 0.576 β.

Conjugate problems of transport phenomena under quasi-steady microaccelerations in realistic spaceflight.

PubMed

Polezhaev, V I; Nikitin, S A

2009-04-01

A new model for spatial convective transport processes conjugated with the measured or calculated realistic quasi-steady microaccelerations is presented. Rotation around the mass center, including accelerated rotation, gravity gradient, and aerodynamical drag are taken into account. New results of the effect on mixing and concentration inhomogeneities of the elementary convective processes are presented. The mixing problem in spacecraft enclosures, concentration inhomogeneities due to convection induced by body forces in realistic spaceflight, and the coupling of this kind of convection with thermocapillary convection on the basis of this model are discussed.

Preclinical manufacture of anti-HER2 liposome-inserting, scFv-PEG-lipid conjugate. 2. Conjugate micelle identity, purity, stability, and potency analysis.

PubMed

Nellis, David F; Giardina, Steven L; Janini, George M; Shenoy, Shilpa R; Marks, James D; Tsai, Richard; Drummond, Daryl C; Hong, Keelung; Park, John W; Ouellette, Thomas F; Perkins, Shelley C; Kirpotin, Dmitri B

2005-01-01

Analytical methods optimized for micellar F5cys-MP-PEG(2000)-DPSE protein-lipopolymer conjugate are presented. The apparent micelle molecular weight, determined by size exclusion chromatography, ranged from 330 to 960 kDa. The F5cys antibody and conjugate melting points, determined by differential scanning calorimetry, were near 82 degrees C. Traditional methods for characterizing monodisperse protein species were inapplicable to conjugate analysis. The isoelectric point of F5cys (9.2) and the conjugate (8.9) were determined by capillary isoelectric focusing (cIEF) after addition of the zwitterionic detergent CHAPS to the buffer. Conjugate incubation with phospholipase B selectively removed DSPE lipid groups and dispersed the conjugate prior to separation by chromatographic methods. Alternatively, adding 2-propanol (29.4 vol %) and n-butanol (4.5 vol %) to buffers for salt-gradient cation exchange chromatography provided gentler, nonenzymatic dispersion, resulting in well-resolved peaks. This method was used to assess stability, identify contaminants, establish lot-to-lot comparability, and determine the average chromatographic purity (93%) for conjugate lots, described previously. The F5cys amino acid content was confirmed after conjugation. The expected conjugate avidity for immobilized HER-2/neu was measured by bimolecular interaction analysis (BIAcore). Mock therapeutic assemblies were made by conjugate insertion into preformed doxorubicin-encapsulating liposomes for antibody-directed uptake of doxorubicin by HER2-overexpressing cancer cells in vitro. Together these developed assays established that the manufacturing method as described in the first part of this study consistently produced F5cys-MP-PEG(2000)-DSPE having sufficient purity, stability, and functionality for use in preclinical toxicology investigations.

Polyamine-iron chelator conjugate.

PubMed

Bergeron, Raymond J; McManis, James S; Franklin, April M; Yao, Hua; Weimar, William R

2003-12-04

The current study demonstrates unequivocally that polyamines can serve as vectors for the intracellular delivery of the bidentate chelator 1,2-dimethyl-3-hydroxypyridin-4-one (L1). The polyamine-hydroxypyridinone conjugate 1-(12-amino-4,9-diazadodecyl)-2-methyl-3-hydroxy-4(1H)-pyridinone is assembled from spermine and 3-O-benzylmaltol. The conjugate is shown to form a 3:1 complex with Fe(III) and to be taken up by the polyamine transporter 1900-fold against a concentration gradient. The K(i) of the conjugate is 3.7 microM vs spermidine for the polyamine transporter. The conjugate is also at least 230 times more active in suppressing the growth of L1210 murine leukemia cells than is the parent ligand, decreases the activities of the polyamine biosynthetic enzymes ornithine decarboxylase and S-adenosylmethionine decarboxylase, and upregulates spermidine-spermine N (1)-acetyltransferase. However, the effect on native polyamine pools is a moderate one. These findings are in keeping with the idea that polyamines can also serve as efficient vectors for the intracellular delivery of other iron chelators.

Less is More: A Comparison of Antibody-Gold Nanoparticle Conjugates of Different Ratios.

PubMed

Byzova, Nadezhda A; Safenkova, Irina V; Slutskaya, Elvira S; Zherdev, Anatoly V; Dzantiev, Boris B

2017-11-15

This comprehensive study is related to gold nanoparticles (GNPs) conjugated with antibodies. The goal of the study is to determine the minimal concentration of antibodies for conjugate synthesis when the conjugates have high antigen-capturing activity. Two systems were studied: gold nanoparticles conjugated with monoclonal antibodies (mAb-GNP) specific to Helicobacter pylori and gold nanoparticles conjugated with polyclonal antibodies (pAb-GNP) specific to mouse immunoglobulins. Several conjugates were synthesized with different GNP-to-antibody molar ratios (from 1:1 to 1:245) through nondirectional and noncovalent immobilization on a surface of GNPs with a diameter of 25.3 ± 4.6 nm. The maximal antigen-capturing activities and equilibrium constants of the conjugates correlate with the formation of a constant hydrodynamic radius of the conjugates for mAb-GNP (GNP to antibody molar ratio 1:58) and with the stabilizing concentration by flocculation curves for pAb-GNP (GNP to antibody molar ratio 1:116). The application of the conjugates to the lateral flow immunoassay shows that the antibody concentrations used for the conjugation can be reduced (below the stabilizing concentration) without losing activity for the mAb-GNP conjugates. The findings highlight that the optimal concentration of antibodies immobilized on the surface of GNPs is not always equal to the stabilizing concentration determined by the flocculation curve.

Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

2003-02-01

Multi-conjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of AO degrees of freedom. In this paper, we develop an iterative sparse matrix implementation of minimum variance wavefront reconstruction for telescope diameters up to 32m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method, using a multigrid preconditioner incorporating a layer-oriented (block) symmetric Gauss-Seidel iterative smoothing operator. We present open-loop numerical simulation results to illustrate algorithm convergence.

Contour Detection and Completion for Inpainting and Segmentation Based on Topological Gradient and Fast Marching Algorithms

PubMed Central

Auroux, Didier; Cohen, Laurent D.; Masmoudi, Mohamed

2011-01-01

We combine in this paper the topological gradient, which is a powerful method for edge detection in image processing, and a variant of the minimal path method in order to find connected contours. The topological gradient provides a more global analysis of the image than the standard gradient and identifies the main edges of an image. Several image processing problems (e.g., inpainting and segmentation) require continuous contours. For this purpose, we consider the fast marching algorithm in order to find minimal paths in the topological gradient image. This coupled algorithm quickly provides accurate and connected contours. We present then two numerical applications, to image inpainting and segmentation, of this hybrid algorithm. PMID:22194734

Application of COMSOL to Acoustic Imaging

DTIC Science & Technology

2010-10-01

Marquardt (LM) (2 epochs), followed by Broyden, Fletcher, Goldfarb, and Shannon (BFGS) (2 epochs) followed by scaled conjugate gradient ( SCG )(100...Use Matlab’s excellent Neural Network Toolbox  Optimization techniques considered:  Scaled‏Con jugate‏ Gradient‏ (“ SCG ”)‏ - fast  One‏Step

Aircraft symmetric flight optimization. [gradient techniques for supersonic aircraft control

NASA Technical Reports Server (NTRS)

Falco, M.; Kelley, H. J.

1973-01-01

Review of the development of gradient techniques and their application to aircraft optimal performance computations in the vertical plane of flight. Results obtained using the method of gradients are presented for attitude- and throttle-control programs which extremize the fuel, range, and time performance indices subject to various trajectory and control constraints, including boundedness of engine throttle control. A penalty function treatment of state inequality constraints which generally appear in aircraft performance problems is outlined. Numerical results for maximum-range, minimum-fuel, and minimum-time climb paths for a hypothetical supersonic turbojet interceptor are presented and discussed. In addition, minimum-fuel climb paths subject to various levels of ground overpressure intensity constraint are indicated for a representative supersonic transport. A variant of the Gel'fand-Tsetlin 'method of ravines' is reviewed, and two possibilities for further development of continuous gradient processes are cited - namely, a projection version of conjugate gradients and a curvilinear search.

Missing value imputation in DNA microarrays based on conjugate gradient method.

PubMed

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

Adjustment technique without explicit formation of normal equations /conjugate gradient method/

NASA Technical Reports Server (NTRS)

Saxena, N. K.

1974-01-01

For a simultaneous adjustment of a large geodetic triangulation system, a semiiterative technique is modified and used successfully. In this semiiterative technique, known as the conjugate gradient (CG) method, original observation equations are used, and thus the explicit formation of normal equations is avoided, 'huge' computer storage space being saved in the case of triangulation systems. This method is suitable even for very poorly conditioned systems where solution is obtained only after more iterations. A detailed study of the CG method for its application to large geodetic triangulation systems was done that also considered constraint equations with observation equations. It was programmed and tested on systems as small as two unknowns and three equations up to those as large as 804 unknowns and 1397 equations. When real data (573 unknowns, 965 equations) from a 1858-km-long triangulation system were used, a solution vector accurate to four decimal places was obtained in 2.96 min after 1171 iterations (i.e., 2.0 times the number of unknowns).

A new modified conjugate gradient coefficient for solving system of linear equations

NASA Astrophysics Data System (ADS)

Hajar, N.; ‘Aini, N.; Shapiee, N.; Abidin, Z. Z.; Khadijah, W.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is an evolution of computational method in solving unconstrained optimization problems. This approach is easy to implement due to its simplicity and has been proven to be effective in solving real-life application. Although this field has received copious amount of attentions in recent years, some of the new approaches of CG algorithm cannot surpass the efficiency of the previous versions. Therefore, in this paper, a new CG coefficient which retains the sufficient descent and global convergence properties of the original CG methods is proposed. This new CG is tested on a set of test functions under exact line search. Its performance is then compared to that of some of the well-known previous CG methods based on number of iterations and CPU time. The results show that the new CG algorithm has the best efficiency amongst all the methods tested. This paper also includes an application of the new CG algorithm for solving large system of linear equations

Development and applications of algorithms for calculating the transonic flow about harmonically oscillating wings

NASA Technical Reports Server (NTRS)

Ehlers, F. E.; Weatherill, W. H.; Yip, E. L.

1984-01-01

A finite difference method to solve the unsteady transonic flow about harmonically oscillating wings was investigated. The procedure is based on separating the velocity potential into steady and unsteady parts and linearizing the resulting unsteady differential equation for small disturbances. The differential equation for the unsteady velocity potential is linear with spatially varying coefficients and with the time variable eliminated by assuming harmonic motion. An alternating direction implicit procedure was investigated, and a pilot program was developed for both two and three dimensional wings. This program provides a relatively efficient relaxation solution without previously encountered solution instability problems. Pressure distributions for two rectangular wings are calculated. Conjugate gradient techniques were developed for the asymmetric, indefinite problem. The conjugate gradient procedure is evaluated for applications to the unsteady transonic problem. Different equations for the alternating direction procedure are derived using a coordinate transformation for swept and tapered wing planforms. Pressure distributions for swept, untaped wings of vanishing thickness are correlated with linear results for sweep angles up to 45 degrees.

Cosmic Microwave Background Mapmaking with a Messenger Field

NASA Astrophysics Data System (ADS)

Huffenberger, Kevin M.; Næss, Sigurd K.

2018-01-01

We apply a messenger field method to solve the linear minimum-variance mapmaking equation in the context of Cosmic Microwave Background (CMB) observations. In simulations, the method produces sky maps that converge significantly faster than those from a conjugate gradient descent algorithm with a diagonal preconditioner, even though the computational cost per iteration is similar. The messenger method recovers large scales in the map better than conjugate gradient descent, and yields a lower overall χ2. In the single, pencil beam approximation, each iteration of the messenger mapmaking procedure produces an unbiased map, and the iterations become more optimal as they proceed. A variant of the method can handle differential data or perform deconvolution mapmaking. The messenger method requires no preconditioner, but a high-quality solution needs a cooling parameter to control the convergence. We study the convergence properties of this new method and discuss how the algorithm is feasible for the large data sets of current and future CMB experiments.

Generalized conjugate-gradient methods for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing

1991-01-01

A generalized conjugate-gradient method is used to solve the two-dimensional, compressible Navier-Stokes equations of fluid flow. The equations are discretized with an implicit, upwind finite-volume formulation. Preconditioning techniques are incorporated into the new solver to accelerate convergence of the overall iterative method. The superiority of the new solver is demonstrated by comparisons with a conventional line Gauss-Siedel Relaxation solver. Computational test results for transonic flow (trailing edge flow in a transonic turbine cascade) and hypersonic flow (M = 6.0 shock-on-shock phenoena on a cylindrical leading edge) are presented. When applied to the transonic cascade case, the new solver is 4.4 times faster in terms of number of iterations and 3.1 times faster in terms of CPU time than the Relaxation solver. For the hypersonic shock case, the new solver is 3.0 times faster in terms of number of iterations and 2.2 times faster in terms of CPU time than the Relaxation solver.

A combined finite element-boundary integral formulation for solution of two-dimensional scattering problems via CGFFT. [Conjugate Gradient Fast Fourier Transformation

NASA Technical Reports Server (NTRS)

Collins, Jeffery D.; Volakis, John L.; Jin, Jian-Ming

1990-01-01

A new technique is presented for computing the scattering by 2-D structures of arbitrary composition. The proposed solution approach combines the usual finite element method with the boundary-integral equation to formulate a discrete system. This is subsequently solved via the conjugate gradient (CG) algorithm. A particular characteristic of the method is the use of rectangular boundaries to enclose the scatterer. Several of the resulting boundary integrals are therefore convolutions and may be evaluated via the fast Fourier transform (FFT) in the implementation of the CG algorithm. The solution approach offers the principal advantage of having O(N) memory demand and employs a 1-D FFT versus a 2-D FFT as required with a traditional implementation of the CGFFT algorithm. The speed of the proposed solution method is compared with that of the traditional CGFFT algorithm, and results for rectangular bodies are given and shown to be in excellent agreement with the moment method.

The intrinsic antimicrobial activity of citric acid-coated manganese ferrite nanoparticles is enhanced after conjugation with the antifungal peptide Cm-p5

PubMed Central

Lopez-Abarrategui, Carlos; Figueroa-Espi, Viviana; Lugo-Alvarez, Maria B; Pereira, Caroline D; Garay, Hilda; Barbosa, João ARG; Falcão, Rosana; Jiménez-Hernández, Linnavel; Estévez-Hernández, Osvaldo; Reguera, Edilso; Franco, Octavio L; Dias, Simoni C; Otero-Gonzalez, Anselmo J

2016-01-01

Diseases caused by bacterial and fungal pathogens are among the major health problems in the world. Newer antimicrobial therapies based on novel molecules urgently need to be developed, and this includes the antimicrobial peptides. In spite of the potential of antimicrobial peptides, very few of them were able to be successfully developed into therapeutics. The major problems they present are molecule stability, toxicity in host cells, and production costs. A novel strategy to overcome these obstacles is conjugation to nanomaterial preparations. The antimicrobial activity of different types of nanoparticles has been previously demonstrated. Specifically, magnetic nanoparticles have been widely studied in biomedicine due to their physicochemical properties. The citric acid-modified manganese ferrite nanoparticles used in this study were characterized by high-resolution transmission electron microscopy, which confirmed the formation of nanocrystals of approximately 5 nm diameter. These nanoparticles were able to inhibit Candida albicans growth in vitro. The minimal inhibitory concentration was 250 µg/mL. However, the nanoparticles were not capable of inhibiting Gram-negative bacteria (Escherichia coli) or Gram-positive bacteria (Staphylococcus aureus). Finally, an antifungal peptide (Cm-p5) from the sea animal Cenchritis muricatus (Gastropoda: Littorinidae) was conjugated to the modified manganese ferrite nanoparticles. The antifungal activity of the conjugated nanoparticles was higher than their bulk counterparts, showing a minimal inhibitory concentration of 100 µg/mL. This conjugate proved to be nontoxic to a macrophage cell line at concentrations that showed antimicrobial activity. PMID:27563243

Characterisation of minimal-span plane Couette turbulence with pressure gradients

NASA Astrophysics Data System (ADS)

Sekimoto, Atsushi; Atkinson, Callum; Soria, Julio

2018-04-01

The turbulence statistics and dynamics in the spanwise-minimal plane Couette flow with pressure gradients, so-called, Couette-Poiseuille (C-P) flow, are investigated using direct numerical simulation. The large-scale motion is limited in the spanwise box dimension as in the minimal-span channel turbulence of Flores & Jiménez (Phys. Fluids, vol. 22, 2010, 071704). The effect of the top wall, where normal pressure-driven Poiseuille flow is realised, is distinguished from the events on the bottom wall, where the pressure gradient results in mild or almost-zero wall-shear stress. A proper scaling of turbulence statistics in minimal-span C-P flows is presented. Also the ‘shear-less’ wall-bounded turbulence, where the Corrsin shear parameter is very weak compared to normal wall-bounded turbulence, represents local separation, which is also observed as spanwise streaks of reversed flow in full-size plane C-P turbulence. The local separation is a multi-scale event, which grows up to the order of the channel height even in the minimal-span geometry.

Vacuolar transport of the glutathione conjugate of trans-cinnamic acid.

PubMed

Walczak, H A; Dean, J V

2000-02-01

Red beet (Beta vulgaris L.) tonoplast membrane vesicles and [14C]trans-cinnamic acid-glutatione were used to study the vacuolar transport of phynylpropanoid-glutathione conjugates which are formed in peroxidase-mediated reactions. It was determined that the uptake of [14C]trans-cinnamic acid-glutathione into the tonoplast membrane vesicles was MgATP dependent and was 10-fold faster than the uptake of non-conjugated [14C]trans-cinnamic acid. Uptake of the conjugate in the presence of MgATP was not dependent on a trans-tonoblast H+-electrochemical gradient, because uptake was not affected by the addition of NH4Cl (1 mM; 0% inhibition) and was only slightly affected by gramicidin-D (5 microM; 14% inhibition). Uptake of the conjugate was inhibited 92% by the addition of vanadate (1 mM) and 71% by the addition of the model substrate S-(2,4-dinitrophenyl) glutathione (500 microM). Uptake did not occur when a nonhydrolyzable analog of ATP was used in place of MgATP. The calculated Km and Vmax values for uptake were 142 microM amd 5.95 nmol mg(-1) min(-1), respectively. Based on these results, phenylpropanoid-glutation conjugates formed in peroxidase-mediated reactions appear to be transported into the vacuole by the glutathione S-conjugate pump(s) located in the tonoplast membrane.

Template-Based 3D Reconstruction of Non-rigid Deformable Object from Monocular Video

NASA Astrophysics Data System (ADS)

Liu, Yang; Peng, Xiaodong; Zhou, Wugen; Liu, Bo; Gerndt, Andreas

2018-06-01

In this paper, we propose a template-based 3D surface reconstruction system of non-rigid deformable objects from monocular video sequence. Firstly, we generate a semi-dense template of the target object with structure from motion method using a subsequence video. This video can be captured by rigid moving camera orienting the static target object or by a static camera observing the rigid moving target object. Then, with the reference template mesh as input and based on the framework of classical template-based methods, we solve an energy minimization problem to get the correspondence between the template and every frame to get the time-varying mesh to present the deformation of objects. The energy terms combine photometric cost, temporal and spatial smoothness cost as well as as-rigid-as-possible cost which can enable elastic deformation. In this paper, an easy and controllable solution to generate the semi-dense template for complex objects is presented. Besides, we use an effective iterative Schur based linear solver for the energy minimization problem. The experimental evaluation presents qualitative deformation objects reconstruction results with real sequences. Compare against the results with other templates as input, the reconstructions based on our template have more accurate and detailed results for certain regions. The experimental results show that the linear solver we used performs better efficiency compared to traditional conjugate gradient based solver.

Efficiency of unconstrained minimization techniques in nonlinear analysis

NASA Technical Reports Server (NTRS)

Kamat, M. P.; Knight, N. F., Jr.

1978-01-01

Unconstrained minimization algorithms have been critically evaluated for their effectiveness in solving structural problems involving geometric and material nonlinearities. The algorithms have been categorized as being zeroth, first, or second order depending upon the highest derivative of the function required by the algorithm. The sensitivity of these algorithms to the accuracy of derivatives clearly suggests using analytically derived gradients instead of finite difference approximations. The use of analytic gradients results in better control of the number of minimizations required for convergence to the exact solution.

2.5D complex resistivity modeling and inversion using unstructured grids

NASA Astrophysics Data System (ADS)

Xu, Kaijun; Sun, Jie

2016-04-01

The characteristic of complex resistivity on rock and ore has been recognized by people for a long time. Generally we have used the Cole-Cole Model(CCM) to describe complex resistivity. It has been proved that the electrical anomaly of geologic body can be quantitative estimated by CCM parameters such as direct resistivity(ρ0), chargeability(m), time constant(τ) and frequency dependence(c). Thus it is very important to obtain the complex parameters of geologic body. It is difficult to approximate complex structures and terrain using traditional rectangular grid. In order to enhance the numerical accuracy and rationality of modeling and inversion, we use an adaptive finite-element algorithm for forward modeling of the frequency-domain 2.5D complex resistivity and implement the conjugate gradient algorithm in the inversion of 2.5D complex resistivity. An adaptive finite element method is applied for solving the 2.5D complex resistivity forward modeling of horizontal electric dipole source. First of all, the CCM is introduced into the Maxwell's equations to calculate the complex resistivity electromagnetic fields. Next, the pseudo delta function is used to distribute electric dipole source. Then the electromagnetic fields can be expressed in terms of the primary fields caused by layered structure and the secondary fields caused by inhomogeneities anomalous conductivity. At last, we calculated the electromagnetic fields response of complex geoelectric structures such as anticline, syncline, fault. The modeling results show that adaptive finite-element methods can automatically improve mesh generation and simulate complex geoelectric models using unstructured grids. The 2.5D complex resistivity invertion is implemented based the conjugate gradient algorithm.The conjugate gradient algorithm doesn't need to compute the sensitivity matrix but directly computes the sensitivity matrix or its transpose multiplying vector. In addition, the inversion target zones are segmented with fine grids and the background zones are segmented with big grid, the method can reduce the grid amounts of inversion, it is very helpful to improve the computational efficiency. The inversion results verify the validity and stability of conjugate gradient inversion algorithm. The results of theoretical calculation indicate that the modeling and inversion of 2.5D complex resistivity using unstructured grids are feasible. Using unstructured grids can improve the accuracy of modeling, but the large number of grids inversion is extremely time-consuming, so the parallel computation for the inversion is necessary. Acknowledgments: We thank to the support of the National Natural Science Foundation of China(41304094).

Biosensors from conjugated polyelectrolyte complexes

PubMed Central

Wang, Deli; Gong, Xiong; Heeger, Peter S.; Rininsland, Frauke; Bazan, Guillermo C.; Heeger, Alan J.

2002-01-01

A charge neutral complex (CNC) was formed in aqueous solution by combining an orange light emitting anionic conjugated polyelectrolyte and a saturated cationic polyelectrolyte at a 1:1 ratio (per repeat unit). Photoluminescence (PL) from the CNC can be quenched by both the negatively charged dinitrophenol (DNP) derivative, (DNP-BS−), and positively charged methyl viologen (MV2+). Use of the CNC minimizes nonspecific interactions (which modify the PL) between conjugated polyelectrolytes and biopolymers. Quenching of the PL from the CNC by the DNP derivative and specific unquenching on addition of anti-DNP antibody (anti-DNP IgG) were observed. Thus, biosensing of the anti-DNP IgG was demonstrated. PMID:11756675

Comparison of some optimal control methods for the design of turbine blades

NASA Technical Reports Server (NTRS)

Desilva, B. M. E.; Grant, G. N. C.

1977-01-01

This paper attempts a comparative study of some numerical methods for the optimal control design of turbine blades whose vibration characteristics are approximated by Timoshenko beam idealizations with shear and incorporating simple boundary conditions. The blade was synthesized using the following methods: (1) conjugate gradient minimization of the system Hamiltonian in function space incorporating penalty function transformations, (2) projection operator methods in a function space which includes the frequencies of vibration and the control function, (3) epsilon-technique penalty function transformation resulting in a highly nonlinear programming problem, (4) finite difference discretization of the state equations again resulting in a nonlinear program, (5) second variation methods with complex state differential equations to include damping effects resulting in systems of inhomogeneous matrix Riccatti equations some of which are stiff, (6) quasi-linear methods based on iterative linearization of the state and adjoint equation. The paper includes a discussion of some substantial computational difficulties encountered in the implementation of these techniques together with a resume of work presently in progress using a differential dynamic programming approach.

Marine Controlled-Source Electromagnetic 2D Inversion for synthetic models.

NASA Astrophysics Data System (ADS)

Liu, Y.; Li, Y.

2016-12-01

We present a 2D inverse algorithm for frequency domain marine controlled-source electromagnetic (CSEM) data, which is based on the regularized Gauss-Newton approach. As a forward solver, our parallel adaptive finite element forward modeling program is employed. It is a self-adaptive, goal-oriented grid refinement algorithm in which a finite element analysis is performed on a sequence of refined meshes. The mesh refinement process is guided by a dual error estimate weighting to bias refinement towards elements that affect the solution at the EM receiver locations. With the use of the direct solver (MUMPS), we can effectively compute the electromagnetic fields for multi-sources and parametric sensitivities. We also implement the parallel data domain decomposition approach of Key and Ovall (2011), with the goal of being able to compute accurate responses in parallel for complicated models and a full suite of data parameters typical of offshore CSEM surveys. All minimizations are carried out by using the Gauss-Newton algorithm and model perturbations at each iteration step are obtained by using the Inexact Conjugate Gradient iteration method. Synthetic test inversions are presented.

Generating multiplex gradients of biomolecules for controlling cellular adhesion in parallel microfluidic channels.

PubMed

Didar, Tohid Fatanat; Tabrizian, Maryam

2012-11-07

Here we present a microfluidic platform to generate multiplex gradients of biomolecules within parallel microfluidic channels, in which a range of multiplex concentration gradients with different profile shapes are simultaneously produced. Nonlinear polynomial gradients were also generated using this device. The gradient generation principle is based on implementing parrallel channels with each providing a different hydrodynamic resistance. The generated biomolecule gradients were then covalently functionalized onto the microchannel surfaces. Surface gradients along the channel width were a result of covalent attachments of biomolecules to the surface, which remained functional under high shear stresses (50 dyn/cm(2)). An IgG antibody conjugated to three different fluorescence dyes (FITC, Cy5 and Cy3) was used to demonstrate the resulting multiplex concentration gradients of biomolecules. The device enabled generation of gradients with up to three different biomolecules in each channel with varying concentration profiles. We were also able to produce 2-dimensional gradients in which biomolecules were distributed along the length and width of the channel. To demonstrate the applicability of the developed design, three different multiplex concentration gradients of REDV and KRSR peptides were patterned along the width of three parallel channels and adhesion of primary human umbilical vein endothelial cell (HUVEC) in each channel was subsequently investigated using a single chip.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, H.

2017-12-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, some studies suggested possible links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their mechanisms, we need an accurate 3D crustal wavespeed model for North Texas and Oklahoma. Considering the uneven distribution of earthquakes in this region, seismic tomography with local earthquake records have difficulties to achieve good illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. 25 preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model M25 correlates with geological units in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front. In addition, these seismic anomalies correlate with gravity and magnetic observations. This new model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location and moment tensor solutions, which are important for investigating potential relations between seismicity and unconventional oil and gas exploration.

On the Convergence Analysis of the Optimized Gradient Method.

PubMed

Kim, Donghwan; Fessler, Jeffrey A

2017-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov's fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization.

On the Convergence Analysis of the Optimized Gradient Method

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2016-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov’s fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization. PMID:28461707

Inducing cell death in vitro in cancer cells by targeted delivery of cytochrome c via a transferrin conjugate

PubMed Central

Delgado, Yamixa; Sharma, Rohit Kumar; Sharma, Shweta; Guzmán, Solimar Liz Ponce De León; Tinoco, Arthur D.; Griebenow, Kai

2018-01-01

One of the major drawbacks of many of the currently used cancer drugs are off-target effects. Targeted delivery is one method to minimize such unwanted and detrimental events. To actively target lung cancer cells, we have developed a conjugate of the apoptosis inducing protein cytochrome c with transferrin because the transferrin receptor is overexpressed by many rapidly dividing cancer cells. Cytochrome c and transferrin were cross-linked with a redox sensitive disulfide bond for the intra-cellular release of the protein upon endocytosis by the transferrin receptor. Confocal results demonstrated the cellular uptake of the cytochrome c-transferrin conjugate by transferrin receptor overexpressing A549 lung cancer cells. Localization studies further validated that this conjugate escaped the endosome. Additionally, an in vitro assay showed that the conjugate could induce apoptosis by activating caspase-3. The neo-conjugate not only maintained an IC50 value similar to the well known drug cisplatin (50 μM) in A549 cancer cells but also was nontoxic to the normal lung (MRC5) cells. Our neo-conjugate holds promise for future development to target cancers with enhanced transferrin receptor expression. PMID:29649293

Asymmetry and polarity of the South Atlantic conjugated margins related to the presence of cratons: a numerical study

NASA Astrophysics Data System (ADS)

Andrés-Martínez, Miguel; Pérez-Gussinyé, Marta; de Monserrat Navarro, Albert; Morgan, Jason P.

2015-04-01

Tectonic asymmetry of conjugated passive margins, where one margin is much narrower than the conjugate one, is commonly observed at many passive margins world-wide. Conjugate margin asymmetry has been suggested to be a consequence of lateral changes in rheology, composition, temperature gradient or geometries of the crust and lithosphere. Here we use the South Atlantic margins (from Camamu/Gabon to North Santos/South Kwanza) as a natural laboratory to understand conjugate margin asymmetry. Along this margin sector the polarity of the asymmetry changes. To the North, the Brazilian margin developed in the strong Sao Francisco craton, and this constitutes the narrow side of the conjugate pair. To the South, the Brazilian margin developed in the Ribeira fold belt, and the margin is wide. The opposite is true for the African side. We have thus numerically analysed how the relative distance between the initial location of extension and the craton influences the symmetry/asymmetry and polarity of the conjugate margin system. Our numerical model is 2D visco-elasto-plastic and has a free surface, strain weakening and shear heating. The initial set-up includes a cratonic domain, a mobile belt and a transition area between both. We have run tests with different rheologies, thickness of the lithosphere, and weak seeds at different distances from the craton. Results show asymmetric conjugated margins, where the narrower margin is generally the closest to the craton. Our models also allow us to study how the polarity is controlled by the distance between the initial weakness and the craton, and help to understand how the presence of cratonic domains affects the final architecture of the conjugated margins.

α-Methylprednisolone conjugated cyclodextrin polymer-based nanoparticles for rheumatoid arthritis therapy

PubMed Central

Hwang, Jungyeon; Rodgers, Kathleen; Oliver, James C; Schluep, Thomas

2008-01-01

A glycinate derivative of α-methylprednisolone (MP) was prepared and conjugated to a linear cyclodextrin polymer (CDP) with a loading of 12.4% w/w. The polymer conjugate (CDP-MP) self-assembled into nanoparticles with a size of 27 nm. Release kinetics of MP from the polymer conjugate showed a half-life (t1/2) of 50 h in phosphate buffer solution (PBS) and 19 h in human plasma. In vitro, the proliferation of human lymphocytes was suppressed to a similar extent but with a delayed effect when CDP-MP was compared with free MP. In vivo, CDP-MP was administered intravenously to mice with collagen-induced arthritis and compared with free MP. CDP-MP was administered weekly for six weeks (0.07, 0.7, and 7 mg/kg/week) and MP was administered daily for six weeks (0.01, 0.1, and 1 mg/kg/day). Body weight changes were minimal in all animals. After 28 days, a significant decrease in arthritis score was observed in animals treated weekly with an intermediate or high dose of CDP-MP. Additionally, dorsoplantar swelling was reduced to baseline in animals treated with CDP-MP at the intermediate and high dose level. Histological evaluation showed a reduction in synovitis, pannus formation and disruption of architecture at the highest dose level of CDP-MP. MP administered daily at equivalent cumulative doses showed minimal efficacy in this model. This study demonstrates that conjugation of MP to a cyclodextrin-polymer may improve its efficacy, leading to lower doses and less frequent administration for a safer and more convenient management of rheumatoid arthritis. PMID:18990945

A finite element conjugate gradient FFT method for scattering

NASA Technical Reports Server (NTRS)

Collins, Jeffery D.; Ross, Dan; Jin, J.-M.; Chatterjee, A.; Volakis, John L.

1991-01-01

Validated results are presented for the new 3D body of revolution finite element boundary integral code. A Fourier series expansion of the vector electric and mangnetic fields is employed to reduce the dimensionality of the system, and the exact boundary condition is employed to terminate the finite element mesh. The mesh termination boundary is chosen such that is leads to convolutional boundary operatores of low O(n) memory demand. Improvements of this code are discussed along with the proposed formulation for a full 3D implementation of the finite element boundary integral method in conjunction with a conjugate gradiant fast Fourier transformation (CGFFT) solution.

Exciton intrachain transport induced by interchain packing configurations in conjugated polymers.

PubMed

Meng, Ruixuan; Gao, Kun; Zhang, Gaiyan; Han, Shixuan; Yang, Fujiang; Li, Yuan; Xie, Shijie

2015-07-28

Based on a tight binding model combined with a nonadiabatic dynamics approach, we theoretically investigate the exciton intrachain transport in conjugated polymers with different interchain packing configurations. We construct two different interchain packing configurations, i.e. linear and exponential forms, and simulate the dynamical processes of the exciton transport in these systems. We find that, in both cases, there exists a distribution of driving force for exciton transport, which stems from the gradient of the exciton creation energy along the chains. This finding enriches the picture of exciton transport in polymers and provides a new idea to improve the exciton transport length in polymeric photovoltaic devices.

Directed Self-Assembly of Gradient Concentric Carbon Nanotube Rings

NASA Astrophysics Data System (ADS)

Hong, Suck Won; Jeong, Wonje; Ko, Hyunhyub; Tsukruk, Vladimir; Kessler, Michael; Lin, Zhiqun

2008-03-01

Hundreds of gradient concentric rings of linear conjugated polymer, (poly[2-methoxy-5-(2-ethylhexyloxy)-1,4- phenylenevinylene], i.e., MEH-PPV) with remarkable regularity over large areas were produced by controlled, repetitive ``stick- slip'' motions of the contact line in a confined geometry consisting of a sphere on a flat substrate (i.e., sphere-on-flat geometry). Subsequently, MEH-PPV rings exploited as template to direct the formation of gradient concentric rings of multiwalled carbon nanotubes (MWNTs) with controlled density. This method is simple, cost effective, and robust, combining two consecutive self-assembly processes, namely, evaporation-induced self- assembly of polymers in a sphere-on-flat geometry, followed by subsequent directed self-assembly of MWNTs on the polymer- templated surfaces.

First production of fluorescent anti-ribonucleoproteins conjugate for diagnostic of rabies in Brazil.

PubMed

Medeiros Caporale, Graciane Maria; Rodrigues da Silva, Andréa de Cássia; Peixoto, Zélia Maria Pinheiro; Chaves, Luciana Botelho; Carrieri, Maria Luiza; Vassão, Ruth Camargo

2009-01-01

The laboratory tests recommended by the World Health Organization for detection of rabies virus and evaluation of specific antibodies are performed with fluorescent antibodies against the virus, the ribonucleoproteins (RNPs), or by monoclonal antibodies. In this study, we purified the rabies virus RNPs for the production of a conjugate presenting sensibility and specificity compatible with commercial reagents. The method employed for the purification of RNPs was ultracentrifugation in cesium chloride gradient, the obtained product being used for immunizing rabbits, from which the hyperimmune sera were collected. The serum used for conjugate production was the one presenting the highest titer (1/2,560) when tested by indirect immunofluorescence. The antibodies were purified by anion exchange chromatography (QAE-Sephadex A-50),conjugated to fluorescein isothiocyanate and separated by gel filtration (Sephadex G-50). The resulting conjugate presented titers of 1/400 and 1/500 when assayed by direct immunofluorescence (DIF) and simplified fluorescence inhibition microtest, respectively. Sensibility and specificity tests were performed by DIF in 100 central nervous system samples of different animal species, presenting 100% matches when compared with the commercial reagent used as standard, independent of the conservation state of the samples. The quality reached by our conjugate will enable the standardization of this reagent for use by the laboratories performing diagnosis of rabies in Brazil, contributing to the intensification of the epidemiological vigilance and research on this disease. Copyright 2009 Wiley-Liss, Inc.

Wavelet methods in multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Helin, T.; Yudytskiy, M.

2013-08-01

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory.

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

Sparse matrix methods based on orthogonality and conjugacy

NASA Technical Reports Server (NTRS)

Lawson, C. L.

1973-01-01

A matrix having a high percentage of zero elements is called spares. In the solution of systems of linear equations or linear least squares problems involving large sparse matrices, significant saving of computer cost can be achieved by taking advantage of the sparsity. The conjugate gradient algorithm and a set of related algorithms are described.

An Introduction to the Conjugate Gradient Method that Even an Idiot Can Understand

DTIC Science & Technology

1994-03-07

to Omar Ghattas, who taught me much of what I know about numerical methods, and provided me with extensive comments on the first draft of this article...Dongarra, Victor Eijkhout, Roldan Pozo, Charles Romine, and Henk van der Vorst, Templates for the solution of linear systems: Building blocks for iterative

Sensitivity calculations for iteratively solved problems

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1985-01-01

The calculation of sensitivity derivatives of solutions of iteratively solved systems of algebraic equations is investigated. A modified finite difference procedure is presented which improves the accuracy of the calculated derivatives. The procedure is demonstrated for a simple algebraic example as well as an element-by-element preconditioned conjugate gradient iterative solution technique applied to truss examples.

Self-calibrated multiple-echo acquisition with radial trajectories using the conjugate gradient method (SMART-CG).

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Bydder, Mark; Block, Walter F

2011-04-01

To remove phase inconsistencies between multiple echoes, an algorithm using a radial acquisition to provide inherent phase and magnitude information for self correction was developed. The information also allows simultaneous support for parallel imaging for multiple coil acquisitions. Without a separate field map acquisition, a phase estimate from each echo in multiple echo train was generated. When using a multiple channel coil, magnitude and phase estimates from each echo provide in vivo coil sensitivities. An algorithm based on the conjugate gradient method uses these estimates to simultaneously remove phase inconsistencies between echoes, and in the case of multiple coil acquisition, simultaneously provides parallel imaging benefits. The algorithm is demonstrated on single channel, multiple channel, and undersampled data. Substantial image quality improvements were demonstrated. Signal dropouts were completely removed and undersampling artifacts were well suppressed. The suggested algorithm is able to remove phase cancellation and undersampling artifacts simultaneously and to improve image quality of multiecho radial imaging, the important technique for fast three-dimensional MRI data acquisition. Copyright © 2011 Wiley-Liss, Inc.

Self-calibrated Multiple-echo Acquisition with Radial Trajectories using the Conjugate Gradient Method (SMART-CG)

PubMed Central

Jung, Youngkyoo; Samsonov, Alexey A; Bydder, Mark; Block, Walter F.

2011-01-01

Purpose To remove phase inconsistencies between multiple echoes, an algorithm using a radial acquisition to provide inherent phase and magnitude information for self correction was developed. The information also allows simultaneous support for parallel imaging for multiple coil acquisitions. Materials and Methods Without a separate field map acquisition, a phase estimate from each echo in multiple echo train was generated. When using a multiple channel coil, magnitude and phase estimates from each echo provide in-vivo coil sensitivities. An algorithm based on the conjugate gradient method uses these estimates to simultaneously remove phase inconsistencies between echoes, and in the case of multiple coil acquisition, simultaneously provides parallel imaging benefits. The algorithm is demonstrated on single channel, multiple channel, and undersampled data. Results Substantial image quality improvements were demonstrated. Signal dropouts were completely removed and undersampling artifacts were well suppressed. Conclusion The suggested algorithm is able to remove phase cancellation and undersampling artifacts simultaneously and to improve image quality of multiecho radial imaging, the important technique for fast 3D MRI data acquisition. PMID:21448967

Two-step reconstruction method using global optimization and conjugate gradient for ultrasound-guided diffuse optical tomography.

PubMed

Tavakoli, Behnoosh; Zhu, Quing

2013-01-01

Ultrasound-guided diffuse optical tomography (DOT) is a promising method for characterizing malignant and benign lesions in the female breast. We introduce a new two-step algorithm for DOT inversion in which the optical parameters are estimated with the global optimization method, genetic algorithm. The estimation result is applied as an initial guess to the conjugate gradient (CG) optimization method to obtain the absorption and scattering distributions simultaneously. Simulations and phantom experiments have shown that the maximum absorption and reduced scattering coefficients are reconstructed with less than 10% and 25% errors, respectively. This is in contrast with the CG method alone, which generates about 20% error for the absorption coefficient and does not accurately recover the scattering distribution. A new measure of scattering contrast has been introduced to characterize benign and malignant breast lesions. The results of 16 clinical cases reconstructed with the two-step method demonstrates that, on average, the absorption coefficient and scattering contrast of malignant lesions are about 1.8 and 3.32 times higher than the benign cases, respectively.

A modified three-term PRP conjugate gradient algorithm for optimization models.

PubMed

Wu, Yanlin

2017-01-01

The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization, especially for large-scale problems, because of its low memory requirement and simplicity. Zhang et al. (IMA J. Numer. Anal. 26:629-649, 2006) firstly propose a three-term CG algorithm based on the well known Polak-Ribière-Polyak (PRP) formula for unconstrained optimization, where their method has the sufficient descent property without any line search technique. They proved the global convergence of the Armijo line search but this fails for the Wolfe line search technique. Inspired by their method, we will make a further study and give a modified three-term PRP CG algorithm. The presented method possesses the following features: (1) The sufficient descent property also holds without any line search technique; (2) the trust region property of the search direction is automatically satisfied; (3) the steplengh is bounded from below; (4) the global convergence will be established under the Wolfe line search. Numerical results show that the new algorithm is more effective than that of the normal method.

A fast mass spring model solver for high-resolution elastic objects

NASA Astrophysics Data System (ADS)

Zheng, Mianlun; Yuan, Zhiyong; Zhu, Weixu; Zhang, Guian

2017-03-01

Real-time simulation of elastic objects is of great importance for computer graphics and virtual reality applications. The fast mass spring model solver can achieve visually realistic simulation in an efficient way. Unfortunately, this method suffers from resolution limitations and lack of mechanical realism for a surface geometry model, which greatly restricts its application. To tackle these problems, in this paper we propose a fast mass spring model solver for high-resolution elastic objects. First, we project the complex surface geometry model into a set of uniform grid cells as cages through *cages mean value coordinate method to reflect its internal structure and mechanics properties. Then, we replace the original Cholesky decomposition method in the fast mass spring model solver with a conjugate gradient method, which can make the fast mass spring model solver more efficient for detailed surface geometry models. Finally, we propose a graphics processing unit accelerated parallel algorithm for the conjugate gradient method. Experimental results show that our method can realize efficient deformation simulation of 3D elastic objects with visual reality and physical fidelity, which has a great potential for applications in computer animation.

Maxwell Strata and Cut Locus in the Sub-Riemannian Problem on the Engel Group

NASA Astrophysics Data System (ADS)

Ardentov, Andrei A.; Sachkov, Yuri L.

2017-12-01

We consider the nilpotent left-invariant sub-Riemannian structure on the Engel group. This structure gives a fundamental local approximation of a generic rank 2 sub-Riemannian structure on a 4-manifold near a generic point (in particular, of the kinematic models of a car with a trailer). On the other hand, this is the simplest sub-Riemannian structure of step three. We describe the global structure of the cut locus (the set of points where geodesics lose their global optimality), the Maxwell set (the set of points that admit more than one minimizer), and the intersection of the cut locus with the caustic (the set of conjugate points along all geodesics). The group of symmetries of the cut locus is described: it is generated by a one-parameter group of dilations R+ and a discrete group of reflections Z2 × Z2 × Z2. The cut locus admits a stratification with 6 three-dimensional strata, 12 two-dimensional strata, and 2 one-dimensional strata. Three-dimensional strata of the cut locus are Maxwell strata of multiplicity 2 (for each point there are 2 minimizers). Two-dimensional strata of the cut locus consist of conjugate points. Finally, one-dimensional strata are Maxwell strata of infinite multiplicity, they consist of conjugate points as well. Projections of sub-Riemannian geodesics to the 2-dimensional plane of the distribution are Euler elasticae. For each point of the cut locus, we describe the Euler elasticae corresponding to minimizers coming to this point. Finally, we describe the structure of the optimal synthesis, i. e., the set of minimizers for each terminal point in the Engel group.

Bacteroides fragilis mobilizable transposon Tn5520 requires a 71 base pair origin of transfer sequence and a single mobilization protein for relaxosome formation during conjugation.

PubMed

Vedantam, Gayatri; Knopf, Sarah; Hecht, David W

2006-01-01

Tn5520 is the smallest known bacterial mobilizable transposon and was isolated from an antibiotic resistant Bacteroides fragilis clinical isolate. When a conjugation apparatus is provided in trans, Tn5520 is mobilized (transferred) efficiently within, and from, both Bacteroides spp. and Escherichia coli. Only two genes are present on Tn5520; one encodes an integrase, and the other a multifunctional mobilization (Mob) protein BmpH. BmpH is essential for Tn5520 mobility. The focus of this study was to identify the Tn5520 origin of conjugative transfer (oriT) and to study BmpH-oriT binding. We delimited the functional Tn5520 oriT to a 71 bp sequence upstream of the bmpH gene. A plasmid vector harbouring this minimal 71 bp oriT was mobilized at the same frequency as that of intact Tn5520. The minimal oriT contains one 17 bp inverted repeat (IR) sequence. We constructed and tested multiple IR mutants and showed that the IR was essential in its entirety for mobilization. A nick site sequence (5'-GCTAC-3') was also identified within the minimal oriT; this sequence resembled nick sites found in plasmids of Gram positive origin. We further showed that mutation of a highly conserved GC dinucleotide in the nick site sequence completely abolished mobilization. We also purified BmpH and showed that it specifically bound a Tn5520 oriT fragment in electrophoretic mobility shift assays. We also identified non-nick site sequences within the minimal oriT that were essential for mobilization. We hypothesize that transposon-based single Mob protein systems may contribute to efficient gene dissemination from Bacteroides spp., because fewer DNA processing proteins are required for relaxosome formation.

Total variation superiorized conjugate gradient method for image reconstruction

NASA Astrophysics Data System (ADS)

Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.

2018-03-01

The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.

Semismooth Newton method for gradient constrained minimization problem

NASA Astrophysics Data System (ADS)

Anyyeva, Serbiniyaz; Kunisch, Karl

2012-08-01

In this paper we treat a gradient constrained minimization problem, particular case of which is the elasto-plastic torsion problem. In order to get the numerical approximation to the solution we have developed an algorithm in an infinite dimensional space framework using the concept of the generalized (Newton) differentiation. Regularization was done in order to approximate the problem with the unconstrained minimization problem and to make the pointwise maximum function Newton differentiable. Using semismooth Newton method, continuation method was developed in function space. For the numerical implementation the variational equations at Newton steps are discretized using finite elements method.

Solar multi-conjugate adaptive optics performance improvement

NASA Astrophysics Data System (ADS)

Zhang, Zhicheng; Zhang, Xiaofang; Song, Jie

2015-08-01

In order to overcome the effect of the atmospheric anisoplanatism, Multi-Conjugate Adaptive Optics (MCAO), which was developed based on turbulence correction by means of several deformable mirrors (DMs) conjugated to different altitude and by which the limit of a small corrected FOV that is achievable with AO is overcome and a wider FOV is able to be corrected, has been widely used to widen the field-of-view (FOV) of a solar telescope. With the assistance of the multi-threaded Adaptive Optics Simulator (MAOS), we can make a 3D reconstruction of the distorted wavefront. The correction is applied by one or more DMs. This technique benefits from information about atmospheric turbulence at different layers, which can be used to reconstruct the wavefront extremely well. In MAOS, the sensors are either simulated as idealized wavefront gradient sensors, tip-tilt sensors based on the best Zernike fit, or a WFS using physical optics and incorporating user specified pixel characteristics and a matched filter pixel processing algorithm. Only considering the atmospheric anisoplanatism, we focus on how the performance of a solar MCAO system is related to the numbers of DMs and their conjugate heights. We theoretically quantify the performance of the tomographic solar MCAO system. The results indicate that the tomographic AO system can improve the average Strehl ratio of a solar telescope by only employing one or two DMs conjugated to the optimum altitude. And the S.R. has a significant increase when more deformable mirrors are used. Furthermore, we discuss the effects of DM conjugate altitude on the correction achievable by the MCAO system, and present the optimum DM conjugate altitudes.

On the constrained minimization of smooth Kurdyka—Łojasiewicz functions with the scaled gradient projection method

NASA Astrophysics Data System (ADS)

Prato, Marco; Bonettini, Silvia; Loris, Ignace; Porta, Federica; Rebegoldi, Simone

2016-10-01

The scaled gradient projection (SGP) method is a first-order optimization method applicable to the constrained minimization of smooth functions and exploiting a scaling matrix multiplying the gradient and a variable steplength parameter to improve the convergence of the scheme. For a general nonconvex function, the limit points of the sequence generated by SGP have been proved to be stationary, while in the convex case and with some restrictions on the choice of the scaling matrix the sequence itself converges to a constrained minimum point. In this paper we extend these convergence results by showing that the SGP sequence converges to a limit point provided that the objective function satisfies the Kurdyka-Łojasiewicz property at each point of its domain and its gradient is Lipschitz continuous.

Ferritin conjugates as specific magnetic labels. Implications for cell separation.

PubMed Central

Odette, L L; McCloskey, M A; Young, S H

1984-01-01

Concanavalin A coupled to the naturally occurring iron storage protein ferritin is used to label rat erythrocytes and increase the cells' magnetic susceptibility. Labeled cells are introduced into a chamber containing spherical iron particles and the chamber is placed in a uniform 5.2 kG (gauss) magnetic field. The trajectory of cells in the inhomogeneous magnetic field around the iron particles and the polar distributions of cells bound to the iron particles compare well with the theoretical predictions for high gradient magnetic systems. On the basis of these findings we suggest that ferritin conjugated ligands can be used for selective magnetic separation of labeled cells. Images FIGURE 2 PMID:6743752

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1984-01-01

The research efforts of University of Virginia students under a NASA sponsored program are summarized and the status of the program is reported. The research includes: testing method evaluations for N version programming; a representation scheme for modeling three dimensional objects; fault tolerant protocols for real time local area networks; performance investigation of Cyber network; XFEM implementation; and vectorizing incomplete Cholesky conjugate gradients.

An iterative method for the Helmholtz equation

NASA Technical Reports Server (NTRS)

Bayliss, A.; Goldstein, C. I.; Turkel, E.

1983-01-01

An iterative algorithm for the solution of the Helmholtz equation is developed. The algorithm is based on a preconditioned conjugate gradient iteration for the normal equations. The preconditioning is based on an SSOR sweep for the discrete Laplacian. Numerical results are presented for a wide variety of problems of physical interest and demonstrate the effectiveness of the algorithm.

Folic Acid-Conjugated Pyropheophorbide a as the Photosensitizer Tested for In Vivo Targeted Photodynamic Therapy.

PubMed

Wang, Jin; Liu, Qian; Zhang, Yuting; Shi, Huan; Liu, Hui; Guo, Wenjun; Ma, Yanhong; Huang, Weiqiang; Hong, Zhangyong

2017-06-01

Photodynamic therapy (PDT) is a highly localized and minimally invasive cancer treatment modality with many important advantages, but the lack of ideal photosensitizers (PSs) greatly restricts its clinical utility. To develop new PSs with highly efficient singlet oxygen production and high tumor-localizing ability to reduce damage to healthy adjacent tissues, we conjugated folic acid (FA) with pyropheophorbide a (Pyro), a potent PS with a very high singlet oxygen quantum yield and a high extinction coefficient. In the present work, we describe the synthesis and PDT evaluation of this FA-Pyro conjugate both in vitro and in vivo. This conjugation increased the accumulation of Pyro inside the tumors and improved the efficiency of PDT, resulting in eradication of subcutaneous xenograft KB (human mouth epidermal carcinoma) tumors after only 1 or 2 applications of external near infrared light irradiation. This outstanding PDT outcome in a tumor-bearing mouse model and the simple synthesis of the conjugate should have very good practical potential for clinical application. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Trifunctional conjugation reagents. Reagents that contain a biotin and a radiometal chelation moiety for application to extracorporeal affinity adsorption of radiolabeled antibodies.

PubMed

Wilbur, D Scott; Chyan, Ming-Kuan; Hamlin, Donald K; Kegley, Brian B; Nilsson, Rune; Sandberg, Bengt E B; Brechbiel, Martin

2002-01-01

A method of removing radiolabeled monoclonal antibodies (mAbs) from blood using a device external to the body, termed extracorporeal affinity-adsorption (EAA), is being evaluated as a means of decreasing irradiation of noncancerous tissues in therapy protocols. The EAA device uses an avidin column to capture biotinylated-radiolabeled mAbs from circulated blood. In this investigation, three trifunctional reagents have been developed to minimize the potential deleterious effect on antigen binding brought about by the combination of radiolabeling and biotinylation of mAbs required in the EAA approach. The studies focused on radiolabeling with (111)In and (90)Y, so the chelates CHX-A' '-DTPA and DOTA, which form stable attachments to these radionuclides, were incorporated in the trifunctional reagents. The first trifunctional reagent prepared did not incorporate a group to block the biotin cleaving enzyme biotinidase, but the two subsequent reagents coupled aspartic acid to the biotin carboxylate for that purpose. All three reagents used 4,7,10-trioxa-1,13-tridecanediamine as water-soluble spacers between an aminoisophthalate core and the biotin or chelation group. The mAb conjugates were radioiodinated to evaluate cell binding as a function of substitution. Radioiodination was used so that a direct comparison with unmodified mAb could be made. Evaluation of the number of conjugates per antibody versus cell binding immunoreactivities indicated that minimizing the number of conjugates was best. Interestingly, a decrease of radioiodination yield as a function of the number of isothiocyanate containing conjugates per mAb was noted. The decreased yields were presumably due to the presence of thiourea functionality formed in the conjugation reaction. Radiolabeling with (111)In and (90)Y was facile at room temperature for conjugates containing the CHX-A' ', but elevated temperature (e.g., 45 degrees C) was required to obtain good yields with the DOTA chelate. Stability of (90)Y labeled mAb in serum, and when challenged with 10 mM EDTA, was high. However, challenging the (90)Y labeled mAb with 10 mM DTPA demonstrated high stability for the DOTA containing conjugate, but low stability for the CHX-A' ' containing conjugate. Thus, the choice between these two chelating moieties might be made on requirements for facile and gentle labeling versus very high in vivo stability. Application of the trifunctional biotinylation reagents to the blood clearance of labeled antibodies in EAA is under investigation. The new reagents may also be useful for other applications.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, Hejun

2018-04-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, numerous studies suggested links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their triggering mechanisms, we need an accurate 3D crustal wavespeed model for the study region. Considering the uneven distribution of earthquakes in this area, seismic tomography with local earthquake records have difficulties achieving even illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. Twenty five preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model TO25 correlates well with geological provinces in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front, etc. In addition, there are relatively good correlations between seismic results with gravity and magnetic observations. This new crustal model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location as well as moment tensor solutions, which are important for investigating triggering mechanisms between these induced earthquakes and unconventional oil and gas exploration activities.

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization.

PubMed

Dash, Tirtharaj; Sahu, Prabhat K

2015-05-30

The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking the center stage with regard to efficient algorithm, computational cost and accuracy. In this article, the gradient-based gravitational search (GGS) algorithm, using analytical gradients for a fast minimization to the next local minimum has been reported. Its efficiency as metaheuristic approach has also been compared with Gradient Tabu Search and others like: Gravitational Search, Cuckoo Search, and Back Tracking Search algorithms for global optimization. Moreover, the GGS approach has also been applied to computational chemistry problems for finding the minimal value potential energy of two-dimensional and three-dimensional off-lattice protein models. The simulation results reveal the relative stability and physical accuracy of protein models with efficient computational cost. © 2015 Wiley Periodicals, Inc.

HPLC analysis of functionalized poly(amidoamine) dendrimers and the interaction between a folate-dendrimer conjugate and folate binding protein.

PubMed

Shi, Xiangyang; Bi, Xiangdong; Ganser, T Rose; Hong, Seungpyo; Myc, Lukasz A; Desai, Ankur; Holl, Mark M Banaszak; Baker, James R

2006-07-01

Poly(amidoamine) (PAMAM) dendrimers of different generations with carboxyl, acetyl, and hydroxyl terminal groups and a folic acid (FA)-dendrimer conjugate were separated and analyzed using reverse-phase high performance liquid chromatography (HPLC). Analysis of both the individual PAMAM derivatives and the separation of mixed generations can be achieved using a linear gradient 0-50% acetonitrile (ACN) (balance water) within 40 min. We also show that PAMAMs with defined acetylation and carboxylation degrees can be analyzed using HPLC. Furthermore, a generation 5 dendrimer-FA conjugate (G5.75Ac-FA4; Ac denotes acetyl) was analyzed and its specific binding with a bovine folic acid binding protein (FBP) was monitored. The HPLC and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) results indicate the formation of three complexes after the binding of G5.75Ac-FA4 with FBP. Dendrimers with FA moieties show much higher specific binding capability with FBP than those without FA moieties. Findings from this study indicate that HPLC is an effective technique not only for characterization and separation of functionalized PAMAM dendrimers and conjugates but also for investigation of the interaction between dendrimers and biomolecules.

The role of polymerase III in conjugation between E. coli K12 donor and recipient strains carrying dnaE ts mutation.

PubMed

Blinkowa, A

1976-01-01

The possible role of DNA polimerase III in conjugation was studied in a series of mutants temperature-sensitive for DNA polymerase III synthesis. The temperature-sensitive DNA mutation called dnaE 486 (ts) prohibits vegetative DNA replication at 41-45 degrees. Transfer of episome and chromosome from temperature-sensitive donor, carrying dnaE mutation to wild-type recipient strains, revertants and dnaE recipients was investigated. In the first two cases the number of Lac+ sexductants being even slightly higher at 43 degrees. Conjugational synthesis accompanying transfer involving the combination of dnaE (ts) thymine dependent and thymine independent donor and recipient strains measured by incorporation of 14C thymine was observed at the restrictive temperature. In the case of conjugation with temperaturesensitive recipient strains a drop of Lac+ sexductants and Pro+ recombinants may be as a result of disturbances in the synthesis of complementary strand in recipient, known to be dependent on pol III. However, the episome investigated by centrifugation in neutral CsC1 gradient after its transfer to the recipient with faulty polymerase III was double stranded (replicated) at the restrictive temperature.

Efficient geostatistical inversion of transient groundwater flow using preconditioned nonlinear conjugate gradients

NASA Astrophysics Data System (ADS)

Klein, Ole; Cirpka, Olaf A.; Bastian, Peter; Ippisch, Olaf

2017-04-01

In the geostatistical inverse problem of subsurface hydrology, continuous hydraulic parameter fields, in most cases hydraulic conductivity, are estimated from measurements of dependent variables, such as hydraulic heads, under the assumption that the parameter fields are autocorrelated random space functions. Upon discretization, the continuous fields become large parameter vectors with O (104 -107) elements. While cokriging-like inversion methods have been shown to be efficient for highly resolved parameter fields when the number of measurements is small, they require the calculation of the sensitivity of each measurement with respect to all parameters, which may become prohibitive with large sets of measured data such as those arising from transient groundwater flow. We present a Preconditioned Conjugate Gradient method for the geostatistical inverse problem, in which a single adjoint equation needs to be solved to obtain the gradient of the objective function. Using the autocovariance matrix of the parameters as preconditioning matrix, expensive multiplications with its inverse can be avoided, and the number of iterations is significantly reduced. We use a randomized spectral decomposition of the posterior covariance matrix of the parameters to perform a linearized uncertainty quantification of the parameter estimate. The feasibility of the method is tested by virtual examples of head observations in steady-state and transient groundwater flow. These synthetic tests demonstrate that transient data can reduce both parameter uncertainty and time spent conducting experiments, while the presented methods are able to handle the resulting large number of measurements.

3D first-arrival traveltime tomography with modified total variation regularization

NASA Astrophysics Data System (ADS)

Jiang, Wenbin; Zhang, Jie

2018-02-01

Three-dimensional (3D) seismic surveys have become a major tool in the exploration and exploitation of hydrocarbons. 3D seismic first-arrival traveltime tomography is a robust method for near-surface velocity estimation. A common approach for stabilizing the ill-posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a 3D first-arrival traveltime tomography method with modified total variation (MTV) regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L2 total variation problem. We apply the conjugate gradient method and split-Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization. We apply the technique to field data. The stacking section shows significant improvements with static corrections from the MTV traveltime tomography.

Adjoint-Baed Optimal Control on the Pitch Angle of a Single-Bladed Vertical-Axis Wind Turbine

NASA Astrophysics Data System (ADS)

Tsai, Hsieh-Chen; Colonius, Tim

2017-11-01

Optimal control on the pitch angle of a NACA0018 single-bladed vertical-axis wind turbine (VAWT) is numerically investigated at a low Reynolds number of 1500. With fixed tip-speed ratio, the input power is minimized and mean tangential force is maximized over a specific time horizon. The immersed boundary method is used to simulate the two-dimensional, incompressible flow around a horizontal cross section of the VAWT. The problem is formulated as a PDE constrained optimization problem and an iterative solution is obtained using adjoint-based conjugate gradient methods. By the end of the longest control horizon examined, two controls end up with time-invariant pitch angles of about the same magnitude but with the opposite signs. The results show that both cases lead to a reduction in the input power but not necessarily an enhancement in the mean tangential force. These reductions in input power are due to the removal of a power-damaging phenomenon that occurs when a vortex pair is captured by the blade in the upwind-half region of a cycle. This project was supported by Caltech FLOWE center/Gordon and Betty Moore Foundation.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments.

PubMed

Fisicaro, G; Genovese, L; Andreussi, O; Marzari, N; Goedecker, S

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction.

PubMed

Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

2015-01-01

Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as "ALM-ANAD". The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics.

An implicit numerical scheme for the simulation of internal viscous flows on unstructured grids

NASA Technical Reports Server (NTRS)

Jorgenson, Philip C. E.; Pletcher, Richard H.

1994-01-01

The Navier-Stokes equations are solved numerically for two-dimensional steady viscous laminar flows. The grids are generated based on the method of Delaunay triangulation. A finite-volume approach is used to discretize the conservation law form of the compressible flow equations written in terms of primitive variables. A preconditioning matrix is added to the equations so that low Mach number flows can be solved economically. The equations are time marched using either an implicit Gauss-Seidel iterative procedure or a solver based on a conjugate gradient like method. A four color scheme is employed to vectorize the block Gauss-Seidel relaxation procedure. This increases the memory requirements minimally and decreases the computer time spent solving the resulting system of equations substantially. A factor of 7.6 speed up in the matrix solver is typical for the viscous equations. Numerical results are obtained for inviscid flow over a bump in a channel at subsonic and transonic conditions for validation with structured solvers. Viscous results are computed for developing flow in a channel, a symmetric sudden expansion, periodic tandem cylinders in a cross-flow, and a four-port valve. Comparisons are made with available results obtained by other investigators.

Compressive sensing of electrocardiogram signals by promoting sparsity on the second-order difference and by using dictionary learning.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2014-04-01

A new algorithm for the reconstruction of electrocardiogram (ECG) signals and a dictionary learning algorithm for the enhancement of its reconstruction performance for a class of signals are proposed. The signal reconstruction algorithm is based on minimizing the lp pseudo-norm of the second-order difference, called as the lp(2d) pseudo-norm, of the signal. The optimization involved is carried out using a sequential conjugate-gradient algorithm. The dictionary learning algorithm uses an iterative procedure wherein a signal reconstruction and a dictionary update steps are repeated until a convergence criterion is satisfied. The signal reconstruction step is implemented by using the proposed signal reconstruction algorithm and the dictionary update step is implemented by using the linear least-squares method. Extensive simulation results demonstrate that the proposed algorithm yields improved reconstruction performance for temporally correlated ECG signals relative to the state-of-the-art lp(1d)-regularized least-squares and Bayesian learning based algorithms. Also for a known class of signals, the reconstruction performance of the proposed algorithm can be improved by applying it in conjunction with a dictionary obtained using the proposed dictionary learning algorithm.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

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

Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S.; Genovese, L.

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and themore » linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.« less

Anti-CD45 Pretargeted Radioimmunotherapy using Bismuth-213: High Rates of Complete Remission and Long-Term Survival in a Mouse Myeloid Leukemia Xenograft Model

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

Pagel, John M; Kenoyer, Aimee L; Back, Tom

2011-07-21

Pretargeted radioimmunotherapy (PRIT) using an anti-CD45 antibody (Ab)-streptavidin (SA) conjugate and DOTA-biotin labeled with β-emitting radionuclides has been explored as a strategy to decrease relapse and toxicity. α-emitting radionuclides exhibit high cytotoxicity coupled with a short path-length, potentially increasing the therapeutic index and making them an attractive alternative to β-emitting radionuclides for patients with Acute Myeloid Leukemia (AML). Accordingly, we have used 213Bi in mice with human leukemia xenografts. Results demonstrated excellent localization of 213Bi-DOTA-biotin to tumors with minimal uptake into normal organs. After 10 minutes, 4.5 ± 1.1% of the injected dose of 213Bi was delivered per gram ofmore » tumor. α imaging demonstrated uniform radionuclide distribution within tumor tissue 45 minutes after 213Bi-DOTA-biotin injection. Radiation absorbed doses were similar to those observed using a β-emitting radionuclide (90Y) in the same model. We conducted therapy experiments in a xenograft model using a single-dose of 213Bi-DOTA-biotin given 24 hours after anti-CD45 Ab-SA conjugate. Among mice treated with anti-CD45 Ab-SA conjugate followed by 800 μCi of 213Bi- or 90Y-DOTA-biotin, 80% and 20%, respectively, survived leukemia-free for >100 days with minimal toxicity. These data suggest that anti-CD45 PRIT using an α-emitting radionuclide may be highly effective and minimally toxic for treatment of AML.« less

TV-based conjugate gradient method and discrete L-curve for few-view CT reconstruction of X-ray in vivo data.

PubMed

Yang, Xiaoli; Hofmann, Ralf; Dapp, Robin; van de Kamp, Thomas; dos Santos Rolo, Tomy; Xiao, Xianghui; Moosmann, Julian; Kashef, Jubin; Stotzka, Rainer

2015-03-09

High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration of in vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce the number of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation.

Ptychographic overlap constraint errors and the limits of their numerical recovery using conjugate gradient descent methods.

PubMed

Tripathi, Ashish; McNulty, Ian; Shpyrko, Oleg G

2014-01-27

Ptychographic coherent x-ray diffractive imaging is a form of scanning microscopy that does not require optics to image a sample. A series of scanned coherent diffraction patterns recorded from multiple overlapping illuminated regions on the sample are inverted numerically to retrieve its image. The technique recovers the phase lost by detecting the diffraction patterns by using experimentally known constraints, in this case the measured diffraction intensities and the assumed scan positions on the sample. The spatial resolution of the recovered image of the sample is limited by the angular extent over which the diffraction patterns are recorded and how well these constraints are known. Here, we explore how reconstruction quality degrades with uncertainties in the scan positions. We show experimentally that large errors in the assumed scan positions on the sample can be numerically determined and corrected using conjugate gradient descent methods. We also explore in simulations the limits, based on the signal to noise of the diffraction patterns and amount of overlap between adjacent scan positions, of just how large these errors can be and still be rendered tractable by this method.

Enhanced spatial resolution in fluorescence molecular tomography using restarted L1-regularized nonlinear conjugate gradient algorithm.

PubMed

Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing

2014-04-01

Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.

Algorithms for the optimization of RBE-weighted dose in particle therapy.

PubMed

Horcicka, M; Meyer, C; Buschbacher, A; Durante, M; Krämer, M

2013-01-21

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Algorithms for the optimization of RBE-weighted dose in particle therapy

NASA Astrophysics Data System (ADS)

Horcicka, M.; Meyer, C.; Buschbacher, A.; Durante, M.; Krämer, M.

2013-01-01

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Applications of the conjugate gradient FFT method in scattering and radiation including simulations with impedance boundary conditions

NASA Technical Reports Server (NTRS)

Barkeshli, Kasra; Volakis, John L.

1991-01-01

The theoretical and computational aspects related to the application of the Conjugate Gradient FFT (CGFFT) method in computational electromagnetics are examined. The advantages of applying the CGFFT method to a class of large scale scattering and radiation problems are outlined. The main advantages of the method stem from its iterative nature which eliminates a need to form the system matrix (thus reducing the computer memory allocation requirements) and guarantees convergence to the true solution in a finite number of steps. Results are presented for various radiators and scatterers including thin cylindrical dipole antennas, thin conductive and resistive strips and plates, as well as dielectric cylinders. Solutions of integral equations derived on the basis of generalized impedance boundary conditions (GIBC) are also examined. The boundary conditions can be used to replace the profile of a material coating by an impedance sheet or insert, thus, eliminating the need to introduce unknown polarization currents within the volume of the layer. A general full wave analysis of 2-D and 3-D rectangular grooves and cavities is presented which will also serve as a reference for future work.

How cereal grass shoots perceive and respond to gravity

NASA Technical Reports Server (NTRS)

Kaufman, P. B.; Brock, T. G.; Song, I.; Rho, Y. B.; Ghosheh, N. S.

1987-01-01

The leaf-sheath pulvinus of grasses presents a unique system for studying gravitropism, primarily because of its differences from other organs. The mature pulvinus is a discrete organ specialized for gravitropism: it is nongrowing in the absence of gravistimulation and capable of displaying a graviresponse independent of the rest of the plant. In this paper we present a model for gravitropism in pulvini based on recent findings from studies on the mechanisms of graviperception and graviresponse. According to this model, amyloplasts play an essential role in perceiving a change in the orientation of the pulvinus. The perception of this reorientation leads to the enhanced synthesis and release from conjugate of the auxin IAA, and the increased conjugation of gibberellin, on a localized basis. Because there is a graded growth promotion across the gravistimulated pulvinus, it is suggested that the observed hormonal asymmetry is actually an indication of a linear gradient of hormone concentration, as well as hormone response, across the pulvinus. It is further suggested that the linear gradient of hormone concentration may be predominantly the result of local changes in hormone level, rather than a product of hormonal movement into or across the pulvinus.

TV-based conjugate gradient method and discrete L-curve for few-view CT reconstruction of X-ray in vivo data

DOE PAGES

Yang, Xiaoli; Hofmann, Ralf; Dapp, Robin; ...

2015-01-01

High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration o f in vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce themore » number of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation.« less

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

NASA Astrophysics Data System (ADS)

Kaporin, I. E.

2012-02-01

In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.

[Effects of choledochal perfusion with biliary acid solutions on activity of the sphincter of Oddi (author's transl)].

PubMed

Bevilacqua, R G; Margarido, N F; Soares, L A; Mansur, R; Koch, V; Gonçalves, E L

1979-06-01

The changes of sphincter of Oddi's resistance, induced by choledochal perfusion of conjugated (taurocolic) and non-conjugated (colic) biliary acid solutions, in anesthetized dogs, were studied. The perfusions were made at a constant flow and intracholedochal pressures were registered. The mean number of contractions per minute, the mean maximal pressures and the mean minimal pressures in each study periods were analysed. The choledochal perfusion with the biliary acids solutions induced a slight but significative increase in sphincteric resistance. After 15 minutes, the perfusion with colic acid solution induced maximal pressures significantly more elevated than the ones observed with taurocolic acid solution. The non-conjugated solution induced a pressure tracing significantly distinct from the tracing observed with the conjugated acid solution. No changes in resistance were observed with a 2% NaCl solution. This implies that the observed changes in resistance were not related to osmotic stimulation of the sphincter of Oddi.

Double diffusive conjugate heat transfer: Part I

NASA Astrophysics Data System (ADS)

Azeem, Soudagar, Manzoor Elahi M.

2018-05-01

The present work is undertaken to investigate the effect of solid wall being placed at left of square cavity filled with porous medium. The presence of a solid wall in the porous medium turns the situation into a conjugate heat transfer problem. The boundary conditions are such that the left vertical surface is maintained at highest temperature and concentration whereas right vertical surface at lowest temperature and concentration in the medium. The top and bottom surfaces are adiabatic. The additional conduction equation along with the regular momentum and energy equations of porous medium are solved in an iterative manner with the help of finite element method. It is seen that the heat and mass transfer rate is lesser due to smaller thermal and concentration gradients.

Minimization of Dead-Periods in MRI Pulse Sequences for Imaging Oblique Planes

PubMed Central

Atalar, Ergin; McVeigh, Elliot R.

2007-01-01

With the advent of breath-hold MR cardiac imaging techniques, the minimization of TR and TE for oblique planes has become a critical issue. The slew rates and maximum currents of gradient amplifiers limit the minimum possible TR and TE by adding dead-periods to the pulse sequences. We propose a method of designing gradient waveforms that will be applied to the amplifiers instead of the slice, readout, and phase encoding waveforms. Because this method ensures that the gradient amplifiers will always switch at their maximum slew rate, it results in the minimum possible dead-period for given imaging parameters and scan plane position. A GRASS pulse sequence has been designed and ultra-short TR and TE values have been obtained with standard gradient amplifiers and coils. For some oblique slices, we have achieved shorter TR and TE values than those for nonoblique slices. PMID:7869900

Conjugated block copolymers as model materials to examine charge transfer in donor-acceptor systems

NASA Astrophysics Data System (ADS)

Gomez, Enrique; Aplan, Melissa; Lee, Youngmin

Weak intermolecular interactions and disorder at junctions of different organic materials limit the performance and stability of organic interfaces and hence the applicability of organic semiconductors to electronic devices. The lack of control of interfacial structure has also prevented studies of how driving forces promote charge photogeneration, leading to conflicting hypotheses in the organic photovoltaic literature. Our approach has focused on utilizing block copolymer architectures -where critical interfaces are controlled and stabilized by covalent bonds- to provide the hierarchical structure needed for high-performance organic electronics from self-assembled soft materials. For example, we have demonstrated control of donor-acceptor heterojunctions through microphase-separated conjugated block copolymers to achieve 3% power conversion efficiencies in non-fullerene photovoltaics. Furthermore, incorporating the donor-acceptor interface within the molecular structure facilitates studies of charge transfer processes. Conjugated block copolymers enable studies of the driving force needed for exciton dissociation to charge transfer states, which must be large to maximize charge photogeneration but must be minimized to prevent losses in photovoltage in solar cell devices. Our work has systematically varied the chemical structure, energetics, and dielectric constant to perturb charge transfer. As a consequence, we predict a minimum dielectric constant needed to minimize the driving force and therefore simultaneously maximize photocurrent and photovoltage in organic photovoltaic devices.

G3.5 PAMAM dendrimers enhance transepithelial transport of SN38 while minimizing gastrointestinal toxicity.

PubMed

Goldberg, Deborah S; Vijayalakshmi, Nirmalkumar; Swaan, Peter W; Ghandehari, Hamidreza

2011-03-30

Poly(amido amine) (PAMAM) dendrimers have shown promise in oral drug delivery. Conjugation of SN38 to PAMAM dendrimers has the potential to improve its oral absorption while minimizing gastrointestinal toxicity. In this work we evaluated G3.5 PAMAM dendrimer-SN38 conjugates with ester-linked glycine and β-alanine spacers for their suitability in oral therapy of hepatic colorectal cancer metastases. G3.5-βAlanine-SN38 was mostly stable while G3.5-Glycine-SN38 showed 10%, 20%, and 56% SN38 release in simulated gastric, intestinal and liver environments for up to 6, 24 and 48 hours, respectively. Short-term treatment of Caco-2 cells with G3.5-SN38 conjugates did not reduce cell viability, while comparable concentrations of SN38 caused significant cytotoxicity. G3.5-Glycine-SN38 and G3.5-βAlanine-SN38 showed IC₅₀ values of 0.60 and 3.59 μM, respectively, in HT-29 cells treated for 48 h, indicating the efficacy of the drug delivery system in colorectal cancer cells with longer incubation time. Both conjugates increased SN38 transepithelial transport compared to the free drug. Transport of G3.5-Glycine-SN38 was highly concentration-dependent whereas transport of G3.5-βAlanine-SN38 was concentration-independent, highlighting the influence of drug loading and spacer chemistry on transport mechanism. Together these results show that PAMAM dendrimers have the potential to improve the oral bioavailability of potent anti-cancer drugs. Copyright © 2010 Elsevier B.V. All rights reserved.

G3.5 PAMAM Dendrimers Enhance Transepithelial Transport of SN38 while minimizing Gastrointestinal Toxicity

PubMed Central

Goldberg, Deborah S.; Vijayalakshmi, Nirmalkumar; Swaan, Peter W.; Ghandehari, Hamidreza

2011-01-01

Poly(amido amine) (PAMAM) dendrimers have shown promise in oral drug delivery. Conjugation of SN38 to PAMAM dendrimers has the potential to improve its oral absorption while minimizing gastrointestinal toxicity. In this work we evaluated G3.5 PAMAM dendrimer-SN38 conjugates with ester-linked glycine and β-alanine spacers for their suitability in oral therapy of hepatic colorectal cancer metastases. G3.5-βAlanine-SN38 was mostly stable while G3.5-Glycine-SN38 showed 10%, 20%, and 56% SN38 release in simulated gastric, intestinal and liver environments for up to 6, 24 and 48 hours, respectively. Short-term treatment of Caco-2 cells with G3.5-SN38 conjugates did not reduce cell viability, while comparable concentrations of SN38 caused significant cytotoxicity. G3.5-Glycine-SN38 and G3.5-βAlanine-SN38 showed IC50 values of 0.60 and 3.59 μM, respectively, in HT-29 cells treated for 48 hours, indicating the efficacy of the drug delivery system in colorectal cancer cells with longer incubation time. Both conjugates increased SN38 transepithelial transport compared to the free drug. Transport of G3.5-Glycine-SN38 was highly concentration-dependent whereas transport of G3.5-βAlanine-SN38 was concentration-independent, highlighting the influence of drug loading and spacer chemistry on transport mechanism. Together these results show that PAMAM dendrimers have the potential to improve the oral bioavailability of potent anti-cancer drugs. PMID:21115079

Inverse problems with nonnegative and sparse solutions: algorithms and application to the phase retrieval problem

NASA Astrophysics Data System (ADS)

Quy Muoi, Pham; Nho Hào, Dinh; Sahoo, Sujit Kumar; Tang, Dongliang; Cong, Nguyen Huu; Dang, Cuong

2018-05-01

In this paper, we study a gradient-type method and a semismooth Newton method for minimization problems in regularizing inverse problems with nonnegative and sparse solutions. We propose a special penalty functional forcing the minimizers of regularized minimization problems to be nonnegative and sparse, and then we apply the proposed algorithms in a practical the problem. The strong convergence of the gradient-type method and the local superlinear convergence of the semismooth Newton method are proven. Then, we use these algorithms for the phase retrieval problem and illustrate their efficiency in numerical examples, particularly in the practical problem of optical imaging through scattering media where all the noises from experiment are presented.

Nonadiabatic excited-state molecular dynamics: modeling photophysics in organic conjugated materials.

PubMed

Nelson, Tammie; Fernandez-Alberti, Sebastian; Roitberg, Adrian E; Tretiak, Sergei

2014-04-15

To design functional photoactive materials for a variety of technological applications, researchers need to understand their electronic properties in detail and have ways to control their photoinduced pathways. When excited by photons of light, organic conjugated materials (OCMs) show dynamics that are often characterized by large nonadiabatic (NA) couplings between multiple excited states through a breakdown of the Born-Oppenheimer (BO) approximation. Following photoexcitation, various nonradiative intraband relaxation pathways can lead to a number of complex processes. Therefore, computational simulation of nonadiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons. Over the years, we have developed a nonadiabatic excited-state molecular dynamics (NA-ESMD) framework that efficiently and accurately describes photoinduced phenomena in extended conjugated molecular systems. We use the fewest-switches surface hopping (FSSH) algorithm to treat quantum transitions among multiple adiabatic excited state potential energy surfaces (PESs). Extended molecular systems often contain hundreds of atoms and involve large densities of excited states that participate in the photoinduced dynamics. We can achieve an accurate description of the multiple excited states using the configuration interaction single (CIS) formalism with a semiempirical model Hamiltonian. Analytical techniques allow the trajectory to be propagated "on the fly" using the complete set of NA coupling terms and remove computational bottlenecks in the evaluation of excited-state gradients and NA couplings. Furthermore, the use of state-specific gradients for propagation of nuclei on the native excited-state PES eliminates the need for simplifications such as the classical path approximation (CPA), which only uses ground-state gradients. Thus, the NA-ESMD methodology offers a computationally tractable route for simulating hundreds of atoms on ~10 ps time scales where multiple coupled excited states are involved. In this Account, we review recent developments in the NA-ESMD modeling of photoinduced dynamics in extended conjugated molecules involving multiple coupled electronic states. We have successfully applied the outlined NA-ESMD framework to study ultrafast conformational planarization in polyfluorenes where the rate of torsional relaxation can be controlled based on the initial excitation. With the addition of the state reassignment algorithm to identify instances of unavoided crossings between noninteracting PESs, NA-ESMD can now be used to study systems in which these so-called trivial unavoided crossings are expected to predominate. We employ this technique to analyze the energy transfer between poly(phenylene vinylene) (PPV) segments where conformational fluctuations give rise to numerous instances of unavoided crossings leading to multiple pathways and complex energy transfer dynamics that cannot be described using a simple Förster model. In addition, we have investigated the mechanism of ultrafast unidirectional energy transfer in dendrimers composed of poly(phenylene ethynylene) (PPE) chromophores and have demonstrated that differential nuclear motion favors downhill energy transfer in dendrimers. The use of native excited-state gradients allows us to observe this feature.

Comparative biodistributions and dosimetry of [¹⁷⁷Lu]DOTA-anti-bcl-2-PNA-Tyr³-octreotate and [¹⁷⁷Lu]DOTA-Tyr³-octreotate in a mouse model of B-cell lymphoma/leukemia.

PubMed

Balkin, Ethan R; Liu, Dijie; Jia, Fang; Ruthengael, Varyanna C; Shaffer, Suzanne M; Miller, William H; Lewis, Michael R

2014-01-01

The B-cell lymphoma/leukemia-2 (bcl-2) proto-oncogene in non-Hodgkin's lymphoma (NHL) is a dominant inhibitor of apoptosis. We developed a (177)Lu-labeled bcl-2 antisense peptide nucleic acid (PNA)-peptide conjugate designed for dual modality NHL therapy, consisting of a radiopharmaceutical capable of simultaneously down-regulating apoptotic resistance and delivering cytotoxic internally emitted radiation. DOTA-anti-bcl-2-Tyr(3)-octreotate was synthesized, labeled with (177)Lu, and purified using RP-HPLC. The PNA-peptide conjugate was evaluated in Mec-1 NHL-bearing mice and compared to [(177)Lu]DOTA-Tyr(3)-octreotate in biodistribution and excretion studies. These data were then used to generate in vivo dosimetry models. The PNA-peptide conjugate was readily prepared and radiolabeled in high yield and radiochemical purity. An in vivo blocking study determined that administration of 50 μg of non-radioactive PNA-peptide was the optimal mass for maximum delivery to the tumor. Based on that result, a dosing regimen of (177)Lu-PNA-peptide, for radiologic effect, followed by the optimal mass of non-radioactive compound, for antisense effect, was designed. Using that dosing regimen, biodistribution of the PNA-peptide showed uptake in the tumor with minimal washout over a 4-day period. Uptakes in receptor-positive normal organs were low and displayed nearly complete washout by 24h. Dosimetry models showed that the tumor absorbed dose of the PNA-peptide conjugate was approximately twice that of the peptide-only conjugate. Biodistribution data showed specific tumor targeting of the (177)Lu-labeled PNA-peptide compound with minimal receptor-positive normal tissue uptake when compared to [(177)Lu]DOTA-Tyr(3)-octreotate. In vivo dosimetry models predicted a more favorable tumor absorbed dose from [(177)Lu]DOTA-anti-bcl-2-Tyr(3)-octreotate. © 2013.

Anti-cancer Antibody Trastuzumab-Melanotransferrin Conjugate (BT2111) for the Treatment of Metastatic HER2+ Breast Cancer Tumors in the Brain: an In-Vivo Study.

PubMed

Nounou, Mohamed Ismail; Adkins, Chris E; Rubinchik, Evelina; Terrell-Hall, Tori B; Afroz, Mohamed; Vitalis, Tim; Gabathuler, Reinhard; Tian, Mei Mei; Lockman, Paul R

2016-12-01

The ability of human melanotransferrin (hMTf) to carry a therapeutic concentration of trastuzumab (BTA) in the brain after conjugation (in the form of trastuzumab-melanotransferrin conjugate, BT2111 conjugate) was investigated by measuring the reduction of the number and size of metastatic human HER 2+ breast cancer tumors in a preclinical model of brain metastases of breast cancer. Human metastatic brain seeking breast cancer cells were injected in NuNu mice (n = 6-12 per group) which then developed experimental brain metastases. Drug uptake was analyzed in relation to metastasis size and blood-tumor barrier permeability. To investigate in-vivo activity against brain metastases, equimolar doses of the conjugate, and relevant controls (hMTf and BTA) in separate groups were administered biweekly after intracardiac injection of the metastatic cancer cells. The trastuzumab-melanotransferrin conjugate (BT2111) reduced the number of preclinical human HER 2+ breast cancer metastases in the brain by 68% compared to control groups. Tumors which remained after treatment were 46% smaller than the control groups. In contrast, BTA alone had no effect on reducing number of metastases, and was associated with only a minimal reduction in metastasis size. The results suggest the novel trastuzumab-melanotransferrin conjugate (BT2111) may have utility in treating brain metastasis and validate hMTf as a potential vector for antibody transport across the Blood Brain Barrier (BBB).

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1986-01-01

Various graduate research activities in the field of computer science are reported. Among the topics discussed are: (1) failure probabilities in multi-version software; (2) Gaussian Elimination on parallel computers; (3) three dimensional Poisson solvers on parallel/vector computers; (4) automated task decomposition for multiple robot arms; (5) multi-color incomplete cholesky conjugate gradient methods on the Cyber 205; and (6) parallel implementation of iterative methods for solving linear equations.

A Fast Deep Learning System Using GPU

DTIC Science & Technology

2014-06-01

hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...widely used in data modeling until three decades later when efficient training algorithm for RBM is invented by Hinton [3] and the computing power is...be trained using most of optimization algorithms , such as BP, conjugate gradient descent (CGD) or Levenberg-Marquardt (LM). The advantage of this

Conference Proceedings: 7th Annual Review of Progress in Applied Computational Electromagnetics at the Naval Postgraduate School, Monterey, California, March 18-22, 1991

DTIC Science & Technology

1991-03-01

34Volume integral Equations and Conjugate Gradient Methods in Electromagnetic Non destructive Evaluation’ by Dr. Harold P.. Sabbagh, Sabbagh Associates...8217 Experimental Demonstrations far teaching Electroamgnetic Folods and Energy’ M. Zathn, J. Mectrer...8217-....................................... . ...................................................... 329 ’PoalarimetrIc Scattering and Control at Radar Crass Section of Chirat Targets at Simple

Finite-temperature stress calculations in atomic models using moments of position.

PubMed

Parthasarathy, Ranganathan; Misra, Anil; Ouyang, Lizhi

2018-07-04

Continuum modeling of finite temperature mechanical behavior of atomic systems requires refined description of atomic motions. In this paper, we identify additional kinematical quantities that are relevant for a more accurate continuum description as the system is subjected to step-wise loading. The presented formalism avoids the necessity for atomic trajectory mapping with deformation, provides the definitions of the kinematic variables and their conjugates in real space, and simplifies local work conjugacy. The total work done on an atom under deformation is decomposed into the work corresponding to changing its equilibrium position and work corresponding to changing its second moment about equilibrium position. Correspondingly, we define two kinematic variables: a deformation gradient tensor and a vibration tensor, and derive their stress conjugates, termed here as static and vibration stresses, respectively. The proposed approach is validated using MD simulation in NVT ensembles for fcc aluminum subjected to uniaxial extension. The observed evolution of second moments in the MD simulation with macroscopic deformation is not directly related to the transformation of atomic trajectories through the deformation gradient using generator functions. However, it is noteworthy that deformation leads to a change in the second moment of the trajectories. Correspondingly, the vibration part of the Piola stress becomes particularly significant at high temperature and high tensile strain as the crystal approaches the softening limit. In contrast to the eigenvectors of the deformation gradient, the eigenvectors of the vibration tensor show strong spatial heterogeneity in the vicinity of softening. More importantly, the elliptic distribution of local atomic density transitions to a dumbbell shape, before significant non-affinity in equilibrium positions has occurred.

Finite-temperature stress calculations in atomic models using moments of position

NASA Astrophysics Data System (ADS)

Parthasarathy, Ranganathan; Misra, Anil; Ouyang, Lizhi

2018-07-01

Continuum modeling of finite temperature mechanical behavior of atomic systems requires refined description of atomic motions. In this paper, we identify additional kinematical quantities that are relevant for a more accurate continuum description as the system is subjected to step-wise loading. The presented formalism avoids the necessity for atomic trajectory mapping with deformation, provides the definitions of the kinematic variables and their conjugates in real space, and simplifies local work conjugacy. The total work done on an atom under deformation is decomposed into the work corresponding to changing its equilibrium position and work corresponding to changing its second moment about equilibrium position. Correspondingly, we define two kinematic variables: a deformation gradient tensor and a vibration tensor, and derive their stress conjugates, termed here as static and vibration stresses, respectively. The proposed approach is validated using MD simulation in NVT ensembles for fcc aluminum subjected to uniaxial extension. The observed evolution of second moments in the MD simulation with macroscopic deformation is not directly related to the transformation of atomic trajectories through the deformation gradient using generator functions. However, it is noteworthy that deformation leads to a change in the second moment of the trajectories. Correspondingly, the vibration part of the Piola stress becomes particularly significant at high temperature and high tensile strain as the crystal approaches the softening limit. In contrast to the eigenvectors of the deformation gradient, the eigenvectors of the vibration tensor show strong spatial heterogeneity in the vicinity of softening. More importantly, the elliptic distribution of local atomic density transitions to a dumbbell shape, before significant non-affinity in equilibrium positions has occurred.

Numerical algorithms for scatter-to-attenuation reconstruction in PET: empirical comparison of convergence, acceleration, and the effect of subsets.

PubMed

Berker, Yannick; Karp, Joel S; Schulz, Volkmar

2017-09-01

The use of scattered coincidences for attenuation correction of positron emission tomography (PET) data has recently been proposed. For practical applications, convergence speeds require further improvement, yet there exists a trade-off between convergence speed and the risk of non-convergence. In this respect, a maximum-likelihood gradient-ascent (MLGA) algorithm and a two-branch back-projection (2BP), which was previously proposed, were evaluated. MLGA was combined with the Armijo step size rule; and accelerated using conjugate gradients, Nesterov's momentum method, and data subsets of different sizes. In 2BP, we varied the subset size, an important determinant of convergence speed and computational burden. We used three sets of simulation data to evaluate the impact of a spatial scale factor. The Armijo step size allowed 10-fold increased step sizes compared to native MLGA. Conjugate gradients and Nesterov momentum lead to slightly faster, yet non-uniform convergence; improvements were mostly confined to later iterations, possibly due to the non-linearity of the problem. MLGA with data subsets achieved faster, uniform, and predictable convergence, with a speed-up factor equivalent to the number of subsets and no increase in computational burden. By contrast, 2BP computational burden increased linearly with the number of subsets due to repeated evaluation of the objective function, and convergence was limited to the case of many (and therefore small) subsets, which resulted in high computational burden. Possibilities of improving 2BP appear limited. While general-purpose acceleration methods appear insufficient for MLGA, results suggest that data subsets are a promising way of improving MLGA performance.

Numerical simulations on active shielding methods comparison and wrapped angle optimization for gradient coil design in MRI with enhanced shielding effect

NASA Astrophysics Data System (ADS)

Wang, Yaohui; Xin, Xuegang; Guo, Lei; Chen, Zhifeng; Liu, Feng

2018-05-01

The switching of a gradient coil current in magnetic resonance imaging will induce an eddy current in the surrounding conducting structures while the secondary magnetic field produced by the eddy current is harmful for the imaging. To minimize the eddy current effects, the stray field shielding in the gradient coil design is usually realized by minimizing the magnetic fields on the cryostat surface or the secondary magnetic fields over the imaging region. In this work, we explicitly compared these two active shielding design methods. Both the stray field and eddy current on the cryostat inner surface were quantitatively discussed by setting the stray field constraint with an ultra-low maximum intensity of 2 G and setting the secondary field constraint with an extreme small shielding ratio of 0.000 001. The investigation revealed that the secondary magnetic field control strategy can produce coils with a better performance. However, the former (minimizing the magnetic fields) is preferable when designing a gradient coil with an ultra-low eddy current that can also strictly control the stray field leakage at the edge of the cryostat inner surface. A wrapped-edge gradient coil design scheme was then optimized for a more effective control of the stray fields. The numerical simulation on the wrapped-edge coil design shows that the optimized wrapping angles for the x and z coils in terms of our coil dimensions are 40° and 90°, respectively.

Nonlinear refraction and reflection travel time tomography

USGS Publications Warehouse

Zhang, Jiahua; ten Brink, Uri S.; Toksoz, M.N.

1998-01-01

We develop a rapid nonlinear travel time tomography method that simultaneously inverts refraction and reflection travel times on a regular velocity grid. For travel time and ray path calculations, we apply a wave front method employing graph theory. The first-arrival refraction travel times are calculated on the basis of cell velocities, and the later refraction and reflection travel times are computed using both cell velocities and given interfaces. We solve a regularized nonlinear inverse problem. A Laplacian operator is applied to regularize the model parameters (cell slownesses and reflector geometry) so that the inverse problem is valid for a continuum. The travel times are also regularized such that we invert travel time curves rather than travel time points. A conjugate gradient method is applied to minimize the nonlinear objective function. After obtaining a solution, we perform nonlinear Monte Carlo inversions for uncertainty analysis and compute the posterior model covariance. In numerical experiments, we demonstrate that combining the first arrival refraction travel times with later reflection travel times can better reconstruct the velocity field as well as the reflector geometry. This combination is particularly important for modeling crustal structures where large velocity variations occur in the upper crust. We apply this approach to model the crustal structure of the California Borderland using ocean bottom seismometer and land data collected during the Los Angeles Region Seismic Experiment along two marine survey lines. Details of our image include a high-velocity zone under the Catalina Ridge, but a smooth gradient zone between. Catalina Ridge and San Clemente Ridge. The Moho depth is about 22 km with lateral variations. Copyright 1998 by the American Geophysical Union.

Terrestrial cross-calibrated assimilation of various datasources

NASA Astrophysics Data System (ADS)

Groß, André; Müller, Richard; Schömer, Elmar; Trentmann, Jörg

2014-05-01

We introduce a novel software tool, ANACLIM, for the efficient assimilation of multiple two-dimensional data sets using a variational approach. We consider a single objective function in two spatial coordinates with higher derivatives. This function measures the deviation of the input data from the target data set. By using the Euler-Lagrange formalism the minimization of this objective function can be transformed into a sparse system of linear equations, which can be efficiently solved by a conjugate gradient solver on a desktop workstation. The objective function allows for a series of physically-motivated constraints. The user can control the relative global weights, as well as the individual weight of each constraint on a per-grid-point level. The different constraints are realized as separate terms of the objective function: One similarity term for each input data set and two additional smoothness terms, penalizing high gradient and curvature values. ANACLIM is designed to combine similarity and smoothness operators easily and to choose different solvers. We performed a series of benchmarks to calibrate and verify our solution. We use, for example, terrestrial stations of BSRN and GEBA for the solar incoming flux and AERONET stations for aerosol optical depth. First results show that the combination of these data sources gain a significant benefit against the input datasets with our approach. ANACLIM also includes a region growing algorithm for the assimilation of ground based data. The region growing algorithm computes the maximum area around a station that represents the station data. The regions are grown under several constraints like the homogeneity of the area. The resulting dataset is then used within the assimilation process. Verification is performed by cross-validation. The method and validation results will be presented and discussed.

2D Seismic Imaging of Elastic Parameters by Frequency Domain Full Waveform Inversion

NASA Astrophysics Data System (ADS)

Brossier, R.; Virieux, J.; Operto, S.

2008-12-01

Thanks to recent advances in parallel computing, full waveform inversion is today a tractable seismic imaging method to reconstruct physical parameters of the earth interior at different scales ranging from the near- surface to the deep crust. We present a massively parallel 2D frequency-domain full-waveform algorithm for imaging visco-elastic media from multi-component seismic data. The forward problem (i.e. the resolution of the frequency-domain 2D PSV elastodynamics equations) is based on low-order Discontinuous Galerkin (DG) method (P0 and/or P1 interpolations). Thanks to triangular unstructured meshes, the DG method allows accurate modeling of both body waves and surface waves in case of complex topography for a discretization of 10 to 15 cells per shear wavelength. The frequency-domain DG system is solved efficiently for multiple sources with the parallel direct solver MUMPS. The local inversion procedure (i.e. minimization of residuals between observed and computed data) is based on the adjoint-state method which allows to efficiently compute the gradient of the objective function. Applying the inversion hierarchically from the low frequencies to the higher ones defines a multiresolution imaging strategy which helps convergence towards the global minimum. In place of expensive Newton algorithm, the combined use of the diagonal terms of the approximate Hessian matrix and optimization algorithms based on quasi-Newton methods (Conjugate Gradient, LBFGS, ...) allows to improve the convergence of the iterative inversion. The distribution of forward problem solutions over processors driven by a mesh partitioning performed by METIS allows to apply most of the inversion in parallel. We shall present the main features of the parallel modeling/inversion algorithm, assess its scalability and illustrate its performances with realistic synthetic case studies.

Process development of a FGF21 protein-antibody conjugate.

PubMed

Dirksen, Anouk; Davis, Keith A; Collins, Joe T; Bhattacharya, Keshab; Finneman, Jari I; Pepin, Erin L; Ryczek, Jeffrey S; Brown, Paul W; Wellborn, William B; Mangalathillam, Ratish; Evans, Brad P; Pozzo, Mark J; Finn, Rory F

2017-09-26

A scalable, viable process was developed for the Fibroblast Growth Factor 21 (FGF21) protein-antibody conjugate, CVX-343, an extended half-life therapeutic for the treatment of metabolic disease. CVX-343 utilizes the CovX antibody scaffold technology platform that was specifically developed for peptide and protein half-life extension. CVX-343 is representative of a growing number of complex novel peptide- and protein-based bioconjugate molecules currently being explored as therapeutic candidates. The complexity of these bioconjugates, assembled using well-established chemistries, can lead to very difficult production schemes requiring multiple starting materials and a combination of diverse technologies. Key improvements had to be made to the original CVX-343 Phase 1 manufacturing process in preparation for Phase 3 and commercial manufacturing. A strategy of minimizing FGF21 A129C dimerization and stabilizing the FGF21 A129C Drug Substance Intermediate (DSI), linker, and activated FGF21 intermediate was pursued. The use of tris(2-carboxyethyl)phosphine (TCEP) to prevent FGF21 A129C dimerization through disulfide formation was eliminated. FGF21 A129C dimerization and linker hydrolysis were minimized by formulating and activating FGF21 A129C at acidic instead of neutral pH. An activation use test was utilized to guide FGF21 A129C pooling in order to minimize misfolds, dimers, and misfolded dimers in the FGF21 A129C DSI. After final optimization of reaction conditions, a process was established that reduced the consumption of FGF21 A129C by 36% (from 4.7 to 3.0 equivalents) and the consumption of linker by 55% (from 1.4 to 0.95 equivalents for a smaller required amount of FGF21 A129C ). The overall process time was reduced from ∼5 to ∼3 days. The product distribution improved from containing ∼60% to ∼75% desired bifunctionalized (+2 FGF21) FGF21-antibody conjugate in the crude conjugation mixture and from ∼80% to ∼85% in the final CVX-343 Drug Substance (DS), while maintaining the same overall process yield based on antibody scaffold input. © 2017 Wiley Periodicals, Inc.

Gradient, contact-free volume transfers minimize compound loss in dose-response experiments.

PubMed

Harris, David; Olechno, Joe; Datwani, Sammy; Ellson, Richard

2010-01-01

More accurate dose-response curves can be constructed by eliminating aqueous serial dilution of compounds. Traditional serial dilutions that use aqueous diluents can result in errors in dose-response values of up to 4 orders of magnitude for a significant percentage of a compound library. When DMSO is used as the diluent, the errors are reduced but not eliminated. The authors use acoustic drop ejection (ADE) to transfer different volumes of model library compounds, directly creating a concentration gradient series in the receiver assay plate. Sample losses and contamination associated with compound handling are therefore avoided or minimized, particularly in the case of less water-soluble compounds. ADE is particularly well suited for assay miniaturization, but gradient volume dispensing is not limited to miniaturized applications.

L-Valine appended PLGA nanoparticles for oral insulin delivery.

PubMed

Jain, Ashish; Jain, Sanjay K

2015-08-01

Oral insulin delivery has been the major research issue, since many decades, due to several obvious advantages over other routes. However, this route poses several constraints for the delivery of peptides and proteins which are to be worked upon. The small intestine has been shown to be able to transport the L-forms of amino acids against a concentration gradient and that they compete for the mechanism concerned. So, L-valine was used as a ligand for carrier-mediated transport of insulin-loaded polylactic-co-glycolic acid (PLGA) nanoparticles (NPs). L-Valine-conjugated PLGA nanoparticles were prepared using double emulsion solvent evaporation method. The NPs and conjugated NPs were characterized for their size, drug entrapment efficiency, zeta potential, polydispersity index and in vitro insulin release. Ex vivo studies on intestine revealed that conjugated nanoparticles showed greater insulin uptake as compared to non-conjugated nanoparticles. In vivo studies were performed on streptozotocin-induced diabetic rabbits. Oral suspension of insulin-loaded PLGA nanoparticles reduced blood glucose level from 265.4 ± 8.5 to 246.6 ± 2.4 mg/dL within 4 h which further decreased to 198.7 ± 7.1 mg/dL value after 8 h. The ligand-conjugated formulation on oral administration produced hypoglycaemic effect (216.9 ± 1.9 mg/dL) within 4 h of administration, and the hypoglycaemic effect prolonged till 12 h of oral administration. Simultaneously, the insulin concentration in withdrawn samples was also assessed and found that profile of insulin level is in compliance with the blood glucose reduction profile. Hence, it is concluded that the L-valine-conjugated NPs bearing insulin are the promising carrier for the transportation of insulin across the intestine on oral administration.

Modelling Schumann resonances from ELF measurements using non-linear optimization methods

NASA Astrophysics Data System (ADS)

Castro, Francisco; Toledo-Redondo, Sergio; Fornieles, Jesús; Salinas, Alfonso; Portí, Jorge; Navarro, Enrique; Sierra, Pablo

2017-04-01

Schumann resonances (SR) can be found in planetary atmospheres, inside the cavity formed by the conducting surface of the planet and the lower ionosphere. They are a powerful tool to investigate both the electric processes that occur in the atmosphere and the characteristics of the surface and the lower ionosphere. In this study, the measurements are obtained in the ELF (Extremely Low Frequency) Juan Antonio Morente station located in the national park of Sierra Nevada. The three first modes, contained in the frequency band between 6 to 25 Hz, will be considered. For each time series recorded by the station, the amplitude spectrum was estimated by using Bartlett averaging. Then, the central frequencies and amplitudes of the SRs were obtained by fitting the spectrum with non-linear functions. In the poster, a study of nonlinear unconstrained optimization methods applied to the estimation of the Schumann Resonances will be presented. Non-linear fit, also known as optimization process, is the procedure followed in obtaining Schumann Resonances from the natural electromagnetic noise. The optimization methods that have been analysed are: Levenberg-Marquardt, Conjugate Gradient, Gradient, Newton and Quasi-Newton. The functions that the different methods fit to data are three lorentzian curves plus a straight line. Gaussian curves have also been considered. The conclusions of this study are outlined in the following paragraphs: i) Natural electromagnetic noise is better fitted using Lorentzian functions; ii) the measurement bandwidth can accelerate the convergence of the optimization method; iii) Gradient method has less convergence and has a highest mean squared error (MSE) between measurement and the fitted function, whereas Levenberg-Marquad, Gradient conjugate method and Cuasi-Newton method give similar results (Newton method presents higher MSE); v) There are differences in the MSE between the parameters that define the fit function, and an interval from 1% to 5% has been found.

Density Functional Theory Calculations of the Dissociation of H[2] on (100) 2H-MoS[2] Surfaces: A Key Step in the Hydroprocessing of Crude Oil

ERIC Educational Resources Information Center

Todorova, Teodora; Alexiev, Valentin; Weber, Thomas

2006-01-01

Hydrogen activation on the (100) surface of MoS[2] structures was investigated by means of density functional theory calculations. Linear and quadratic synchronous transit methods with a conjugate gradient refinement of the saddle point were used to localize transition states. The calculations include heterolytic and homolytic dissociation of…

Motion-compensated cone beam computed tomography using a conjugate gradient least-squares algorithm and electrical impedance tomography imaging motion data.

PubMed

Pengpen, T; Soleimani, M

2015-06-13

Cone beam computed tomography (CBCT) is an imaging modality that has been used in image-guided radiation therapy (IGRT). For applications such as lung radiation therapy, CBCT images are greatly affected by the motion artefacts. This is mainly due to low temporal resolution of CBCT. Recently, a dual modality of electrical impedance tomography (EIT) and CBCT has been proposed, in which the high temporal resolution EIT imaging system provides motion data to a motion-compensated algebraic reconstruction technique (ART)-based CBCT reconstruction software. High computational time associated with ART and indeed other variations of ART make it less practical for real applications. This paper develops a motion-compensated conjugate gradient least-squares (CGLS) algorithm for CBCT. A motion-compensated CGLS offers several advantages over ART-based methods, including possibilities for explicit regularization, rapid convergence and parallel computations. This paper for the first time demonstrates motion-compensated CBCT reconstruction using CGLS and reconstruction results are shown in limited data CBCT considering only a quarter of the full dataset. The proposed algorithm is tested using simulated motion data in generic motion-compensated CBCT as well as measured EIT data in dual EIT-CBCT imaging. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A modified conjugate gradient method based on the Tikhonov system for computerized tomography (CT).

PubMed

Wang, Qi; Wang, Huaxiang

2011-04-01

During the past few decades, computerized tomography (CT) was widely used for non-destructive testing (NDT) and non-destructive examination (NDE) in the industrial area because of its characteristics of non-invasiveness and visibility. Recently, CT technology has been applied to multi-phase flow measurement. Using the principle of radiation attenuation measurements along different directions through the investigated object with a special reconstruction algorithm, cross-sectional information of the scanned object can be worked out. It is a typical inverse problem and has always been a challenge for its nonlinearity and ill-conditions. The Tikhonov regulation method is widely used for similar ill-posed problems. However, the conventional Tikhonov method does not provide reconstructions with qualities good enough, the relative errors between the reconstructed images and the real distribution should be further reduced. In this paper, a modified conjugate gradient (CG) method is applied to a Tikhonov system (MCGT method) for reconstructing CT images. The computational load is dominated by the number of independent measurements m, and a preconditioner is imported to lower the condition number of the Tikhonov system. Both simulation and experiment results indicate that the proposed method can reduce the computational time and improve the quality of image reconstruction. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Solving groundwater flow problems by conjugate-gradient methods and the strongly implicit procedure

USGS Publications Warehouse

Hill, Mary C.

1990-01-01

The performance of the preconditioned conjugate-gradient method with three preconditioners is compared with the strongly implicit procedure (SIP) using a scalar computer. The preconditioners considered are the incomplete Cholesky (ICCG) and the modified incomplete Cholesky (MICCG), which require the same computer storage as SIP as programmed for a problem with a symmetric matrix, and a polynomial preconditioner (POLCG), which requires less computer storage than SIP. Although POLCG is usually used on vector computers, it is included here because of its small storage requirements. In this paper, published comparisons of the solvers are evaluated, all four solvers are compared for the first time, and new test cases are presented to provide a more complete basis by which the solvers can be judged for typical groundwater flow problems. Based on nine test cases, the following conclusions are reached: (1) SIP is actually as efficient as ICCG for some of the published, linear, two-dimensional test cases that were reportedly solved much more efficiently by ICCG; (2) SIP is more efficient than other published comparisons would indicate when common convergence criteria are used; and (3) for problems that are three-dimensional, nonlinear, or both, and for which common convergence criteria are used, SIP is often more efficient than ICCG, and is sometimes more efficient than MICCG.

Bundle block adjustment of large-scale remote sensing data with Block-based Sparse Matrix Compression combined with Preconditioned Conjugate Gradient

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhang, Yongjun; Zhou, Shunping; Zhu, Junfeng; Xiong, Xiaodong

2016-07-01

In recent years, new platforms and sensors in photogrammetry, remote sensing and computer vision areas have become available, such as Unmanned Aircraft Vehicles (UAV), oblique camera systems, common digital cameras and even mobile phone cameras. Images collected by all these kinds of sensors could be used as remote sensing data sources. These sensors can obtain large-scale remote sensing data which consist of a great number of images. Bundle block adjustment of large-scale data with conventional algorithm is very time and space (memory) consuming due to the super large normal matrix arising from large-scale data. In this paper, an efficient Block-based Sparse Matrix Compression (BSMC) method combined with the Preconditioned Conjugate Gradient (PCG) algorithm is chosen to develop a stable and efficient bundle block adjustment system in order to deal with the large-scale remote sensing data. The main contribution of this work is the BSMC-based PCG algorithm which is more efficient in time and memory than the traditional algorithm without compromising the accuracy. Totally 8 datasets of real data are used to test our proposed method. Preliminary results have shown that the BSMC method can efficiently decrease the time and memory requirement of large-scale data.

Modeling of Field-Aligned Guided Echoes in the Plasmasphere

NASA Technical Reports Server (NTRS)

Fung, Shing F.; Green, James L.

2004-01-01

The conditions under which high frequency (f>>f(sub uh)) long-range extraordinary-mode discrete field-aligned echoes observed by the Radio Plasma Imager (RPI) on board the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite in the plasmasphere are investigated by ray tracing modeling. Field-aligned discrete echoes are most commonly observed by RPI in the plasmasphere although they are also observed over the polar cap region. The plasmasphere field-aligned echoes appearing as multiple echo traces at different virtual ranges are attributed to signals reflected successively between conjugate hemispheres that propagate along or nearly along closed geomagnetic field lines. The ray tracing simulations show that field-aligned ducts with as little as 1% density perturbations (depletions) and less than 10 wavelengths wide can guide nearly field-aligned propagating high frequency X mode waves. Effective guidance of wave at a given frequency and wave normal angle (Psi) depends on the cross-field density scale of the duct, such that ducts with stronger density depletions need to be wider in order to maintain the same gradient of refractive index across the magnetic field. While signal guidance by field aligned density gradient without ducting is possible only over the polar region, conjugate field-aligned echoes that have traversed through the equatorial region are most likely guided by ducting.

Uptake and intracellular fate of [14C]sucrose-insulin in perfused rat livers.

PubMed

Surmacz, C A; Wert, J J; Ward, W F; Mortimore, G E

1988-07-01

Insulin was covalently linked to [14C]sucrose by means of cyanuric chloride to provide a label that would remain entrapped within the vacuolar system. The uptake of the conjugate by the perfused rat liver was rapid (half-life = 2.9 min), competitively inhibited by native insulin, and abolished by alkali denaturation. As assessed by its distribution on self-generating gradients of colloidal silica-povidone, label in lysosome-enriched samples of liver taken at different times after the addition of the conjugate moved progressively during 15 min from the plasma membrane into an intermediate peak and then to dense lysosomal fractions. After 30-60 min, the label had equilibrated throughout the lysosomal-vacuolar system. The initial movement from the plasma membrane to the intermediate peak occurred between 2 and 5 min. Because label in the peak could be physically separated from the lysosomal marker, beta-acetylglucosaminidase, by dispersing the sample through the gradient mixture before centrifugation rather than layering it, we concluded that the intermediate particles in question were not lysosomal in nature. On gel-filtration chromatography, label extracted from the intermediate peak did not move with insulin but rather as a broad band of lower molecular weight products, suggesting that insulin is subject to early proteolytic attack within a nonlysosomal compartment.

Optimization of computations for adjoint field and Jacobian needed in 3D CSEM inversion

NASA Astrophysics Data System (ADS)

Dehiya, Rahul; Singh, Arun; Gupta, Pravin K.; Israil, M.

2017-01-01

We present the features and results of a newly developed code, based on Gauss-Newton optimization technique, for solving three-dimensional Controlled-Source Electromagnetic inverse problem. In this code a special emphasis has been put on representing the operations by block matrices for conjugate gradient iteration. We show how in the computation of Jacobian, the matrix formed by differentiation of system matrix can be made independent of frequency to optimize the operations at conjugate gradient step. The coarse level parallel computing, using OpenMP framework, is used primarily due to its simplicity in implementation and accessibility of shared memory multi-core computing machine to almost anyone. We demonstrate how the coarseness of modeling grid in comparison to source (comp`utational receivers) spacing can be exploited for efficient computing, without compromising the quality of the inverted model, by reducing the number of adjoint calls. It is also demonstrated that the adjoint field can even be computed on a grid coarser than the modeling grid without affecting the inversion outcome. These observations were reconfirmed using an experiment design where the deviation of source from straight tow line is considered. Finally, a real field data inversion experiment is presented to demonstrate robustness of the code.

Assessment of Linear Finite-Difference Poisson-Boltzmann Solvers

PubMed Central

Wang, Jun; Luo, Ray

2009-01-01

CPU time and memory usage are two vital issues that any numerical solvers for the Poisson-Boltzmann equation have to face in biomolecular applications. In this study we systematically analyzed the CPU time and memory usage of five commonly used finite-difference solvers with a large and diversified set of biomolecular structures. Our comparative analysis shows that modified incomplete Cholesky conjugate gradient and geometric multigrid are the most efficient in the diversified test set. For the two efficient solvers, our test shows that their CPU times increase approximately linearly with the numbers of grids. Their CPU times also increase almost linearly with the negative logarithm of the convergence criterion at very similar rate. Our comparison further shows that geometric multigrid performs better in the large set of tested biomolecules. However, modified incomplete Cholesky conjugate gradient is superior to geometric multigrid in molecular dynamics simulations of tested molecules. We also investigated other significant components in numerical solutions of the Poisson-Boltzmann equation. It turns out that the time-limiting step is the free boundary condition setup for the linear systems for the selected proteins if the electrostatic focusing is not used. Thus, development of future numerical solvers for the Poisson-Boltzmann equation should balance all aspects of the numerical procedures in realistic biomolecular applications. PMID:20063271

TV-based conjugate gradient method and discrete L-curve for few-view CT reconstruction of X-ray in vivo data

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

Yang, Xiaoli; Hofmann, Ralf; Dapp, Robin

2015-01-01

High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration of in vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce the numbermore » of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation. (C) 2015 Optical Society of America« less

Characterization of minimal sequences associated with self-similar interval exchange maps

NASA Astrophysics Data System (ADS)

Cobo, Milton; Gutiérrez-Romo, Rodolfo; Maass, Alejandro

2018-04-01

The construction of affine interval exchange maps (IEMs) with wandering intervals that are semi-conjugate to a given self-similar IEM is strongly related to the existence of the so-called minimal sequences associated with local potentials, which are certain elements of the substitution subshift arising from the given IEM. In this article, under the condition called unique representation property, we characterize such minimal sequences for potentials coming from non-real eigenvalues of the substitution matrix. We also give conditions on the slopes of the affine extensions of a self-similar IEM that determine whether it exhibits a wandering interval or not.

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

Fine-scale features in the far-field of a turbulent jet

NASA Astrophysics Data System (ADS)

Buxton, Oliver; Ganapathisubramani, Bharathram

2008-11-01

The structure of a fully turbulent axisymmetric jet, at Reynolds number based on jet exit conditions of 5000, is investigated with cinematographic (1 kHz) stereoscopic PIV in a plane normal to the jet axis. Taylor's hypothesis is employed to calculate all three velocity gradients in the axial direction. The technique's resolution allows all terms of the velocity gradient tensor, hence strain rate tensor and kinetic energy dissipation, to be computed at each point within the plane. The data reveals that the vorticity field is dominated by high enstrophy tube-like structures. Conversely, the dissipation field appears to consist of sheet-like structures. Several criteria for isolating these strongly swirling vortical structures from the background turbulence were employed. One such technique involves isolating points in which the velocity gradient tensor has a real and a pair of complex conjugate eigenvectors. Once identified, the alignment of the various structures with relation to the vorticity vector and the real velocity gradient tensor eigenvector is investigated. The effect of the strain field on the geometry of the structures is also examined.

Mapping interactions between the RNA chaperone FinO and its RNA targets

PubMed Central

Arthur, David C.; Tsutakawa, Susan; Tainer, John A.; Frost, Laura S.; Glover, J. N. Mark

2011-01-01

Bacterial conjugation is regulated by two-component repression comprising the antisense RNA FinP, and its protein co-factor FinO. FinO mediates base-pairing of FinP to the 5′-untranslated region (UTR) of traJ mRNA, which leads to translational inhibition of the transcriptional activator TraJ and subsequent down regulation of conjugation genes. Yet, little is known about how FinO binds to its RNA targets or how this interaction facilitates FinP and traJ mRNA pairing. Here, we use solution methods to determine how FinO binds specifically to its minimal high affinity target, FinP stem–loop II (SLII), and its complement SLIIc from traJ mRNA. Ribonuclease footprinting reveals that FinO contacts the base of the stem and the 3′ single-stranded tails of these RNAs. The phosphorylation or oxidation of the 3′-nucleotide blocks FinO binding, suggesting FinO binds the 3′-hydroxyl of its RNA targets. The collective results allow the generation of an energy-minimized model of the FinO–SLII complex, consistent with small-angle X-ray scattering data. The repression complex model was constrained using previously reported cross-linking data and newly developed footprinting results. Together, these data lead us to propose a model of how FinO mediates FinP/traJ mRNA pairing to down regulate bacterial conjugation. PMID:21278162

Fluorescence in vivo imaging of live tumor cells with pH-activatable targeted probes via receptor-mediated endocytosis

NASA Astrophysics Data System (ADS)

Asanuma, Daisuke; Urano, Yasuteru; Nagano, Tetsuo; Hama, Yukihiro; Koyama, Yoshinori; Kobayashi, Hisataka

2009-02-01

One goal of molecular imaging is to establish a widely applicable technique for specific detection of tumors with minimal background. Here, we achieve specific in vivo tumor visualization with a newly-designed "activatable" targeted fluorescence probe. This agent is activated after cellular internalization by sensing the pH change in the lysosome. Novel acidic pH-activatable probes based on the BODIPY fluorophore were synthesized, and then conjugated to a cancer-targeting monoclonal antibody, Trastuzumab, or galactosyl serum albumin (GSA). As proof of concept, ex and in vivo imaging of two different tumor mouse models was performed: HER2-overexpressed lung metastasis tumor with Trastuzumab-pH probe conjugates and lectin-overexpressed i.p. disseminated tumor with GSA-pH probe conjugates. These pH-activatable targeted probes were highly specific for tumors with minimal background signal. Because the acidic pH in lysosomes is maintained by the energy-consuming proton pump, only viable cancer cells were successfully visualized. Furthermore, this strategy was also applied to fluorescence endoscopy in tumor mouse models, resulting in specific visualization of tumors as small as submillimeter in size that could hardly detected by naked eyes because of their poor contrast against normal tissues. The design concept can be widely adapted to cancer-specific cell-surface-targeting molecules that result in cellular internalization.

Multivalent conjugates of basic fibroblast growth factor enhance in vitro proliferation and migration of endothelial cells.

PubMed

Zbinden, Aline; Browne, Shane; Altiok, Eda I; Svedlund, Felicia L; Jackson, Wesley M; Healy, Kevin E

2018-05-01

Growth factors hold great promise for regenerative therapies. However, their clinical use has been halted by poor efficacy and rapid clearance from tissue, necessitating the delivery of extremely high doses to achieve clinical effectiveness which has raised safety concerns. Thus, strategies to either enhance growth factor activity at low doses or to increase their residence time within target tissues are necessary for clinical success. In this study, we generated multivalent conjugates (MVCs) of basic fibroblast growth factor (bFGF), a key growth factor involved in angiogenesis and wound healing, to hyaluronic acid (HyA) polymer chains. Multivalent bFGF conjugates (mvbFGF) were fabricated with minimal non-specific interaction observed between bFGF and the HyA chain. The hydrodynamic radii of mvbFGF ranged from ∼50 to ∼75 nm for conjugation ratios of bFGF to HyA chains at low (10 : 1) and high (30 : 1) feed ratios, respectively. The mvbFGF demonstrated enhanced bioactivity compared to unconjugated bFGF in assays of cell proliferation and migration, processes critical to angiogenesis and tissue regeneration. The 30 : 1 mvbFGF outperformed the 10 : 1 conjugate, which could be due to either FGF receptor clustering or interference with receptor mediated internalization and signal deactivation. This study simultaneously investigated the role of both protein to polymer ratio and multivalent conjugate size on their bioactivity, and determined that increasing the protein-to-polymer ratio and conjugate size resulted in greater cell bioactivity.

Experimental design to optimize an Haemophilus influenzae type b conjugate vaccine made with hydrazide-derivatized tetanus toxoid.

PubMed

Laferriere, Craig; Ravenscroft, Neil; Wilson, Seanette; Combrink, Jill; Gordon, Lizelle; Petre, Jean

2011-10-01

The introduction of type b Haemophilus influenzae conjugate vaccines into routine vaccination schedules has significantly reduced the burden of this disease; however, widespread use in developing countries is constrained by vaccine costs, and there is a need for a simple and high-yielding manufacturing process. The vaccine is composed of purified capsular polysaccharide conjugated to an immunogenic carrier protein. To improve the yield and rate of the reductive amination conjugation reaction used to make this vaccine, some of the carboxyl groups of the carrier protein, tetanus toxoid, were modified to hydrazides, which are more reactive than the ε -amine of lysine. Other reaction parameters, including the ratio of the reactants, the size of the polysaccharide, the temperature and the salt concentration, were also investigated. Experimental design was used to minimize the number of experiments required to optimize all these parameters to obtain conjugate in high yield with target characteristics. It was found that increasing the reactant ratio and decreasing the size of the polysaccharide increased the polysaccharide:protein mass ratio in the product. Temperature and salt concentration did not improve this ratio. These results are consistent with a diffusion controlled rate limiting step in the conjugation reaction. Excessive modification of tetanus toxoid with hydrazide was correlated with reduced yield and lower free polysaccharide. This was attributed to a greater tendency for precipitation, possibly due to changes in the isoelectric point. Experimental design and multiple regression helped identify key parameters to control and thereby optimize this conjugation reaction.

Phototodynamic activity of zinc monocarboxyphenoxy phthalocyane (ZnMCPPc) conjugated to gold silver (AuAg) nanoparticles in melanoma cancer cells

NASA Astrophysics Data System (ADS)

Manoto, Sello L.; Oluwole, David O.; Malabi, Rudzani; Maphanga, Charles; Ombinda-Lemboumba, Saturnin; Nyokong, Tebello; Mthunzi-Kufa, Patience

2017-02-01

Photodynamic therapy (PDT) is a minimally invasive therapeutic modality for the treatment of neoplastic and non-neoplastic diseases. In PDT of cancer, irradiation with light of a specific wavelength leads to activation of a photosensitizer which results in generation of reactive oxygen species (ROS) which induces cell death. Many phthalocyanine photosensitizers are hydrophobic and insoluble in water, which limits their therapeutic efficiency. Consequently, advanced delivery systems and strategies are needed to improve the effectiveness of these photosensitizers. Nanoparticles have shown promising results in increasing aqueous solubility, bioavailability, stability and delivery of photosensitizers to their target. This study investigated the photodynamic activity of zinc monocarboxyphenoxy phthalocyanine (ZnMCPPc) conjugated to gold silver (AuAg) nanoparticles in melanoma cancer cells. The photodynamic activity of ZnMCPPc conjugated to AuAg nanoparticles were evaluated using cellular morphology, viability, proliferation and cytotoxicity. Untreated cells showed no changes in cellular morphology, proliferation and cytotoxicity. However, photoactivated ZnMCPPc conjugated to AuAg nanoparticles showed changes in cell morphology and a dose dependent decrease in cellular viability, proliferation and an increase in cell membrane damage. The ZnMCPPc conjugated to AuAg nanoparticles used in this study was highly effective in inducing cell death of melanoma cancer cells.

Intracellular delivery and antitumor effects of a redox-responsive polymeric paclitaxel conjugate based on hyaluronic acid.

PubMed

Yin, Shaoping; Huai, Jue; Chen, Xi; Yang, Yong; Zhang, Xinxin; Gan, Yong; Wang, Guangji; Gu, Xiaochen; Li, Juan

2015-10-01

Polymer-drug conjugates have demonstrated application potentials in optimizing chemotherapeutics. In this study a new bioconjugate, HA-ss-PTX, was designed and synthesized with cooperative dual characteristics of active tumor targeting and selective intracellular drug release. Paclitaxel (PTX) was covalently attached to hyaluronic acid (HA) with various sizes (MW 9.5, 35, 770 kDa); a cross-linker containing disulfide bond was also used to shield drug leakage in blood circulation and to achieve rapid drug release in tumor cells in response to glutathione. Incorporation of HA to the conjugate enhanced the capabilities of drug loading, intracellular endocytosis and tumor targeting of micelles in comparison to mPEG. HA molecular weight showed significant effect on properties and antitumor efficacy of the synthesized conjugates. Intracellular uptake of HA-ss-PTX toward MCF-7 cells was mediated by CD44-caveolae-mediated endocytosis. Compared to Taxol and mPEG-ss-PTX, HA9.5-ss-PTX demonstrated improved tumor growth inhibition in vivo with a TIR of 83.27 ± 5.20%. It was concluded that HA9.5-ss-PTX achieved rapid intracellular release of PTX and enhanced its therapeutic efficacy, thus providing a platform for specific drug targeting and controlled intracellular release in chemotherapeutics. Polymer-drug conjugates, promising nanomedicines, still face some technical challenges including a lack of specific targeting and rapid intracellular drug release at the target site. In this manuscript we designed and constructed a novel bioconjugate HA-ss-PTX, which possessed coordinated dual characteristics of active tumor targeting and selective intracellular drug release. Redox-responsive disulfide bond was introduced to the conjugate to shield drug leakage in blood circulation and to achieve rapid drug release at tumor site in response to reductant like glutathione. Paclitaxel was selected as a model drug to be covalently attached to hyaluronic acid (HA) with various sizes to elucidate the structure-activity relationship and to address whether HA could substitute PEG as a carrier for polymeric conjugates. Based on a series of in vitro and in vivo experiments, HA-ss-PTX performed well in drug loading, cellular internalization, tumor targeting by entering tumor cells via CD44-caveolae-mediated endocytosis and rapidly release drug at target in the presence of GSH. One of the key issues in clinical oncology is to enhance drug delivery efficacy while minimizing side effects. The study indicated that this new polymeric conjugate system would be useful in delivering anticancer agents to improve therapeutic efficacy and to minimize adverse effects, thus providing a platform for specific drug targeting and controlled intracellular release in chemotherapeutics. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Calixarene-Mediated Liquid-Membrane Transport of Choline Conjugates.

PubMed

Adhikari, Birendra Babu; Fujii, Ayu; Schramm, Michael P

2014-05-01

A series of supramolecular calixarenes efficiently transport distinct molecular species through a liquid membrane when attached to a receptor-complementary choline handle. Calix-[6]arene hexacarboxylic acid was highly effective at transporting different target molecules against a pH gradient. Both carboxylic- and phosphonic-acid-functionalized calix[4]arenes effect transport without requiring a pH or ion gradient. NMR binding studies, two-phase solvent extraction, and three-phase transport experiments reveal the necessary and subtle parameters to effect the transport of molecules attached to a choline "handle". On the other hand, rescorin[4]arene cavitands, which have similar guest recognition profiles, did not transport guest molecules. These developments reveal new approaches towards attempting synthetic-receptor-mediated selective small-molecule transport in vesicular and cellular systems.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

PubMed

Chang, Joshua; Paydarfar, David

2014-12-01

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Detection of thermal gradients through fiber-optic Chirped Fiber Bragg Grating (CFBG): Medical thermal ablation scenario

NASA Astrophysics Data System (ADS)

Korganbayev, Sanzhar; Orazayev, Yerzhan; Sovetov, Sultan; Bazyl, Ali; Schena, Emiliano; Massaroni, Carlo; Gassino, Riccardo; Vallan, Alberto; Perrone, Guido; Saccomandi, Paola; Arturo Caponero, Michele; Palumbo, Giovanna; Campopiano, Stefania; Iadicicco, Agostino; Tosi, Daniele

2018-03-01

In this paper, we describe a novel method for spatially distributed temperature measurement with Chirped Fiber Bragg Grating (CFBG) fiber-optic sensors. The proposed method determines the thermal profile in the CFBG region from demodulation of the CFBG optical spectrum. The method is based on an iterative optimization that aims at minimizing the mismatch between the measured CFBG spectrum and a CFBG model based on coupled-mode theory (CMT), perturbed by a temperature gradient. In the demodulation part, we simulate different temperature distribution patterns with Monte-Carlo approach on simulated CFBG spectra. Afterwards, we obtain cost function that minimizes difference between measured and simulated spectra, and results in final temperature profile. Experiments and simulations have been carried out first with a linear gradient, demonstrating a correct operation (error 2.9 °C); then, a setup has been arranged to measure the temperature pattern on a 5-cm long section exposed to medical laser thermal ablation. Overall, the proposed method can operate as a real-time detection technique for thermal gradients over 1.5-5 cm regions, and turns as a key asset for the estimation of thermal gradients at the micro-scale in biomedical applications.

Complex wet-environments in electronic-structure calculations

NASA Astrophysics Data System (ADS)

Fisicaro, Giuseppe; Genovese, Luigi; Andreussi, Oliviero; Marzari, Nicola; Goedecker, Stefan

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of an applied electrochemical potentials, including complex electrostatic screening coming from the solvent. In the present work we present a solver to handle both the Generalized Poisson and the Poisson-Boltzmann equation. A preconditioned conjugate gradient (PCG) method has been implemented for the Generalized Poisson and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations. On the other hand, a self-consistent procedure enables us to solve the Poisson-Boltzmann problem. The algorithms take advantage of a preconditioning procedure based on the BigDFT Poisson solver for the standard Poisson equation. They exhibit very high accuracy and parallel efficiency, and allow different boundary conditions, including surfaces. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and it will be released as a independent program, suitable for integration in other codes. We present test calculations for large proteins to demonstrate efficiency and performances. This work was done within the PASC and NCCR MARVEL projects. Computer resources were provided by the Swiss National Supercomputing Centre (CSCS) under Project ID s499. LG acknowledges also support from the EXTMOS EU project.

Blind Deconvolution of Astronomical Images with a Constraint on Bandwidth Determined by the Parameters of the Optical System

NASA Astrophysics Data System (ADS)

Luo, Lin; Fan, Min; Shen, Mang-zuo

2008-01-01

Atmospheric turbulence severely restricts the spatial resolution of astronomical images obtained by a large ground-based telescope. In order to reduce effectively this effect, we propose a method of blind deconvolution, with a bandwidth constraint determined by the parameters of the telescope's optical system based on the principle of maximum likelihood estimation, in which the convolution error function is minimized by using the conjugate gradient algorithm. A relation between the parameters of the telescope optical system and the image's frequency-domain bandwidth is established, and the speed of convergence of the algorithm is improved by using the positivity constraint on the variables and the limited-bandwidth constraint on the point spread function. To avoid the effective Fourier frequencies exceed the cut-off frequency, it is required that each single image element (e.g., the pixel in the CCD imaging) in the sampling focal plane should be smaller than one fourth of the diameter of the diffraction spot. In the algorithm, no object-centered constraint was used, so the proposed method is suitable for the image restoration of a whole field of objects. By the computer simulation and by the restoration of an actually-observed image of α Piscium, the effectiveness of the proposed method is demonstrated.

Optimal trajectories of aircraft and spacecraft

NASA Technical Reports Server (NTRS)

Miele, A.

1990-01-01

Work done on algorithms for the numerical solutions of optimal control problems and their application to the computation of optimal flight trajectories of aircraft and spacecraft is summarized. General considerations on calculus of variations, optimal control, numerical algorithms, and applications of these algorithms to real-world problems are presented. The sequential gradient-restoration algorithm (SGRA) is examined for the numerical solution of optimal control problems of the Bolza type. Both the primal formulation and the dual formulation are discussed. Aircraft trajectories, in particular, the application of the dual sequential gradient-restoration algorithm (DSGRA) to the determination of optimal flight trajectories in the presence of windshear are described. Both take-off trajectories and abort landing trajectories are discussed. Take-off trajectories are optimized by minimizing the peak deviation of the absolute path inclination from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. The survival capability of an aircraft in a severe windshear is discussed, and the optimal trajectories are found to be superior to both constant pitch trajectories and maximum angle of attack trajectories. Spacecraft trajectories, in particular, the application of the primal sequential gradient-restoration algorithm (PSGRA) to the determination of optimal flight trajectories for aeroassisted orbital transfer are examined. Both the coplanar case and the noncoplanar case are discussed within the frame of three problems: minimization of the total characteristic velocity; minimization of the time integral of the square of the path inclination; and minimization of the peak heating rate. The solution of the second problem is called nearly-grazing solution, and its merits are pointed out as a useful engineering compromise between energy requirements and aerodynamics heating requirements.

MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model -- GMG Linear Equation Solver Package Documentation

USGS Publications Warehouse

Wilson, John D.; Naff, Richard L.

2004-01-01

A geometric multigrid solver (GMG), based in the preconditioned conjugate gradient algorithm, has been developed for solving systems of equations resulting from applying the cell-centered finite difference algorithm to flow in porous media. This solver has been adapted to the U.S. Geological Survey ground-water flow model MODFLOW-2000. The documentation herein is a description of the solver and the adaptation to MODFLOW-2000.

Toward an Integrated Framwork for Data-Efficient Parametric Adaptive Detection

DTIC Science & Technology

2012-02-27

any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a ...SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON a . REPORT...2012-0534 Distribution A - Approved for Public Release The conjugate-gradient (CG) algorithm is investigated for reduced-rank STAP detection. A family

Conjugate Gradient Parametric Detection of Multichannel Signals (Preprint)

DTIC Science & Technology

2012-05-01

aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information...if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YY) 2...processing (STAP) detection is re- examined in this paper. Originally, the PAMF detector was introduced by using a multichannel autoregressive (AR

Benchmarking and tuning the MILC code on clusters and supercomputers

NASA Astrophysics Data System (ADS)

Gottlieb, Steven

2002-03-01

Recently, we have benchmarked and tuned the MILC code on a number of architectures including Intel Itanium and Pentium IV (PIV), dual-CPU Athlon, and the latest Compaq Alpha nodes. Results will be presented for many of these, and we shall discuss some simple code changes that can result in a very dramatic speedup of the KS conjugate gradient on processors with more advanced memory systems such as PIV, IBM SP and Alpha.

Benchmarking and tuning the MILC code on clusters and supercomputers

NASA Astrophysics Data System (ADS)

Gottlieb, Steven

Recently, we have benchmarked and tuned the MILC code on a number of architectures including Intel Itanium and Pentium IV (PIV), dual-CPU Athlon, and the latest Compaq Alpha nodes. Results will be presented for many of these, and we shall discuss some simple code changes that can result in a very dramatic speedup of the KS conjugate gradient on processors with more advanced memory systems such as PIV, IBM SP and Alpha.

2-D weighted least-squares phase unwrapping

DOEpatents

Ghiglia, Dennis C.; Romero, Louis A.

1995-01-01

Weighted values of interferometric signals are unwrapped by determining the least squares solution of phase unwrapping for unweighted values of the interferometric signals; and then determining the least squares solution of phase unwrapping for weighted values of the interferometric signals by preconditioned conjugate gradient methods using the unweighted solutions as preconditioning values. An output is provided that is representative of the least squares solution of phase unwrapping for weighted values of the interferometric signals.

2-D weighted least-squares phase unwrapping

DOEpatents

Ghiglia, D.C.; Romero, L.A.

1995-06-13

Weighted values of interferometric signals are unwrapped by determining the least squares solution of phase unwrapping for unweighted values of the interferometric signals; and then determining the least squares solution of phase unwrapping for weighted values of the interferometric signals by preconditioned conjugate gradient methods using the unweighted solutions as preconditioning values. An output is provided that is representative of the least squares solution of phase unwrapping for weighted values of the interferometric signals. 6 figs.

Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

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

Mory, Cyril, E-mail: cyril.mory@philips.com; Philips Research Medisys, 33 rue de Verdun, 92156 Suresnes; Auvray, Vincent

2014-02-15

Purpose: Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. Methods: The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method,more » which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. Results: 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction. Conclusions: 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.« less

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

NASA Astrophysics Data System (ADS)

Codd, A. L.; Gross, L.

2018-03-01

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

Evaluation of cell-penetrating peptides (CPPs) as vehicles for intracellular delivery of antisense peptide nucleic acid (PNA).

PubMed

Bendifallah, Nadia; Rasmussen, Frank Winther; Zachar, Vladimir; Ebbesen, Peter; Nielsen, Peter E; Koppelhus, Uffe

2006-01-01

Cell-penetrating peptides (CPPs) are characterized by their ability to be internalized in mammalian cells. To investigate the relative potency of CPPs as carriers of medicinally relevant cargo, a positive read-out assay based on the ability of a peptide nucleic acid (PNA) oligomer to promote correct expression of a recombinant luciferase gene was employed. Seven different CPPs were included in the study: Transportan, oligo-arginine (R7-9), pTat, Penetratin, KFF, SynB3, and NLS. The CPP-PNA conjugates were synthesized by different conjugation chemistries: continuous synthesis, maleimide coupling, and ester or disulfide linkage. Under serum-free conditions PNA-SS-Transportan-amide (ortho)-PNA was found to be the most potent conjugate, resulting in maximum luciferase signal at a concentration of 1-2 microM. (D-Arg)9-PNA showed optimal efficacy at 5 microM but gave rise to only one-third of the luciferase signal obtained with the Transportan conjugate. The pTat- and KFF-PNA conjugates showed significantly lower efficacy. The penetratin-, SynB3-. and NLS-PNA conjugates showed only minimal or no activity. Serum was found to have a drastic negative impact on CPP-driven cellular uptake. PNA-SS-Transportan-acid (ortho) and (D-Arg)9-PNA were least sensitive to the presence of serum. Both the chemical nature and, in the case of Transportan, the position of the peptide PNA coupling were found to have a major impact on the transport capacity of the peptides. However, no simple relationship between linker type and antisense activity of the conjugates could be deduced from the data.

Site-Specific Integration of Foreign DNA into Minimal Bacterial and Human Target Sequences Mediated by a Conjugative Relaxase

PubMed Central

Agúndez, Leticia; González-Prieto, Coral; Machón, Cristina; Llosa, Matxalen

2012-01-01

Background Bacterial conjugation is a mechanism for horizontal DNA transfer between bacteria which requires cell to cell contact, usually mediated by self-transmissible plasmids. A protein known as relaxase is responsible for the processing of DNA during bacterial conjugation. TrwC, the relaxase of conjugative plasmid R388, is also able to catalyze site-specific integration of the transferred DNA into a copy of its target, the origin of transfer (oriT), present in a recipient plasmid. This reaction confers TrwC a high biotechnological potential as a tool for genomic engineering. Methodology/Principal Findings We have characterized this reaction by conjugal mobilization of a suicide plasmid to a recipient cell with an oriT-containing plasmid, selecting for the cointegrates. Proteins TrwA and IHF enhanced integration frequency. TrwC could also catalyze integration when it is expressed from the recipient cell. Both Y18 and Y26 catalytic tyrosil residues were essential to perform the reaction, while TrwC DNA helicase activity was dispensable. The target DNA could be reduced to 17 bp encompassing TrwC nicking and binding sites. Two human genomic sequences resembling the 17 bp segment were accepted as targets for TrwC-mediated site-specific integration. TrwC could also integrate the incoming DNA molecule into an oriT copy present in the recipient chromosome. Conclusions/Significance The results support a model for TrwC-mediated site-specific integration. This reaction may allow R388 to integrate into the genome of non-permissive hosts upon conjugative transfer. Also, the ability to act on target sequences present in the human genome underscores the biotechnological potential of conjugative relaxase TrwC as a site-specific integrase for genomic modification of human cells. PMID:22292089

Natural convection in binary gases driven by combined horizontal thermal and vertical solutal gradients

NASA Technical Reports Server (NTRS)

Weaver, J. A.; Viskanta, Raymond

1992-01-01

An investigation of natural convection is presented to examine the influence of a horizontal temperature gradient and a concentration gradient occurring from the bottom to the cold wall in a cavity. As the solutal buoyancy force changes from augmenting to opposing the thermal buoyancy force, the fluid motion switches from unicellular to multicellular flow (fluid motion is up the cold wall and down the hot wall for the bottom counterrotating flow cell). Qualitatively, the agreement between predicted streamlines and smoke flow patterns is generally good. In contrast, agreement between measured and predicted temperature and concentration distributions ranges from fair to poor. Part of the discrepancy can be attributed to experimental error. However, there remains considerable discrepancy between data and predictions due to the idealizations of the mathematical model, which examines only first-order physical effects. An unsteady flow, variable thermophysical properties, conjugate effects, species interdiffusion, and radiation were not accounted for in the model.

Texturing of high T(sub c) superconducting polycrystalline fibers/wires by laser-driven directional solidification in an thermal gradient

NASA Technical Reports Server (NTRS)

Varshney, Usha; Eichelberger, B. Davis, III

1995-01-01

This paper summarizes the technique of laser-driven directional solidification in a controlled thermal gradient of yttria stabilized zirconia core coated Y-Ba-Cu-O materials to produce textured high T(sub c) superconducting polycrystalline fibers/wires with improved critical current densities in the extended range of magnetic fields at temperatures greater than 77 K. The approach involves laser heating to minimize phase segregation by heating very rapidly through the two-phase incongruent melt region to the single phase melt region and directionally solidifying in a controlled thermal gradient to achieve highly textured grains in the fiber axis direction. The technique offers a higher grain growth rate and a lower thermal budget compared with a conventional thermal gradient and is amenable as a continuous process for improving the J(sub c) of high T(sub c) superconducting polycrystalline fibers/wires. The technique has the advantage of suppressing weak-link behavior by orientation of crystals, formation of dense structures with enhanced connectivity, formation of fewer and cleaner grain boundaries, and minimization of phase segregation in the incongruent melt region.

Optimal trajectories for aeroassisted orbital transfer

NASA Technical Reports Server (NTRS)

Miele, A.; Venkataraman, P.

1983-01-01

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

Polymers modified with double-tailed fluorous compounds for efficient DNA and siRNA delivery.

PubMed

He, Bingwei; Wang, Yitong; Shao, Naimin; Chang, Hong; Cheng, Yiyun

2015-08-01

Cationic polymers are widely used as gene carriers, however, these polymers are usually associated with low transfection efficacy and non-negligible toxicity. Fluorination on polymers significantly improves their performances in gene delivery, but a high density of fluorous chains must be conjugated on a single polymer. Here we present a new strategy to construct fluorinated polymers with minimal fluorous chains for efficient DNA and siRNA delivery. A double-tailed fluorous compound 2-chloro-4,6-bis[(perfluorohexyl)propyloxy]-1,3,5-triazine (CBT) was conjugated on dendrimers of different generations and low molecular weight polyethylenimine via a facile synthesis. The yielding products with average numbers of 1-2 conjugated CBT moieties showed much improved EGFP and luciferase transfection efficacy compared to unmodified polymers. In addition, these polymers show high siRNA delivery efficacy on different cell lines. Among the synthesized polymers, generation 1 (G1) dendrimer modified with an average number of 1.9 CBT moieties (G1-CBT1.9) shows the highest efficacy when delivering both DNA and siRNA and its efficacy approaches that of Lipofectamine 2000. G1-CBT1.9 also shows efficient gene silencing in vivo. All of the CBT-modified polymers exhibit minimal toxicity on the cells at their optimal transfection conditions. This study provides a new strategy to design efficient fluorous polymers for DNA and siRNA delivery. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Pyrrole-hyaluronic acid conjugates for decreasing cell binding to metals and conducting polymers

PubMed Central

Lee, Jae Young; Schmidt, Christine E.

2010-01-01

Surface modification of electrically conductive biomaterials has been studied to improve biocompatibility for a number of applications, such as implantable sensors and microelectrode arrays. In this study, we electrochemically coated electrodes with biocompatible and non-cell adhesive hyaluronic acid (HA) to reduce cellular adhesion for potential use in neural prostheses. To this end, pyrrole-conjugated hyaluronic acid (PyHA) was synthesized and employed for electrochemical coating of platinum, indium-tin-oxide, and polystyrene sulfonate-doped polypyrrole electrodes. This PyHA conjugate consists of (1) a pyrrole moiety that allows the compound to be electrochemically deposited onto a conductive substrate and (2) non-adhesive HA to minimize cell adhesion and to potentially decrease inflammatory tissue responses. Our characterization results showed the presence of a hydrophilic p(PyHA) layer on the modified electrode, and impedance measurements revealed impedance that was statistically the same as the unmodified electrode. We found that the p(PyHA)-coated electrodes minimized adhesion and migration of fibroblasts and astrocytes for a minimum of up to 3 months. Also, the coating was stable in physiological solution for 3 months and also stable against enzymatic degradation by hyaluronidase. These studies suggest that this p(PyHA)-coating has the potential to be used to mask conducting electrodes from adverse glial responses that occur upon implantation. In addition, electrochemical coating with PyHA can be potentially extended for the surface modification of other metallic and conducting substances such as stents and biosensors. PMID:20558330

Conformational analysis of a polyconjugated protein-binding ligand by joint quantum chemistry and polarizable molecular mechanics. Addressing the issues of anisotropy, conjugation, polarization, and multipole transferability.

PubMed

Goldwaser, Elodie; de Courcy, Benoit; Demange, Luc; Garbay, Christiane; Raynaud, Françoise; Hadj-Slimane, Reda; Piquemal, Jean-Philip; Gresh, Nohad

2014-11-01

We investigate the conformational properties of a potent inhibitor of neuropilin-1, a protein involved in cancer processes and macular degeneration. This inhibitor consists of four aromatic/conjugated fragments: a benzimidazole, a methylbenzene, a carboxythiourea, and a benzene-linker dioxane, and these fragments are all linked together by conjugated bonds. The calculations use the SIBFA polarizable molecular mechanics procedure. Prior to docking simulations, it is essential to ensure that variations in the ligand conformational energy upon rotations around its six main-chain torsional bonds are correctly represented (as compared to high-level ab initio quantum chemistry, QC). This is done in two successive calibration stages and one validation stage. In the latter, the minima identified following independent stepwise variations of each of the six main-chain torsion angles are used as starting points for energy minimization of all the torsion angles simultaneously. Single-point QC calculations of the minimized structures are then done to compare their relative energies ΔE conf to the SIBFA ones. We compare three different methods of deriving the multipoles and polarizabilities of the central, most critical moiety of the inhibitor: carboxythiourea (CTU). The representation that gives the best agreement with QC is the one that includes the effects of the mutual polarization energy E pol between the amide and thioamide moieties. This again highlights the critical role of this contribution. The implications and perspectives of these findings are discussed.

E2~Ub conjugates regulate the kinase activity of Shigella effector OspG during pathogenesis

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

Pruneda, Jonathan N.; Smith, F. Donelson; Daurie, Angela

Pathogenic bacteria introduce effector proteins directly into the cytosol of eukaryotic cells to promote invasion and colonization. OspG, a Shigella spp. effector kinase, plays a role in this process by helping to suppress the host inflammatory response. OspG has been reported to bind host E2 ubiquitin-conjugating enzymes activated with ubiquitin (E2~Ub), a key enzyme complex in ubiquitin transfer pathways. A cocrystal structure of the OspG/UbcH5c~Ub complex reveals that complex formation has important ramifications for the activity of both OspG and the UbcH5c~Ub conjugate. OspG is a minimal kinase domain containing only essential elements required for catalysis. UbcH5c~Ub binding stabilizes anmore » active conformation of the kinase, greatly enhancing OspG kinase activity. In contrast, interaction with OspG stabilizes an extended, less reactive form of UbcH5c~Ub. Recognizing conserved E2 features, OspG can interact with at least ten distinct human E2s~Ub. Mouse oral infection studies indicate that E2~Ub conjugates act as novel regulators of OspG effector kinase function in eukaryotic host cells.« less

Iterative algorithms for large sparse linear systems on parallel computers

NASA Technical Reports Server (NTRS)

Adams, L. M.

1982-01-01

Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1985-01-01

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.

Calixarene-Mediated Liquid-Membrane Transport of Choline Conjugates

PubMed Central

Adhikari, Birendra Babu; Fujii, Ayu

2015-01-01

A series of supramolecular calixarenes efficiently transport distinct molecular species through a liquid membrane when attached to a receptor-complementary choline handle. Calix-[6]arene hexacarboxylic acid was highly effective at transporting different target molecules against a pH gradient. Both carboxylic- and phosphonic-acid-functionalized calix[4]arenes effect transport without requiring a pH or ion gradient. NMR binding studies, two-phase solvent extraction, and three-phase transport experiments reveal the necessary and subtle parameters to effect the transport of molecules attached to a choline “handle”. On the other hand, rescorin[4]arene cavitands, which have similar guest recognition profiles, did not transport guest molecules. These developments reveal new approaches towards attempting synthetic-receptor-mediated selective small-molecule transport in vesicular and cellular systems. PMID:26161034

User intent prediction with a scaled conjugate gradient trained artificial neural network for lower limb amputees using a powered prosthesis.

PubMed

Woodward, Richard B; Spanias, John A; Hargrove, Levi J

2016-08-01

Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming. By using subject independent datasets, whereby a unique subject is tested against a pooled dataset of other subjects, we believe subject training time can be reduced while still achieving an accurate classification. We present here an intent recognition system using an artificial neural network (ANN) with a scaled conjugate gradient learning algorithm to classify gait intention with user-dependent and independent datasets for six unilateral lower limb amputees. We compare these results against a linear discriminant analysis (LDA) classifier. The ANN was found to have significantly lower classification error (P<;0.05) than LDA with all user-dependent step-types, as well as transitional steps for user-independent datasets. Both types of classifiers are capable of making fast decisions; 1.29 and 2.83 ms for the LDA and ANN respectively. These results suggest that ANNs can provide suitable and accurate offline classification in prosthesis gait prediction.

Practical method development for the separation of monoclonal antibodies and antibody-drug-conjugate species in hydrophobic interaction chromatography, part 1: optimization of the mobile phase.

PubMed

Rodriguez-Aller, Marta; Guillarme, Davy; Beck, Alain; Fekete, Szabolcs

2016-01-25

The goal of this work is to provide some recommendations for method development in HIC using monoclonal antibodies (mAbs) and antibody-drug conjugates (ADCs) as model drug candidates. The effects of gradient steepness, mobile phase pH, salt concentration and type, as well as organic modifier were evaluated for tuning selectivity and retention in HIC. Except the nature of the stationary phase, which was not discussed in this study, the most important parameter for modifying selectivity was the gradient steepness. The addition of organic solvent (up to 15% isopropanol) in the mobile phase was also found to be useful for mAbs analysis, since it could provide some changes in elution order, in some cases. On the contrary, isopropanol was not beneficial with ADCs, since the most hydrophobic DAR species (DAR6 and DAR8) cannot be eluted from the stationary phase under these conditions. This study also illustrates the possibility to perform HIC method development using optimization software, such as Drylab. The optimum conditions suggested by the software were tested using therapeutic mAbs and commercial cysteine linked ADC (brentuximab-vedotin) and the average retention time errors between predicted and experimental retention times were ∼ 1%. Copyright © 2015 Elsevier B.V. All rights reserved.

A finite element: Boundary integral method for electromagnetic scattering. Ph.D. Thesis Technical Report, Feb. - Sep. 1992

NASA Technical Reports Server (NTRS)

Collins, J. D.; Volakis, John L.

1992-01-01

A method that combines the finite element and boundary integral techniques for the numerical solution of electromagnetic scattering problems is presented. The finite element method is well known for requiring a low order storage and for its capability to model inhomogeneous structures. Of particular emphasis in this work is the reduction of the storage requirement by terminating the finite element mesh on a boundary in a fashion which renders the boundary integrals in convolutional form. The fast Fourier transform is then used to evaluate these integrals in a conjugate gradient solver, without a need to generate the actual matrix. This method has a marked advantage over traditional integral equation approaches with respect to the storage requirement of highly inhomogeneous structures. Rectangular, circular, and ogival mesh termination boundaries are examined for two-dimensional scattering. In the case of axially symmetric structures, the boundary integral matrix storage is reduced by exploiting matrix symmetries and solving the resulting system via the conjugate gradient method. In each case several results are presented for various scatterers aimed at validating the method and providing an assessment of its capabilities. Important in methods incorporating boundary integral equations is the issue of internal resonance. A method is implemented for their removal, and is shown to be effective in the two-dimensional and three-dimensional applications.

Modeling of field-aligned guided echoes in the plasmasphere

NASA Astrophysics Data System (ADS)

Fung, Shing F.; Green, James L.

2005-01-01

Ray tracing modeling is used to investigate the plasma conditions under which high-frequency (f ≫ fuh) extraordinary mode waves can be guided along geomagnetic field lines. These guided signals have often been observed as long-range discrete echoes in the plasmasphere by the Radio Plasma Imager (RPI) onboard the Imager for Magnetopause-to-Aurora Global Exploration satellite. Field-aligned discrete echoes are most commonly observed by RPI in the plasmasphere, although they are also observed over the polar cap region. The plasmasphere field-aligned echoes appearing as multiple echo traces at different virtual ranges are attributed to signals reflected successively between conjugate hemispheres that propagate along or nearly along closed geomagnetic field lines. The ray tracing simulations show that field-aligned ducts with as little as 1% density perturbations (depletions) and <10 wavelengths wide can guide nearly field-aligned propagating high-frequency X mode waves. Effective guidance of a wave at a given frequency and wave normal angle (Ψ) depends on the cross-field density scale of the duct, such that ducts with stronger density depletions need to be wider in order to maintain the same gradient of refractive index across the magnetic field. While signal guidance by field aligned density gradient without ducting is possible only over the polar region, conjugate field-aligned echoes that have traversed through the equatorial region are most likely guided by ducting.

Pixel-based OPC optimization based on conjugate gradients.

PubMed

Ma, Xu; Arce, Gonzalo R

2011-01-31

Optical proximity correction (OPC) methods are resolution enhancement techniques (RET) used extensively in the semiconductor industry to improve the resolution and pattern fidelity of optical lithography. In pixel-based OPC (PBOPC), the mask is divided into small pixels, each of which is modified during the optimization process. Two critical issues in PBOPC are the required computational complexity of the optimization process, and the manufacturability of the optimized mask. Most current OPC optimization methods apply the steepest descent (SD) algorithm to improve image fidelity augmented by regularization penalties to reduce the complexity of the mask. Although simple to implement, the SD algorithm converges slowly. The existing regularization penalties, however, fall short in meeting the mask rule check (MRC) requirements often used in semiconductor manufacturing. This paper focuses on developing OPC optimization algorithms based on the conjugate gradient (CG) method which exhibits much faster convergence than the SD algorithm. The imaging formation process is represented by the Fourier series expansion model which approximates the partially coherent system as a sum of coherent systems. In order to obtain more desirable manufacturability properties of the mask pattern, a MRC penalty is proposed to enlarge the linear size of the sub-resolution assistant features (SRAFs), as well as the distances between the SRAFs and the main body of the mask. Finally, a projection method is developed to further reduce the complexity of the optimized mask pattern.

Ordering effects of conjugate thermal fields in simulations of molecular liquids: Carbon dioxide and water

NASA Astrophysics Data System (ADS)

Dittmar, Harro R.; Kusalik, Peter G.

2016-10-01

As shown previously, it is possible to apply configurational and kinetic thermostats simultaneously in order to induce a steady thermal flux in molecular dynamics simulations of many-particle systems. This flux appears to promote motion along potential gradients and can be utilized to enhance the sampling of ordered arrangements, i.e., it can facilitate the formation of a critical nucleus. Here we demonstrate that the same approach can be applied to molecular systems, and report a significant enhancement of the homogeneous crystal nucleation of a carbon dioxide (EPM2 model) system. Quantitative ordering effects and reduction of the particle mobilities were observed in water (TIP4P-2005 model) and carbon dioxide systems. The enhancement of the crystal nucleation of carbon dioxide was achieved with relatively small conjugate thermal fields. The effect is many orders of magnitude bigger at milder supercooling, where the forward flux sampling method was employed, than at a lower temperature that enabled brute force simulations of nucleation events. The behaviour exhibited implies that the effective free energy barrier of nucleation must have been reduced by the conjugate thermal field in line with our interpretation of previous results for atomic systems.

An efficient sequential strategy for realizing cross-gradient joint inversion: method and its application to 2-D cross borehole seismic traveltime and DC resistivity tomography

NASA Astrophysics Data System (ADS)

Gao, Ji; Zhang, Haijiang

2018-05-01

Cross-gradient joint inversion that enforces structural similarity between different models has been widely utilized in jointly inverting different geophysical data types. However, it is a challenge to combine different geophysical inversion systems with the cross-gradient structural constraint into one joint inversion system because they may differ greatly in the model representation, forward modelling and inversion algorithm. Here we propose a new joint inversion strategy that can avoid this issue. Different models are separately inverted using the existing inversion packages and model structure similarity is only enforced through cross-gradient minimization between two models after each iteration. Although the data fitting and structural similarity enforcing processes are decoupled, our proposed strategy is still able to choose appropriate models to balance the trade-off between geophysical data fitting and structural similarity. This is realized by using model perturbations from separate data inversions to constrain the cross-gradient minimization process. We have tested this new strategy on 2-D cross borehole synthetic seismic traveltime and DC resistivity data sets. Compared to separate geophysical inversions, our proposed joint inversion strategy fits the separate data sets at comparable levels while at the same time resulting in a higher structural similarity between the velocity and resistivity models.

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

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Baysal, Oktay

1997-01-01

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

Photosensitizer (PS)-cyanine dye (CD) conjugates: Impact of the linkers joining the PS and CD moieties and their orientation in tumor-uptake and photodynamic therapy (PDT).

PubMed

James, Nadine S; Joshi, Penny; Ohulchanskyy, Tymish Y; Chen, Yihui; Tabaczynski, Walter; Durrani, Farukh; Shibata, Masayuki; Pandey, Ravindra K

2016-10-21

To investigate the impact of linker(s) joining the photosensitizer HPPH [3-(1'-hexyloxy) ethyl-3-devinylpyropheophorbide-a] and the cyanine dye (CD) in tumor-imaging and photodynamic therapy (dual-function agents), a series of HPPH-CD conjugates were synthesized. The modifications were done in an attempt to minimize Forster Resonance Energy Transfer (FRET) between the two chromophores and maximize singlet oxygen production. Among the conjugates containing variable length of linkers, the HPPH-CD conjugate, in which the photosensitizer (PS) and the CD was joined by four Carbon [(CH2)4] units showed higher tumor uptake, improved tumor contrast and limited skin uptake in mice bearing Colon-26 (BALB/c) or U87 tumors in Nude mice. The bi-functional agents in which the HPPH was linked at the meta-position of phenyl-substituted CD 5, 6 and 7 showed longer tumor response (cure) than the corresponding para-substituted analogs 2, 3, and 4, which suggests that the orientation of the PS and CD moieties within the conjugate also makes a substantial difference in tumor-specificity. Compared to HPPH, the singlet oxygen yields of all the HPPH-CD conjugates were significantly low, and required a higher therapeutic dose to achieve the same in vivo response obtained by HPPH-PDT alone. However, conjugate 6 produced a higher singlet oxygen yield with reduced FRET and exhibited enhanced long-term PDT efficacy in mice bearing Colon-26 (BALB/c) and U87 tumors (nude) than its counterparts, including our lead compound (HPPH-CD), making it the most efficacious of the series. Thus, these conjugates bearing cyanine dye moiety (CD) provide an opportunity of imaging deeply seated tumors for fluorescence-guided surgery with an option of PDT. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

A facile means for the identification of indolic compounds from plant tissues.

PubMed

Yu, Peng; Hegeman, Adrian D; Cohen, Jerry D

2014-09-01

The bulk of indole-3-acetic acid (IAA) in plants is found in the form of conjugated molecules, yet past research on identifying these compounds has largely relied on methods that were both laborious and inefficient. Using recent advances in analytical instrumentation, we have developed a simple yet powerful liquid chromatography-mass spectrometry (LC-MS)-based method for the facile characterization of the small IAA conjugate profile of plants. The method uses the well-known quinolinium ion (m/z 130.0651) generated in MS processes as a signature with high mass accuracy that can be used to screen plant extracts for indolic compounds, including IAA conjugates. We reinvestigated Glycine max (soybean) for its indoles and found indole-3-acetyl-trytophan (IA-Trp) in addition to the already known indole-3-acetyl-aspartic acid (IA-Asp) and indole-3-acetyl-glutamic acid (IA-Glu) conjugates. Surprisingly, several organic acid conjugates of tryptophan were also discovered, many of which have not been reported in planta before. These compounds may have important physiological roles in tryptophan metabolism, which in turn can affect human nutrition. We also demonstrated the general applicability of this method by identifying indolic compounds in different plant tissues of diverse phylogenetic origins. It involves minimal sample preparation but can work in conjunction with sample enrichment techniques. This method enables quick screening of IAA conjugates in both previously characterized as well as uncharacterized species, and facilitates the identification of indolic compounds in general. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Structural optimization with approximate sensitivities

NASA Technical Reports Server (NTRS)

Patnaik, S. N.; Hopkins, D. A.; Coroneos, R.

1994-01-01

Computational efficiency in structural optimization can be enhanced if the intensive computations associated with the calculation of the sensitivities, that is, gradients of the behavior constraints, are reduced. Approximation to gradients of the behavior constraints that can be generated with small amount of numerical calculations is proposed. Structural optimization with these approximate sensitivities produced correct optimum solution. Approximate gradients performed well for different nonlinear programming methods, such as the sequence of unconstrained minimization technique, method of feasible directions, sequence of quadratic programming, and sequence of linear programming. Structural optimization with approximate gradients can reduce by one third the CPU time that would otherwise be required to solve the problem with explicit closed-form gradients. The proposed gradient approximation shows potential to reduce intensive computation that has been associated with traditional structural optimization.

A frequency dependent preconditioned wavelet method for atmospheric tomography

NASA Astrophysics Data System (ADS)

Yudytskiy, Mykhaylo; Helin, Tapio; Ramlau, Ronny

2013-12-01

Atmospheric tomography, i.e. the reconstruction of the turbulence in the atmosphere, is a main task for the adaptive optics systems of the next generation telescopes. For extremely large telescopes, such as the European Extremely Large Telescope, this problem becomes overly complex and an efficient algorithm is needed to reduce numerical costs. Recently, a conjugate gradient method based on wavelet parametrization of turbulence layers was introduced [5]. An iterative algorithm can only be numerically efficient when the number of iterations required for a sufficient reconstruction is low. A way to achieve this is to design an efficient preconditioner. In this paper we propose a new frequency-dependent preconditioner for the wavelet method. In the context of a multi conjugate adaptive optics (MCAO) system simulated on the official end-to-end simulation tool OCTOPUS of the European Southern Observatory we demonstrate robustness and speed of the preconditioned algorithm. We show that three iterations are sufficient for a good reconstruction.

High-density sub-100-nm peptide-gold nanoparticle complexes improve vaccine presentation by dendritic cells in vitro.

PubMed

Lin, Adam Yuh; Lunsford, Jessica; Bear, Adham Sean; Young, Joseph Keith; Eckels, Phillip; Luo, Laureen; Foster, Aaron Edward; Drezek, Rebekah Anna

2013-02-12

Nanocarriers have been explored to improve the delivery of tumor antigens to dendritic cells (DCs). Gold nanoparticles are attractive nanocarriers because they are inert, non-toxic, and can be readily endocytosed by DCs. Here, we designed novel gold-based nanovaccines (AuNVs) using a simple self-assembling bottom-up conjugation method to generate high-peptide density delivery and effective immune responses with limited toxicity. AuNVs were synthesized using a self-assembling conjugation method and optimized using DC-to-splenocyte interferon-γ enzyme-linked immunosorbent spot assays. The AuNV design has shown successful peptide conjugation with approximately 90% yield while remaining smaller than 80 nm in diameter. DCs uptake AuNVs with minimal toxicity and are able to process the vaccine peptides on the particles to stimulate cytotoxic T lymphocytes (CTLs). These high-peptide density AuNVs can stimulate CTLs better than free peptides and have great potential as carriers for various vaccine types.

Folate receptor‐targeted aminoglycoside‐derived polymers for transgene expression in cancer cells

PubMed Central

Godeshala, Sudhakar; Nitiyanandan, Rajeshwar; Thompson, Brian; Goklany, Sheba; Nielsen, David R.

2016-01-01

Abstract Targeted delivery of anticancer therapeutics can potentially overcome the limitations associated with current chemotherapeutic regimens. Folate receptors are overexpressed in several cancers, including ovarian, triple‐negative breast and bladder cancers, making them attractive for targeted delivery of nucleic acid therapeutics to these tumors. This work describes the synthesis, characterization and evaluation of folic acid‐conjugated, aminoglycoside‐derived polymers for targeted delivery of transgenes to breast and bladder cancer cell lines. Transgene expression was significantly higher with FA‐conjugated aminoglycoside‐derived polymers than with Lipofectamine, and these polymers demonstrated minimal cytotoxicty. Competitive inhibition using free folic acid significantly reduced transgene expression efficacy of folate‐targeted polymers, suggesting a role for folate receptor‐mediated uptake. High efficacy FA‐targeted polymers were employed to deliver a plasmid expressing the TRAIL protein, which induced death in cancer cells. These results indicate that FA‐conjugated aminoglycoside‐derived polymers are promising for targeted delivery of nucleic acids to cancer cells that overexpress folate receptors. PMID:29313013

High-density sub-100-nm peptide-gold nanoparticle complexes improve vaccine presentation by dendritic cells in vitro

NASA Astrophysics Data System (ADS)

Lin, Adam Yuh; Lunsford, Jessica; Bear, Adham Sean; Young, Joseph Keith; Eckels, Phillip; Luo, Laureen; Foster, Aaron Edward; Drezek, Rebekah Anna

2013-02-01

Nanocarriers have been explored to improve the delivery of tumor antigens to dendritic cells (DCs). Gold nanoparticles are attractive nanocarriers because they are inert, non-toxic, and can be readily endocytosed by DCs. Here, we designed novel gold-based nanovaccines (AuNVs) using a simple self-assembling bottom-up conjugation method to generate high-peptide density delivery and effective immune responses with limited toxicity. AuNVs were synthesized using a self-assembling conjugation method and optimized using DC-to-splenocyte interferon-γ enzyme-linked immunosorbent spot assays. The AuNV design has shown successful peptide conjugation with approximately 90% yield while remaining smaller than 80 nm in diameter. DCs uptake AuNVs with minimal toxicity and are able to process the vaccine peptides on the particles to stimulate cytotoxic T lymphocytes (CTLs). These high-peptide density AuNVs can stimulate CTLs better than free peptides and have great potential as carriers for various vaccine types.

Development and application of a UPLC-MS/MS method for the pharmacokinetic study of 10-hydroxy camptothecin and hydroxyethyl starch conjugate in rats.

PubMed

Li, Guofei; Cai, Cuifang; Ren, Tianyang; Tang, Xing

2014-01-01

With the purpose to carry out the pharmacokinetic studies of 10-hydroxy camptothecin (10-HCPT) and hydroxyethyl starch (10-HCPT-HES) conjugate, an ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method has been developed and validated. The analytes, 10-HCPT and the internal standard, Diphenhydramine hydrochloride were extracted with ethyl acetate-isopropanol (95:5, v/v) and separated on an ACQUITY UPLC™ BEH C18 column using a mobile phase composed of acetonitrile and water (containing 0.1% formic acid) with a linear gradient program. With positive ion electrospray ionization (ESI), the analytes were monitored on a triple quadrupole mass spectrometer in the multiple reaction monitoring (MRM) mode. Linear calibration curves were obtained over the concentration ranges of 0.5-2500ng/mL. The intra- and inter-day precisions were less than 9.8% and 10.8%, respectively. The accuracy was within 12.1%. The mean recoveries of 10-HCPT at three concentrations of 2.5, 100, 2000ng/mL were higher than 87.2%. Commercial 10-HCPT injection and 10-HCPT-HES conjugate were administered intravenously at an equal dose of 10-HCPT at 0.5mg/kg. The biological half-life of conjugate was increased significantly from 10min to 3.15h and the bioavailability was 40 times higher than 10-HCPT injection. Consequently, the proposed UPLC-ESI-MS/MS method was proved to be sensitive, specific and reliable to analyze 10-HCPT in biological samples; 10-HCPT and HES conjugate is a promising strategy for delivery of 10-HCPT with prolonged half time and improved bioavailability. Copyright © 2013 Elsevier B.V. All rights reserved.

Grafting PNIPAAm from β-barrel shaped transmembrane nanopores.

PubMed

Charan, Himanshu; Kinzel, Julia; Glebe, Ulrich; Anand, Deepak; Garakani, Tayebeh Mirzaei; Zhu, Leilei; Bocola, Marco; Schwaneberg, Ulrich; Böker, Alexander

2016-11-01

The research on protein-polymer conjugates by grafting from the surface of proteins has gained significant interest in the last decade. While there are many studies with globular proteins, membrane proteins have remained untouched to the best of our knowledge. In this study, we established the conjugate formation with a class of transmembrane proteins and grow polymer chains from the ferric hydroxamate uptake protein component A (FhuA; a β-barrel transmembrane protein of Escherichia coli). As the lysine residues of naturally occurring FhuA are distributed over the whole protein, FhuA was reengineered to have up to 11 lysines, distributed symmetrically in a rim on the membrane exposed side (outside) of the protein channel and exclusively above the hydrophobic region. Reengineering of FhuA ensures a polymer growth only on the outside of the β-barrel and prevents blockage of the channel as a result of the polymerization. A water-soluble initiator for controlled radical polymerization (CRP) was consecutively linked to the lysine residues of FhuA and N-isopropylacrylamide (NIPAAm) polymerized under copper-mediated CRP conditions. The conjugate formation was analyzed by using MALDI-ToF mass spectrometry, SDS-PAGE, circular dichroism spectroscopy, analytical ultracentrifugation, dynamic light scattering, transmission electron microscopy and size exclusion chromatography. Such conjugates combine the specific functions of the transmembrane proteins, like maintaining membrane potential gradients or translocation of substrates with the unique properties of synthetic polymers such as temperature and pH stimuli handles. FhuA-PNIPAAm conjugates will serve as functional nanosized building blocks for applications in targeted drug delivery, self-assembly systems, functional membranes and transmembrane protein gated nanoreactors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Imperfect coupling between northern and southern ionospheres: asymmetry in TEC anomalies before earthquakes

NASA Astrophysics Data System (ADS)

Jhuang, Hau-Kun; Ho, Yi-Ying; Lee, Lou-Chuang

2016-04-01

The northern ionosphere is coupled to the conjugate southern ionosphere through the highly conducting geomagenetic field lines. The coupling is very strong or "perfect" if the geomagnetic field lines are equipotential (the parallel electric field E||=0) and hence the perpendicular electric field (E⊥) at the conjugate sites of both ionospheres are equal. The coupling is "imperfect" if some of the geomagnetic field lines are non-equipotential (E||≠0). The field-aligned electric field E|| can be associated with electron inertia, pressure gradient and collisions appearing in the form of double layer, kinetic Alfvén waves and finite field-aligned conductivity σ||. We use the Global Ionospheric Maps (GIM) data to examine the conjugate effect of total electron content (TEC) for six significant earthquakes. The anomalous (ΔTEC)source in the source ionosphere and (ΔTEC)conjugate in the conjugate ionosphere are obtained for 85 events before the six earthquakes. The ΔTEC ratio β = (ΔTEC)conjugate / (ΔTEC)source is calculated for each anomaly. For a "perfect" coupling, β=1. There are 85 anomalous events before the six significant earthquakes, with 62 events occurring in the daytime (07-18 LT) and 23 events in the nighttime (19-06 LT). The average value of daytime (07-18 LT) TEC variations in the source ionosphere is |ΔTEC|source =20.13 TECu, while the average value in the nighttime (19-06 LT) ionosphere is |ΔTEC|source=14.43 TECu. The value of ΔTEC ratio β ranges from 0.05 (very weak coupling) to 0.98 (nearly perfect coupling) with an average of 0.52. There are 14 strong coupling cases with β ≥0.8, which take place from 11 LT to 19 LT. The daytime (07-18 LT) β average value is 0.57 and the nighttime (19-06 LT) β average is 0.37. The south-north ionosphere coupling is stronger (weaker) in the daytime (nighttime).

Experimental feasibility of investigating acoustic waves in Couette flow with entropy and pressure gradients

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Zorumski, William E.; Rawls, John W., Jr.

1990-01-01

The feasibility is discussed for an experimental program for studying the behavior of acoustic wave propagation in the presence of strong gradients of pressure, temperature, and flow. Theory suggests that gradients effects can be experimentally observed as resonant frequency shifts and mode shape changes in a waveguide. A convenient experimental geometry for such experiments is the annular region between two co-rotating cylinders. Radial temperature gradients in a spinning annulus can be generated by differentially heating the two cylinders via electromagnetic induction. Radial pressure gradients can be controlled by varying the cylinder spin rates. Present technology appears adequate to construct an apparatus to allow independent control of temperature and pressure gradients. A complicating feature of a more advanced experiment, involving flow gradients, is the requirement for independently controlled cylinder spin rates. Also, the boundary condition at annulus terminations must be such that flow gradients are minimally disturbed. The design and construction of an advanced apparatus to include flow gradients will require additional technology development.

Biominetic High Density Lipoproteins for the Delivery of Therapeutic Oligonucleotides

NASA Astrophysics Data System (ADS)

Tripathy, Sushant

Advances in nanotechnology have brought about novel inorganic and hybrid nanoparticles with unique physico-chemical properties that make them suitable for a broad range of applications---from nano-circuitry to drug delivery. A significant part of those advancements have led to ground-breaking discoveries that have changed the approaches to formulation of therapeutics against diseases, such as cancer. Now-a-days the focus does not lie solely on finding a candidate small-molecule therapeutic with minimal adverse effects, but researchers are looking up to nanoparticles to improve biodistribution and biocompatibility profile of clinically proven therapeutics. The plethora of conjugation chemistries offered by currently extant inorganic nanoparticles have, in recent years, led to great leaps in the field of biomimicry---a modality that promises high biocompatibility. Further, in the pursuit of highly specific therapeutic molecules, researchers have turned to silencing oligonucleotides and some have already brought together the strengths of nanoparticles and silencing oligonucleotides in search of an efficacious therapy for cancer with minimal adverse effects. This dissertation work focuses on such a biomimetic platform---a gold nanoparticle based high density lipoprotein biomimetic (HDL NP), for the delivery of therapeutic oligonucleotides. The first chapter of this body of work introduces the molecular target of the silencing oligonucleotides---VEGFR2, and its role in the progression of solid tumor cancers. The background information also covers important aspects of natural high density lipoproteins (HDL), especially their innate capacity to bind and deliver exogenous and endogenous silencing oligonucleotides to tissues that express their high affinity receptor SRB1. We subsequently describe the synthesis of the biomimetic HDL NP and its oligonucleotide conjugates, and establish their biocompatibility. Further on, experimental data demonstrate the efficacy of silencing oligonucleotides conjugated HDL NPs in regulating the expression and function of VEGFR2 in cultured endothelial cells. Finally, the efficacy of the conjugates in two animal models of angiogenesis is presented.

Non-classical continuum theory for fluids incorporating internal and Cosserat rotation rates

NASA Astrophysics Data System (ADS)

Surana, K. S.; Joy, A. D.; Reddy, J. N.

2017-11-01

This paper presents a non-classical continuum theory for fluent continua in which the conservation and balance laws are derived by incorporating both internal rotation rates arising from the velocity gradient tensor and the rotation rates of the Cosserats. Specifically, in this non-classical continuum theory we have (1) the usual velocities (\\bar{ ±b {\\varvec{v }}}), (2) the three internal rotation rates ({}_i^t\\bar{ ±b {\\varvec{Θ }}}) about the axes of a fixed triad whose axes are parallel to the x-frame arising from the velocity gradient tensor (\\bar{ ±b {\\varvec{L }}}) that are completely defined by the antisymmetric part of the velocity gradient tensor, and (3) three additional rotation rates ({}_e^t\\bar{ ±b {\\varvec{Θ }}}) about the axes of the same triad located at each material point as additional three unknown degrees of freedom, referred to as Cosserat rotation rates. This gives rise to \\bar{ ±b {\\varvec{v }}} and {}_e^t\\bar{ ±b {\\varvec{Θ }}} as six degrees of freedom at a material point. The internal rotation rates {}_i^t\\bar{ ±b {\\varvec{Θ }}}, often neglected in classical fluid mechanics, exist in all deforming fluent continua as these are due to velocity gradient tensor. When the internal rotation rates {}_i^t\\bar{ ±b {\\varvec{Θ }}} are resisted by deforming fluent continua, conjugate moment tensor arises that together with {}_i^t\\bar{ ±b {\\varvec{Θ }}} may result in energy storage and/or dissipation, which must be considered in the conservation and balance laws. The Cosserat rotation rations {}_e^t\\bar{ ±b {\\varvec{Θ }}} also result in conjugate moment tensor that together with {}_e^t\\bar{ ±b {\\varvec{Θ }}} may also result in energy storage and/or dissipation. The main focus of this paper is a consistent derivation of conservation and balance laws for fluent continua that incorporate the aforementioned physics and associated constitutive theories for thermofluids using the conditions resulting from the entropy inequality. The material coefficients derived in the constitutive theories are clearly defined and discussed.

New Langevin and gradient thermostats for rigid body dynamics.

PubMed

Davidchack, R L; Ouldridge, T E; Tretyakov, M V

2015-04-14

We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator.

Interpolation algorithm for asynchronous ADC-data

NASA Astrophysics Data System (ADS)

Bramburger, Stefan; Zinke, Benny; Killat, Dirk

2017-09-01

This paper presents a modified interpolation algorithm for signals with variable data rate from asynchronous ADCs. The Adaptive weights Conjugate gradient Toeplitz matrix (ACT) algorithm is extended to operate with a continuous data stream. An additional preprocessing of data with constant and linear sections and a weighted overlap of step-by-step into spectral domain transformed signals improve the reconstruction of the asycnhronous ADC signal. The interpolation method can be used if asynchronous ADC data is fed into synchronous digital signal processing.

Identification of the Thermal Conductivity Coefficient for Quasi-Stationary Two-Dimensional Heat Conduction Equations

NASA Astrophysics Data System (ADS)

Matsevityi, Yu. M.; Alekhina, S. V.; Borukhov, V. T.; Zayats, G. M.; Kostikov, A. O.

2017-11-01

The problem of identifying the time-dependent thermal conductivity coefficient in the initial-boundary-value problem for the quasi-stationary two-dimensional heat conduction equation in a bounded cylinder is considered. It is assumed that the temperature field in the cylinder is independent of the angular coordinate. To solve the given problem, which is related to a class of inverse problems, a mathematical approach based on the method of conjugate gradients in a functional form is being developed.

Curved-line search algorithm for ab initio atomic structure relaxation

NASA Astrophysics Data System (ADS)

Chen, Zhanghui; Li, Jingbo; Li, Shushen; Wang, Lin-Wang

2017-09-01

Ab initio atomic relaxations often take large numbers of steps and long times to converge, especially when the initial atomic configurations are far from the local minimum or there are curved and narrow valleys in the multidimensional potentials. An atomic relaxation method based on on-the-flight force learning and a corresponding curved-line search algorithm is presented to accelerate this process. Results demonstrate the superior performance of this method for metal and magnetic clusters when compared with the conventional conjugate-gradient method.

D4Z - a new renumbering for iterative solution of ground-water flow and solute- transport equations

USGS Publications Warehouse

Kipp, K.L.; Russell, T.F.; Otto, J.S.

1992-01-01

D4 zig-zag (D4Z) is a new renumbering scheme for producing a reduced matrix to be solved by an incomplete LU preconditioned, restarted conjugate-gradient iterative solver. By renumbering alternate diagonals in a zig-zag fashion, a very low sensitivity of convergence rate to renumbering direction is obtained. For two demonstration problems involving groundwater flow and solute transport, iteration counts are related to condition numbers and spectra of the reduced matrices.

Mapping the Conjugate Gradient Algorithm onto High Performance Heterogeneous Computers

DTIC Science & Technology

2014-05-01

Matrix Storage Formats According to J . Dongarra (Dongerra 2000), the efficiency of most iterative methods, such as CG, can be attributed to the...valh = aij) ⇒ (colh = j ). The ptr integer vector is of length n + 1 and contains the index in val where each matrix row starts. For example, the...first nonzero element of matrix rowm is found at index ptrm of val. By convention, ptrn+1 ≡ nz + 1. Notice that (aij) ⇒ (ptri ≤ j < ptri+1) for all i. An

Image Understanding Workshop. Proceedings of a Workshop Held in Los Angeles, California on 23-25 February 1987. Volume 2

DTIC Science & Technology

1987-02-25

Modellierung von Kanten bei unregel. Navigation within a building, to be published in IEEE mifliger Rasterung in Bildverarbeitun uand Muster...converted them into equivalent machine cycles in Table 3-1. We took into account of 100 nanosecond 0 - 0, machine cycle time of the MPP. In MPP, NON- VON ...We show the result for the conjugate gradient method in of NON- VON . We assumed that the instructions which carry Table 4-4. The computation of four

Higher Integrability for Minimizers of the Mumford-Shah Functional

NASA Astrophysics Data System (ADS)

De Philippis, Guido; Figalli, Alessio

2014-08-01

We prove higher integrability for the gradient of local minimizers of the Mumford-Shah energy functional, providing a positive answer to a conjecture of De Giorgi (Free discontinuity problems in calculus of variations. Frontiers in pure and applied mathematics, North-Holland, Amsterdam, pp 55-62, 1991).

Thermal Design to Meet Stringent Temperature Gradient/Stability Requirements of SWIFT BAT Detectors

NASA Technical Reports Server (NTRS)

Choi, Michael K.

2000-01-01

The Burst Alert Telescope (BAT) is an instrument on the National Aeronautics and Space Administration (NASA) SWIFT spacecraft. It is designed to detect gamma ray burst over a broad region of the sky and quickly align the telescopes on the spacecraft to the gamma ray source. The thermal requirements for the BAT detector arrays are very stringent. The maximum allowable temperature gradient of the 256 cadmium zinc telluride (CZT) detectors is PC. Also, the maximum allowable rate of temperature change of the ASICs of the 256 Detector Modules (DMs) is PC on any time scale. The total power dissipation of the DMs and Block Command & Data Handling (BCDH) is 180 W. This paper presents a thermal design that uses constant conductance heat pipes (CCHPs) to minimize the temperature gradient of the DMs, and loop heat pipes (LHPs) to transport the waste heat to the radiator. The LHPs vary the effective thermal conductance from the DMs to the radiator to minimize heater power to meet the heater power budget, and to improve the temperature stability. The DMs are cold biased, and active heater control is used to meet the temperature gradient and stability requirements.

Role of central and peripheral opiate receptors in the effects of fentanyl on analgesia, ventilation and arterial blood-gas chemistry in conscious rats

PubMed Central

Henderson, Fraser; May, Walter J.; Gruber, Ryan B.; Discala, Joseph F.; Puscovic, Veljko; Young, Alex P.; Baby, Santhosh M.; Lewis, Stephen J.

2015-01-01

This study determined the effects of the peripherally restricted µ-opiate receptor (µ-OR) antagonist, naloxone methiodide (NLXmi) on fentanyl (25 µg/kg, i.v.)-induced changes in (1) analgesia, (2) arterial blood gas chemistry (ABG) and alveolar-arterial gradient (A-a gradient), and (3) ventilatory parameters, in conscious rats. The fentanyl-induced increase in analgesia was minimally affected by a 1.5 mg/kg of NLXmi but was attenuated by a 5.0 mg/kg dose. Fentanyl decreased arterial blood pH, pO2 and sO2 and increased pCO2 and A-a gradient. These responses were markedly diminished in NLXmi (1.5 mg/kg)-pretreated rats. Fentanyl caused ventilatory depression (e.g., decreases in tidal volume and peak inspiratory flow). Pretreatment with NLXmi (1.5 mg/kg, i.v.) antagonized the fentanyl decrease in tidal volume but minimally affected the other responses. These findings suggest that (1) the analgesia and ventilatory depression caused by fentanyl involve peripheral µ-ORs and (2) NLXmi prevents the fentanyl effects on ABG by blocking the negative actions of the opioid on tidal volume and A-a gradient. PMID:24284037

Surface chemistry of photoluminescent F8BT conjugated polymer nanoparticles determines protein corona formation and internalization by phagocytic cells.

PubMed

Ahmad Khanbeigi, Raha; Abelha, Thais Fedatto; Woods, Arcadia; Rastoin, Olivia; Harvey, Richard D; Jones, Marie-Christine; Forbes, Ben; Green, Mark A; Collins, Helen; Dailey, Lea Ann

2015-03-09

Conjugated polymer nanoparticles are being developed for a variety of diagnostic and theranostic applications. The conjugated polymer, F8BT, a polyfluorene derivative, was used as a model system to examine the biological behavior of conjugated polymer nanoparticle formulations stabilized with ionic (sodium dodecyl sulfate; F8BT-SDS; ∼207 nm; -31 mV) and nonionic (pegylated 12-hydroxystearate; F8BT-PEG; ∼175 nm; -5 mV) surfactants, and compared with polystyrene nanoparticles of a similar size (PS200; ∼217 nm; -40 mV). F8BT nanoparticles were as hydrophobic as PS200 (hydrophobic interaction chromatography index value: 0.96) and showed evidence of protein corona formation after incubation with serum-containing medium; however, unlike polystyrene, F8BT nanoparticles did not enrich specific proteins onto the nanoparticle surface. J774A.1 macrophage cells internalized approximately ∼20% and ∼60% of the F8BT-SDS and PS200 delivered dose (calculated by the ISDD model) in serum-supplemented and serum-free conditions, respectively, while cell association of F8BT-PEG was minimal (<5% of the delivered dose). F8BT-PEG, however, was more cytotoxic (IC50 4.5 μg cm(-2)) than F8BT-SDS or PS200. The study results highlight that F8BT surface chemistry influences the composition of the protein corona, while the properties of the conjugated polymer nanoparticle surfactant stabilizer used determine particle internalization and biocompatibility profile.

In Vitro and In Vivo Analysis of Indocyanine Green-Labeled Panitumumab for Optical Imaging—A Cautionary Tale

PubMed Central

2015-01-01

Indocyanine green (IC-Green), the only FDA approved near-infrared (NIR) fluorophore for clinical use, is attractive to researchers for the development of targeted optical imaging agents by modification of its structure and conjugation to monoclonal antibodies (mAbs) or their fragments. IC-Green derivative, ICG-sulfo-OSu (ICG-sOSu), is frequently used for antibody conjugation. However, ICG-sOSu is amphiphilic and readily facilitates aggregation of mAbs that is not easily separable from the desired immunoconjugates. Complications originating from this behavior are frequently overlooked by researchers. This study examined detailed chemical and biological characteristics of an ICG-sOSu-labeled mAb, panitumumab, and provided a clinically applicable strategy to deliver a pure conjugation product. Size-exclusion high-performance liquid chromatography (SE-HPLC) analysis of conjugation reactions, performed at molar reaction ratios of ICG-sOSu: mAb of 5, 10, or 20, resulted in isolable desired ICG-sOSu-panitumumab conjugation product in 72%, 53%, and 19% yields, respectively, with the remainder consisting of high molecular weight aggregates (>150 kDa) 14%, 30%, and 51%, respectively. The HPLC-purified ICG-sOSu-panitumumab products were analyzed by native and SDS polyacrylamide gel electrophoresis (PAGE) followed by optical imaging. Results indicated that the interaction between ICG-sOSu and panitumumab was due to both covalent and noncovalent binding of the ICG-sOSu to the protein. Noncovalently bound dye in the ICG-sOSu-panitumumab conjugate products was removed by extraction with ethyl acetate to further purify the HPLC-isolated conjugation products. With conserved immunoreactivity, excellent target-specific uptake of the doubly purified bioconjugates was observed with minimal liver retention in athymic nude mice bearing HER1-expressing tumor xenografts. In summary, the preparation of well-defined bioconjugate products labeled with commercial ICG-sOSu dye is not a simple process and control of the conjugation reaction ratio and conditions is crucial. Furthermore, absolute purification and characterization of the products is necessitated prior to in vivo optical imaging. Use of validated and characterized dye conjugate products should facilitate the development of clinically viable and reproducible IC-Green derivative and other NIR dye mAb conjugates for optical imaging applications. PMID:25243604

In vitro and in vivo analysis of indocyanine green-labeled panitumumab for optical imaging-a cautionary tale.

PubMed

Zhou, Yang; Kim, Young-Seung; Milenic, Diane E; Baidoo, Kwamena E; Brechbiel, Martin W

2014-10-15

Indocyanine green (IC-Green), the only FDA approved near-infrared (NIR) fluorophore for clinical use, is attractive to researchers for the development of targeted optical imaging agents by modification of its structure and conjugation to monoclonal antibodies (mAbs) or their fragments. IC-Green derivative, ICG-sulfo-OSu (ICG-sOSu), is frequently used for antibody conjugation. However, ICG-sOSu is amphiphilic and readily facilitates aggregation of mAbs that is not easily separable from the desired immunoconjugates. Complications originating from this behavior are frequently overlooked by researchers. This study examined detailed chemical and biological characteristics of an ICG-sOSu-labeled mAb, panitumumab, and provided a clinically applicable strategy to deliver a pure conjugation product. Size-exclusion high-performance liquid chromatography (SE-HPLC) analysis of conjugation reactions, performed at molar reaction ratios of ICG-sOSu: mAb of 5, 10, or 20, resulted in isolable desired ICG-sOSu-panitumumab conjugation product in 72%, 53%, and 19% yields, respectively, with the remainder consisting of high molecular weight aggregates (>150 kDa) 14%, 30%, and 51%, respectively. The HPLC-purified ICG-sOSu-panitumumab products were analyzed by native and SDS polyacrylamide gel electrophoresis (PAGE) followed by optical imaging. Results indicated that the interaction between ICG-sOSu and panitumumab was due to both covalent and noncovalent binding of the ICG-sOSu to the protein. Noncovalently bound dye in the ICG-sOSu-panitumumab conjugate products was removed by extraction with ethyl acetate to further purify the HPLC-isolated conjugation products. With conserved immunoreactivity, excellent target-specific uptake of the doubly purified bioconjugates was observed with minimal liver retention in athymic nude mice bearing HER1-expressing tumor xenografts. In summary, the preparation of well-defined bioconjugate products labeled with commercial ICG-sOSu dye is not a simple process and control of the conjugation reaction ratio and conditions is crucial. Furthermore, absolute purification and characterization of the products is necessitated prior to in vivo optical imaging. Use of validated and characterized dye conjugate products should facilitate the development of clinically viable and reproducible IC-Green derivative and other NIR dye mAb conjugates for optical imaging applications.

Microgravity Particle Dynamics

NASA Technical Reports Server (NTRS)

Clark, Ivan O.; Johnson, Edward J.

1996-01-01

This research seeks to identify the experiment design parameters for future flight experiments to better resolve the effects of thermal and velocity gradients on gas-solid flows. By exploiting the reduced body forces and minimized thermal convection current of reduced gravity experiments, features of gas-solid flow normally masked by gravitationally induced effects can be studied using flow regimes unattainable under unigravity. This paper assesses the physical scales of velocity, length, time, thermal gradient magnitude, and velocity gradient magnitude likely to be involved in laminar gas-solid multiphase flight experiments for 1-100 micro-m particles.

Gradient-based adaptation of general gaussian kernels.

PubMed

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

Echo planar imaging at 4 Tesla with minimum acoustic noise.

PubMed

Tomasi, Dardo G; Ernst, Thomas

2003-07-01

To minimize the acoustic sound pressure levels of single-shot echo planar imaging (EPI) acquisitions on high magnetic field MRI scanners. The resonance frequencies of gradient coil vibrations, which depend on the coil length and the elastic properties of the materials in the coil assembly, were measured using piezoelectric transducers. The frequency of the EPI-readout train was adjusted to avoid the frequency ranges of mechanical resonances. Our MRI system exhibited two sharp mechanical resonances (at 720 and 1220 Hz) that can increase vibrational amplitudes up to six-fold. A small adjustment of the EPI-readout frequency made it possible to reduce the sound pressure level of EPI-based perfusion and functional MRI scans by 12 dB. Normal vibrational modes of MRI gradient coils can dramatically increase the sound pressure levels during echo planar imaging (EPI) scans. To minimize acoustic noise, the frequency of EPI-readout trains and the resonance frequencies of gradient coil vibrations need to be different. Copyright 2003 Wiley-Liss, Inc.

Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance.

PubMed

Cilliers, Cornelius; Nessler, Ian; Christodolu, Nikolas; Thurber, Greg M

2017-05-01

Monoclonal antibodies labeled with near-infrared (NIR) fluorophores have potential use in disease detection, intraoperative imaging, and pharmacokinetic characterization of therapeutic antibodies in both the preclinical and clinical setting. Recent work has shown conjugation of NIR fluorophores to antibodies can potentially alter antibody disposition at a sufficiently high degree of labeling (DoL); however, other reports show minimal impact after labeling with NIR fluorophores. In this work, we label two clinically approved antibodies, Herceptin (trastuzumab) and Avastin (bevacizumab), with NIR dyes IRDye 800CW (800CW) or Alexa Fluor 680 (AF680), at 1.2 and 0.3 dyes/antibody and examine the impact of fluorophore conjugation on antibody plasma clearance and tissue distribution. At 0.3 DoL, AF680 conjugates exhibited similar clearance to unlabeled antibody over 17 days while 800CW conjugates diverged after 4 days, suggesting AF680 is a more suitable choice for long-term pharmacokinetic studies. At the 1.2 DoL, 800CW conjugates cleared faster than unlabeled antibodies after several hours, in agreement with other published reports. The tissue biodistribution for bevacizumab-800CW and -AF680 conjugates agreed well with literature reported biodistributions using radiolabels. However, the greater tissue autofluorescence at 680 nm resulted in limited detection above background at low (∼2 mg/kg) doses and 0.3 DoL for AF680, indicating that 800CW is more appropriate for short-term biodistribution measurements and intraoperative imaging. Overall, our work shows a DoL of 0.3 or less for non-site-specifically labeled antibodies (with a Poisson distribution) is ideal for limiting the impact of NIR fluorophores on antibody pharmacokinetics.

High-resolution chromatography/time-of-flight MSE with in silico data mining is an information-rich approach to reactive metabolite screening.

PubMed

Barbara, Joanna E; Castro-Perez, Jose M

2011-10-30

Electrophilic reactive metabolite screening by liquid chromatography/mass spectrometry (LC/MS) is commonly performed during drug discovery and early-stage drug development. Accurate mass spectrometry has excellent utility in this application, but sophisticated data processing strategies are essential to extract useful information. Herein, a unified approach to glutathione (GSH) trapped reactive metabolite screening with high-resolution LC/TOF MS(E) analysis and drug-conjugate-specific in silico data processing was applied to rapid analysis of test compounds without the need for stable- or radio-isotope-labeled trapping agents. Accurate mass defect filtering (MDF) with a C-heteroatom dealkylation algorithm dynamic with mass range was compared to linear MDF and shown to minimize false positive results. MS(E) data-filtering, time-alignment and data mining post-acquisition enabled detection of 53 GSH conjugates overall formed from 5 drugs. Automated comparison of sample and control data in conjunction with the mass defect filter enabled detection of several conjugates that were not evident with mass defect filtering alone. High- and low-energy MS(E) data were time-aligned to generate in silico product ion spectra which were successfully applied to structural elucidation of detected GSH conjugates. Pseudo neutral loss and precursor ion chromatograms derived post-acquisition demonstrated 50.9% potential coverage, at best, of the detected conjugates by any individual precursor or neutral loss scan type. In contrast with commonly applied neutral loss and precursor-based techniques, the unified method has the advantage of applicability across different classes of GSH conjugates. The unified method was also successfully applied to cyanide trapping analysis and has potential for application to alternate trapping agents. Copyright © 2011 John Wiley & Sons, Ltd.

Heterogeneity of the IgE response to allergenic determinants of cefaclor in serum samples from patients with cefaclor-induced anaphylaxis.

PubMed

Kim, Sang-Hoon; Choi, Jeong-Hee; Park, Hae-Sim

2005-06-01

Beta-lactam antibiotics, such as cefaclor, may cause IgE-mediated anaphylactic reactions. However, the clinically available serologic test has not been widely accepted, and the antigenic determinants of these drugs are unclear. To describe 4 cases of anaphylaxis caused by cefaclor in which a specific IgE response to cefaclor was demonstrated. Four patients with anaphylaxis to cefaclor and 35 nonatopic controls never exposed to cefaclor were studied. Skin tests and oral challenges with this drug were performed. The specific IgE response to the antigenic determinant of cefaclor-human serum albumin (HSA) conjugate was compared in each patient. The serum specific IgE to cefaclor-HSA conjugate was detected using enzyme-linked immunosorbent assay (ELISA). Also, ELISA inhibition studies using various concentrations of cefaclor-HSA, HSA alone, and free cefaclor were performed, as were hapten inhibition studies using cefaclor, cephalexin, cefadroxil, ampicillin, ceftriaxone, and cefotaxime. Three patients showed high levels of serum specific IgE to cefaclor-HSA and marked inhibition patterns to free cefaclor and cefaclor-HSA conjugate on ELISA inhibition testing. Hapten inhibition testing in 3 individual serum samples showed 2 different patterns. In patient 3, significant dose-dependent inhibitions (up to 92%) were noted with additions of free cefaclor and cefaclor-HSA conjugate, and lesser inhibitions (up to 74%) were noted with cephalexin, which shares the aminobenzyl side chain. In patients 1 and 2, marked dose-dependent inhibitions were noted only with additions of cefaclor-HSA conjugate and free cefaclor, whereas minimal inhibitions were noted with the other 5 compounds. The specific IgE response to cefaclor-HSA conjugate in patients with cefaclor anaphylaxis occurs against the hapten, in which heterogeneity of the antigenic determinant was noted to depend on the individual.

Co-delivery of hydrophilic and hydrophobic drugs by micelles: a new approach using drug conjugated PEG-PCLNanoparticles.

PubMed

Danafar, Hossein; Rostamizadeh, Kobra; Davaran, Soodabeh; Hamidi, Mehrdad

2017-11-01

Co-delivery strategy has been proposed to minimize the amount of each drug and to achieve the synergistic effect for cancer therapies. A conjugate of the antitumor drug, doxorubicin, with diblock methoxy poly (ethylene glycol)-poly caprolactone (mPEG-PCL) copolymer was synthesized by the reaction of mPEG-PCL copolymer with doxorubicin in the presence of p-nitrophenylchloroformate. The conjugated copolymer was characterized in vitro by 1 H-NMR, FTIR, DSC and GPC techniques. Then, the doxorubicin conjugated mPEG-PCL(DOX-mPEG-PCL) was self-assembled into micelles in the presence of curcumin in aqueous solution. The resulting micelles were characterized further by various techniques such as dynamic light scattering (DLS) and atomic force microscopy (AFM).The encapsulation efficiency of doxorubicin and curcumin were 82.31 ± 3.32 and 78.15 ± 3.14%, respectively. The results revealed that the micelles formed by the DOX-mPEG-PCL with and without curcumin have spherical structure with average size of 116 and 134 nm respectively. The release behavior of curcumin and doxorubicin loaded to micelles were investigated in a different media. The release rate of micelles consisted of the conjugated copolymer was pH dependent as it was higher at lower pH than in neutral condition. Another feature of the conjugated micelles was a sustained release profile. The cytotoxicity of micelles were evaluated by MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, atetrazole) assay on lung cancer A549 cell lines. In vitro cytotoxicity assay showed that the mPEG-PCL copolymer did not affect the growth of A549 cells. The cytotoxic activity of the micelles against A549 cells was greater than free doxorubicin and free curcumin.

Targeting of follicle stimulating hormone peptide-conjugated dendrimers to ovarian cancer cells

NASA Astrophysics Data System (ADS)

Modi, Dimple A.; Sunoqrot, Suhair; Bugno, Jason; Lantvit, Daniel D.; Hong, Seungpyo; Burdette, Joanna E.

2014-02-01

Ovarian cancer is the most lethal gynecological malignancy. Current treatment modalities include a combination of surgery and chemotherapy, which often lead to loss of fertility in premenopausal women and a myriad of systemic side effects. To address these issues, we have designed poly(amidoamine) (PAMAM) dendrimers to selectively target the follicle stimulating hormone receptor (FSHR), which is overexpressed by tumorigenic ovarian cancer cells but not by immature primordial follicles and other non-tumorigenic cells. Fluorescein-labeled generation 5 (G5) PAMAM dendrimers were conjugated with the binding peptide domain of FSH (FSH33) that has a high affinity to FSHR. The targeted dendrimers exhibited high receptor selectivity to FSHR-expressing OVCAR-3 cells, resulting in significant uptake and downregulation of an anti-apoptotic protein survivin, while showing minimal interactions with SKOV-3 cells that do not express FSHR. The selectivity of the FSH33-targeted dendrimers was further validated in 3D organ cultures of normal mouse ovaries. Immunostaining of the conjugates revealed their selective binding and uptake by ovarian surface epithelium (OSE) cells that express FSHR, while sparing the immature primordial follicles. In addition, an in vivo study monitoring tissue accumulation following a single intraperitoneal (i.p.) injection of the conjugates showed significantly higher accumulation of FSH33-targeted dendrimers in the ovary and oviduct compared to the non-targeted conjugates. These proof-of-concept findings highlight the potential of these FSH33-targeted dendrimers to serve as a delivery platform for anti-ovarian cancer drugs, while reducing their systemic side effects by preventing nonspecific uptake by the primordial follicles.Ovarian cancer is the most lethal gynecological malignancy. Current treatment modalities include a combination of surgery and chemotherapy, which often lead to loss of fertility in premenopausal women and a myriad of systemic side effects. To address these issues, we have designed poly(amidoamine) (PAMAM) dendrimers to selectively target the follicle stimulating hormone receptor (FSHR), which is overexpressed by tumorigenic ovarian cancer cells but not by immature primordial follicles and other non-tumorigenic cells. Fluorescein-labeled generation 5 (G5) PAMAM dendrimers were conjugated with the binding peptide domain of FSH (FSH33) that has a high affinity to FSHR. The targeted dendrimers exhibited high receptor selectivity to FSHR-expressing OVCAR-3 cells, resulting in significant uptake and downregulation of an anti-apoptotic protein survivin, while showing minimal interactions with SKOV-3 cells that do not express FSHR. The selectivity of the FSH33-targeted dendrimers was further validated in 3D organ cultures of normal mouse ovaries. Immunostaining of the conjugates revealed their selective binding and uptake by ovarian surface epithelium (OSE) cells that express FSHR, while sparing the immature primordial follicles. In addition, an in vivo study monitoring tissue accumulation following a single intraperitoneal (i.p.) injection of the conjugates showed significantly higher accumulation of FSH33-targeted dendrimers in the ovary and oviduct compared to the non-targeted conjugates. These proof-of-concept findings highlight the potential of these FSH33-targeted dendrimers to serve as a delivery platform for anti-ovarian cancer drugs, while reducing their systemic side effects by preventing nonspecific uptake by the primordial follicles. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05042d

A minimal cost function method for optimizing the age-Depth relation of deep-sea sediment cores

NASA Astrophysics Data System (ADS)

Brüggemann, Wolfgang

1992-08-01

The question of an optimal age-depth relation for deep-sea sediment cores has been raised frequently. The data from such cores (e.g., δ18O values) are used to test the astronomical theory of ice ages as established by Milankovitch in 1938. In this work, we use a minimal cost function approach to find simultaneously an optimal age-depth relation and a linear model that optimally links solar insolation or other model input with global ice volume. Thus a general tool for the calibration of deep-sea cores to arbitrary tuning targets is presented. In this inverse modeling type approach, an objective function is minimized that penalizes: (1) the deviation of the data from the theoretical linear model (whose transfer function can be computed analytically for a given age-depth relation) and (2) the violation of a set of plausible assumptions about the model, the data and the obtained correction of a first guess age-depth function. These assumptions have been suggested before but are now quantified and incorporated explicitly into the objective function as penalty terms. We formulate an optimization problem that is solved numerically by conjugate gradient type methods. Using this direct approach, we obtain high coherences in the Milankovitch frequency bands (over 90%). Not only the data time series but also the the derived correction to a first guess linear age-depth function (and therefore the sedimentation rate) itself contains significant energy in a broad frequency band around 100 kyr. The use of a sedimentation rate which varies continuously on ice age time scales results in a shift of energy from 100 kyr in the original data spectrum to 41, 23, and 19 kyr in the spectrum of the corrected data. However, a large proportion of the data variance remains unexplained, particularly in the 100 kyr frequency band, where there is no significant input by orbital forcing. The presented method is applied to a real sediment core and to the SPECMAP stack, and results are compared with those obtained in earlier investigations.

Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection

PubMed Central

Bilgic, Berkin; Fan, Audrey P.; Polimeni, Jonathan R.; Cauley, Stephen F.; Bianciardi, Marta; Adalsteinsson, Elfar; Wald, Lawrence L.; Setsompop, Kawin

2014-01-01

Purpose To enable fast reconstruction of quantitative susceptibility maps with Total Variation penalty and automatic regularization parameter selection. Methods ℓ1-regularized susceptibility mapping is accelerated by variable-splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and FFTs. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization. Results Compared to the nonlinear Conjugate Gradient (CG) solver, the proposed method offers 20× speed-up in reconstruction time. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering and ℓ1-regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 minutes using Matlab on a standard workstation compared to 22 minutes using the Conjugate Gradient solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 minutes, which would have taken 4 hours with the CG algorithm. Proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5× faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional BOLD susceptibility mapping, where processing of the massive time-series dataset would otherwise be prohibitive with the CG solver. Conclusion Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion. PMID:24259479

Deconvolution of astronomical images using SOR with adaptive relaxation.

PubMed

Vorontsov, S V; Strakhov, V N; Jefferies, S M; Borelli, K J

2011-07-04

We address the potential performance of the successive overrelaxation technique (SOR) in image deconvolution, focusing our attention on the restoration of astronomical images distorted by atmospheric turbulence. SOR is the classical Gauss-Seidel iteration, supplemented with relaxation. As indicated by earlier work, the convergence properties of SOR, and its ultimate performance in the deconvolution of blurred and noisy images, can be made competitive to other iterative techniques, including conjugate gradients, by a proper choice of the relaxation parameter. The question of how to choose the relaxation parameter, however, remained open, and in the practical work one had to rely on experimentation. In this paper, using constructive (rather than exact) arguments, we suggest a simple strategy for choosing the relaxation parameter and for updating its value in consecutive iterations to optimize the performance of the SOR algorithm (and its positivity-constrained version, +SOR) at finite iteration counts. We suggest an extension of the algorithm to the notoriously difficult problem of "blind" deconvolution, where both the true object and the point-spread function have to be recovered from the blurred image. We report the results of numerical inversions with artificial and real data, where the algorithm is compared with techniques based on conjugate gradients. In all of our experiments +SOR provides the highest quality results. In addition +SOR is found to be able to detect moderately small changes in the true object between separate data frames: an important quality for multi-frame blind deconvolution where stationarity of the object is a necesessity.

Preconditioned conjugate-gradient methods for low-speed flow calculations

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing

1993-01-01

An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations is integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the Lower-Upper Successive Symmetric Over-Relaxation iterative scheme is more efficient than a preconditioner based on Incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional Line Gauss-Seidel Relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.

Preconditioned Conjugate Gradient methods for low speed flow calculations

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing

1993-01-01

An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations are integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and the convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the lower-upper (L-U)-successive symmetric over-relaxation iterative scheme is more efficient than a preconditioner based on incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional line Gauss-Seidel relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.

A numerical solution for the diffusion equation in hydrogeologic systems

USGS Publications Warehouse

Ishii, A.L.; Healy, R.W.; Striegl, Robert G.

1989-01-01

The documentation of a computer code for the numerical solution of the linear diffusion equation in one or two dimensions in Cartesian or cylindrical coordinates is presented. Applications of the program include molecular diffusion, heat conduction, and fluid flow in confined systems. The flow media may be anisotropic and heterogeneous. The model is formulated by replacing the continuous linear diffusion equation by discrete finite-difference approximations at each node in a block-centered grid. The resulting matrix equation is solved by the method of preconditioned conjugate gradients. The conjugate gradient method does not require the estimation of iteration parameters and is guaranteed convergent in the absence of rounding error. The matrixes are preconditioned to decrease the steps to convergence. The model allows the specification of any number of boundary conditions for any number of stress periods, and the output of a summary table for selected nodes showing flux and the concentration of the flux quantity for each time step. The model is written in a modular format for ease of modification. The model was verified by comparison of numerical and analytical solutions for cases of molecular diffusion, two-dimensional heat transfer, and axisymmetric radial saturated fluid flow. Application of the model to a hypothetical two-dimensional field situation of gas diffusion in the unsaturated zone is demonstrated. The input and output files are included as a check on program installation. The definition of variables, input requirements, flow chart, and program listing are included in the attachments. (USGS)

Multi-GPU Accelerated Admittance Method for High-Resolution Human Exposure Evaluation.

PubMed

Xiong, Zubiao; Feng, Shi; Kautz, Richard; Chandra, Sandeep; Altunyurt, Nevin; Chen, Ji

2015-12-01

A multi-graphics processing unit (GPU) accelerated admittance method solver is presented for solving the induced electric field in high-resolution anatomical models of human body when exposed to external low-frequency magnetic fields. In the solver, the anatomical model is discretized as a three-dimensional network of admittances. The conjugate orthogonal conjugate gradient (COCG) iterative algorithm is employed to take advantage of the symmetric property of the complex-valued linear system of equations. Compared against the widely used biconjugate gradient stabilized method, the COCG algorithm can reduce the solving time by 3.5 times and reduce the storage requirement by about 40%. The iterative algorithm is then accelerated further by using multiple NVIDIA GPUs. The computations and data transfers between GPUs are overlapped in time by using asynchronous concurrent execution design. The communication overhead is well hidden so that the acceleration is nearly linear with the number of GPU cards. Numerical examples show that our GPU implementation running on four NVIDIA Tesla K20c cards can reach 90 times faster than the CPU implementation running on eight CPU cores (two Intel Xeon E5-2603 processors). The implemented solver is able to solve large dimensional problems efficiently. A whole adult body discretized in 1-mm resolution can be solved in just several minutes. The high efficiency achieved makes it practical to investigate human exposure involving a large number of cases with a high resolution that meets the requirements of international dosimetry guidelines.

Horizontal Gene Transfers in Mycoplasmas (Mollicutes).

PubMed

Citti, C; Dordet-Frisoni, E; Nouvel, L X; Kuo, C H; Baranowski, E

2018-04-12

The class Mollicutes (trivial name "mycoplasma") is composed of wall-less bacteria with reduced genomes whose evolution was long thought to be only driven by gene losses. Recent evidences of massive horizontal gene transfer (HGT) within and across species provided a new frame to understand the successful adaptation of these minimal bacteria to a broad range of hosts. Mobile genetic elements are being identified in a growing number of mycoplasma species, but integrative and conjugative elements (ICEs) are emerging as pivotal in HGT. While sharing common traits with other bacterial ICEs, such as their chromosomal integration and the use of a type IV secretion system to mediate horizontal dissemination, mycoplasma ICEs (MICEs) revealed unique features: their chromosomal integration is totally random and driven by a DDE recombinase related to the Mutator-like superfamily. Mycoplasma conjugation is not restricted to ICE transmission, but also involves the transfer of large chromosomal fragments that generates progenies with mosaic genomes, nearly every position of chromosome being mobile. Mycoplasmas have thus developed efficient ways to gain access to a considerable reservoir of genetic resources distributed among a vast number of species expanding the concept of minimal cell to the broader context of flowing information.

Project Report: Reducing Color Rivalry in Imagery for Conjugated Multiple Bandpass Filter Based Stereo Endoscopy

NASA Technical Reports Server (NTRS)

Ream, Allen

2011-01-01

A pair of conjugated multiple bandpass filters (CMBF) can be used to create spatially separated pupils in a traditional lens and imaging sensor system allowing for the passive capture of stereo video. This method is especially useful for surgical endoscopy where smaller cameras are needed to provide ample room for manipulating tools while also granting improved visualizations of scene depth. The significant issue in this process is that, due to the complimentary nature of the filters, the colors seen through each filter do not match each other, and also differ from colors as seen under a white illumination source. A color correction model was implemented that included optimized filter selection, such that the degree of necessary post-processing correction was minimized, and a chromatic adaptation transformation that attempted to fix the imaged colors tristimulus indices based on the principle of color constancy. Due to fabrication constraints, only dual bandpass filters were feasible. The theoretical average color error after correction between these filters was still above the fusion limit meaning that rivalry conditions are possible during viewing. This error can be minimized further by designing the filters for a subset of colors corresponding to specific working environments.

Study of the antibacterial activity of electro-activated solutions of salts of weak organic acids on Salmonella enterica, Staphylococcus aureus and Listeria monocytogenes.

PubMed

Liato, Viacheslav; Labrie, Steve; Aïder, Mohammed

2017-01-01

This work assessed the antibacterial activity of electro-activated solutions of salts of weak organic acids (potassium acetate, potassium citrate and calcium lactate) on Salmonella enterica, Staphylococcus aureus and Listeria monocytogenes. This activity was compared in terms of minimal inhibitory (bactericidal) concentration to the effect of commercial acetic, citric and lactic acid at equivalent titratable acidity. Staining live/dead BacLight method was used to consider physiological state of bacteria following the evaluation of pathogenic strains during exposure to the tested solutions. The results demonstrated strong inhibitory activity of all electro-activated solutions. After 10 min of exposure to electro-activated potassium acetate, a reduction of ≥6 log CFU/ml of all bacteria was observed. The electro-activated potassium citrate demonstrated the lowest minimal inhibitory concentration. Nevertheless, its inactivation power was significantly higher than that of conjugated citric acid. Although electro-activated calcium lactate was found less effective in comparison with its conjugated acid form, after 10 min of contact with the tested pathogens, it induced a population reduction of 2.23, 2.97 and 5.57 log CFU/ml of S. aureus, L. monocytogenes and S. enterica, respectively.

Separation of antibody drug conjugate species by RPLC: A generic method development approach.

PubMed

Fekete, Szabolcs; Molnár, Imre; Guillarme, Davy

2017-04-15

This study reports the use of modelling software for the successful method development of IgG1 cysteine conjugated antibody drug conjugate (ADC) in RPLC. The goal of such a method is to be able to calculate the average drug to antibody ratio (DAR) of and ADC product. A generic method development strategy was proposed including the optimization of mobile phase temperature, gradient profile and mobile phase ternary composition. For the first time, a 3D retention modelling was presented for large therapeutic protein. Based on a limited number of preliminary experiments, a fast and efficient separation of the DAR species of a commercial ADC sample, namely brentuximab vedotin, was achieved. The prediction offered by the retention model was found to be highly reliable, with an average error of retention time prediction always lower than 0.5% using a 2D or 3D retention models. For routine purpose, four to six initial experiments were required to build the 2D retention models, while 12 experiments were recommended to create the 3D model. At the end, RPLC can therefore be considered as a good method for estimating the average DAR of an ADC, based on the observed peak area ratios of RPLC chromatogram of the reduced ADC sample. Copyright © 2017 Elsevier B.V. All rights reserved.

X-ray computed tomography imaging of a tumor with high sensitivity using gold nanoparticles conjugated to a cancer-specific antibody via polyethylene glycol chains on their surface

NASA Astrophysics Data System (ADS)

Nakagawa, Tomohiko; Gonda, Kohsuke; Kamei, Takashi; Cong, Liman; Hamada, Yoh; Kitamura, Narufumi; Tada, Hiroshi; Ishida, Takanori; Aimiya, Takuji; Furusawa, Naoko; Nakano, Yasushi; Ohuchi, Noriaki

2016-01-01

Contrast agents are often used to enhance the contrast of X-ray computed tomography (CT) imaging of tumors to improve diagnostic accuracy. However, because the iodine-based contrast agents currently used in hospitals are of low molecular weight, the agent is rapidly excreted from the kidney or moves to extravascular tissues through the capillary vessels, depending on its concentration gradient. This leads to nonspecific enhancement of contrast images for tissues. Here, we created gold (Au) nanoparticles as a new contrast agent to specifically image tumors with CT using an enhanced permeability and retention (EPR) effect. Au has a higher X-ray absorption coefficient than does iodine. Au nanoparticles were supported with polyethylene glycol (PEG) chains on their surface to increase the blood retention and were conjugated with a cancer-specific antibody via terminal PEG chains. The developed Au nanoparticles were injected into tumor-bearing mice, and the distribution of Au was examined with CT imaging, transmission electron microscopy, and elemental analysis using inductively coupled plasma optical emission spectrometry. The results show that specific localization of the developed Au nanoparticles in the tumor is affected by a slight difference in particle size and enhanced by the conjugation of a specific antibody against the tumor.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning

NASA Astrophysics Data System (ADS)

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-08-01

{{\\ell }2,1} -minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the {{\\ell }2,1} -based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the {{\\ell }2,1} -minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the {{\\ell }2,1} -minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the {{\\ell }2,1} -minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning.

PubMed

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-07-20

[Formula: see text]-minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the [Formula: see text]-based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the [Formula: see text]-minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the [Formula: see text]-minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the [Formula: see text]-minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

Efficient realization of 3D joint inversion of seismic and magnetotelluric data with cross gradient structure constraint

NASA Astrophysics Data System (ADS)

Luo, H.; Zhang, H.; Gao, J.

2016-12-01

Seismic and magnetotelluric (MT) imaging methods are generally used to characterize subsurface structures at various scales. The two methods are complementary to each other and the integration of them is helpful for more reliably determining the resistivity and velocity models of the target region. Because of the difficulty in finding empirical relationship between resistivity and velocity parameters, Gallardo and Meju [2003] proposed a joint inversion method enforcing resistivity and velocity models consistent in structure, which is realized by minimizing cross gradients between two models. However, it is extremely challenging to combine two different inversion systems together along with the cross gradient constraints. For this reason, Gallardo [2007] proposed a joint inversion scheme that decouples the seismic and MT inversion systems by iteratively performing seismic and MT inversions as well as cross gradient minimization separately. This scheme avoids the complexity of combining two different systems together but it suffers the issue of balancing between data fitting and structure constraint. In this study, we have developed a new joint inversion scheme that avoids the problem encountered by the scheme of Gallardo [2007]. In the new scheme, seismic and MT inversions are still separately performed but the cross gradient minimization is also constrained by model perturbations from separate inversions. In this way, the new scheme still avoids the complexity of combining two different systems together and at the same time the balance between data fitting and structure consistency constraint can be enforced. We have tested our joint inversion algorithm for both 2D and 3D cases. Synthetic tests show that joint inversion better reconstructed the velocity and resistivity models than separate inversions. Compared to separate inversions, joint inversion can remove artifacts in the resistivity model and can improve the resolution for deeper resistivity structures. We will also show results applying the new joint seismic and MT inversion scheme to southwest China, where several MT profiles are available and earthquakes are very active.

Exploiting the Temperature Dependence of Magnetic Susceptibility to Control Convective in Fundamental Studies of Solidification Phenomena

NASA Technical Reports Server (NTRS)

Seybert, C.; Evans, J. W.; Leslie, F.; Jones, W. K., Jr.

2001-01-01

It is well known that convection is a dominant mass transport mechanism when materials are solidified on Earth's surface. This convection is caused by gradients in density (and therefore gravitational force) that are brought about by gradients in temperature, composition or both. Diffusion of solute is therefore dwarfed by convection and the study of fundamental parameters, such as dendrite tip shape and growth velocity in the absence of convection is nearly impossible. Significant experimental work has therefore been carried out in orbiting laboratories with the intent of minimizing convection by minimizing gravity. One of the best known experiments of this kind is the Isothermal Dendritic Growth Experiment (IDGE), supported by NASA. Naturally such experiments are costly and one objective of the present investigation is to develop an experimental method whereby convection can be halted, in solidification and other experiments, on the Earth's surface. A second objective is to use the method to minimize convection resulting from the residual accelerations suffered by experiments in microgravity.

Minimizing hot spot temperature in asymmetric gradient coil design.

PubMed

While, Peter T; Forbes, Larry K; Crozier, Stuart

2011-08-01

Heating caused by gradient coils is a considerable concern in the operation of magnetic resonance imaging (MRI) scanners. Hot spots can occur in regions where the gradient coil windings are closely spaced. These problem areas are particularly common in the design of gradient coils with asymmetrically located target regions. In this paper, an extension of an existing coil design method is described, to enable the design of asymmetric gradient coils with reduced hot spot temperatures. An improved model is presented for predicting steady-state spatial temperature distributions for gradient coils. A great amount of flexibility is afforded by this model to consider a wide range of geometries and system material properties. A feature of the temperature distribution related to the temperature gradient is used in a relaxed fixed point iteration routine for successively altering coil windings to have a lower hot spot temperature. Results show that significant reductions in peak temperature are possible at little or no cost to coil performance when compared to minimum power coils of equivalent field error.

Self-assembly of pi-conjugated peptides in aqueous environments leading to energy-transporting bioelectronic nanostructures

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

Tavor, John

The realization of new supramolecular pi-conjugated organic structures inspired and driven by peptide-based self-assembly will offer a new approach to interface with the biotic environment in a way that will help to meet many DOE-recognized grand challenges. Previously, we developed pi-conjugated peptides that undergo supramolecular self-assembly into one-dimensional (1-D) organic electronic nanomaterials under benign aqueous conditions. The intermolecular interactions among the pi-conjugated organic segments within these nanomaterials lead to defined perturbations of their optoelectronic properties and yield nanoscale conduits that support energy transport within individual nanostructures and throughout bulk macroscopic collections of nanomaterials. Our objectives for future research are tomore » construct and study biomimetic electronic materials for energy-related technology optimized for harsher non-biological environments where peptide-driven self-assembly enhances pi-stacking within nanostructured biomaterials, as detailed in the following specific tasks: (1) synthesis and detailed optoelectronic characterization of new pi-electron units to embed within homogeneous self assembling peptides, (2) molecular and data-driven modeling of the nanomaterial aggregates and their higher-order assemblies, and (3) development of new hierarchical assembly paradigms to organize multiple electronic subunits within the nanomaterials leading to heterogeneous electronic properties (i.e. gradients and localized electric fields). These intertwined research tasks will lead to the continued development and fundamental mechanistic understanding of a powerful bioinspired materials set capable of making connections between nanoscale electronic materials and macroscopic bulk interfaces, be they those of a cell, a protein or a device.« less

Ruxolitinib-conjugated gold nanoparticles for topical administration: An alternative for treating alopecia?

PubMed

Boca, Sanda; Berce, Cristian; Jurj, Ancuta; Petrushev, Bobe; Pop, Laura; Gafencu, Grigore-Aristide; Selicean, Sonia; Moisoiu, Vlad; Temian, Daiana; Micu, Wilhelm-Thomas; Astilean, Simion; Braicu, Cornelia; Tomuleasa, Ciprian; Berindan-Neagoe, Ioana

2017-11-01

Alopecia is a dermatological condition for which Janus kinase (JAK) inhibitors have recently emerged as potential therapy options, but with limited practical use because of the systemic side effects. The topical use of Ruxolitinib in alopecia universalis has been demonstrated, but little is known about the pharmacodynamics and pharmacokinetics of this way of administration. Nanomedicine provides improved therapeutics. In the current paper we present preliminary data regarding the potential use of Ruxolitinib-conjugated gold nanoparticles (GNPs) in dermatological conditions, as GNPs have been proven to have a reduced absorption rate into the systemic blood flow for cutaneous administration. Internalization of the newly formed bioconjugate was assessed by electron microscopy and the functional effects of the drug were investigated by cell counting, flow cytometry and western blotting. Our data show that gold nanoparticles conjugated with Ruxolitinib inhibit the proliferation of fibroblasts by inhibiting JAK2 protein. Ruxolitinib carried by gold nanoparticles alters the proliferation of human fibroblasts, which is of great clinical importance as it can be readily administered on the skin with minimal risk of systemic side effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of enrichment with polyunsaturated fatty acids (omega-3 and conjugated linoleic acid) on consumer liking of beef aged for 7 or 21 d evaluated at different locations.

PubMed

Pérez-Juan, María; Realini, Carolina E; Barahona, Marta; Sarriés, Maria Victoria; del Mar Campo, Maria; Beriain, María José; Vitale, Mauro; Gil, Marta; Albertí, Pere

2014-11-01

The effect of different animal diets supplemented with linseed (source of omega-3 fatty acids: n-3) and/or conjugated linoleic acid (CON: control, LIN: 10% linseed, CLA: 2% conjugated linoleic acid, LINCLA: 10% linseed plus 2% CLA) on consumer liking of beef aged for 7 or 21 d was assessed in 3 Spanish cities. Overall, tenderness, juiciness, and flavor liking of beef were evaluated by consumers (n = 720) using 9-point scales. Hedonic scores assigned by consumers did not differ (P > 0.05) for beef from animals fed the different diets and aged for 7 or 21 d. Consumer scores showed an increasing trend in beef liking with aging time. Consumers from Pamplona assigned lower (P < 0.05) hedonic scores for beef liking than consumers from Barcelona and Zaragoza. Linseed and/or CLA can be fed to improve the fatty acid profile in beef with minimal impact on consumer liking. Consumer ratings seem to depend on regional tastes and preferences. © 2014 Institute of Food Technologists®

Cell Partition in Two Polymer Aqueous Phases

NASA Technical Reports Server (NTRS)

Harris, J. M.

1985-01-01

Partition of biological cells in two phase aqueous polymer systems is recognized as a powerful separation technique which is limited by gravity. The synthesis of new, selective polymer ligand conjugates to be used in affinity partition separations is of interest. The two most commonly used polymers in two phase partitioning are dextran and polyethylene glycol. A thorough review of the chemistry of these polymers was begun, particularly in the area of protein attachment. Preliminary studies indicate the importance in affinity partitioning of minimizing gravity induced randomizing forces in the phase separation process. The PEG-protein conjugates that were prepared appear to be ideally suited for achieving high quality purifications in a microgravity environment. An interesting spin-off of this synthetic work was the observation of catalytic activity for certain of our polymer derivatives.

Error measure comparison of currently employed dose-modulation schemes for e-beam proximity effect control

NASA Astrophysics Data System (ADS)

Peckerar, Martin C.; Marrian, Christie R.

1995-05-01

Standard matrix inversion methods of e-beam proximity correction are compared with a variety of pseudoinverse approaches based on gradient descent. It is shown that the gradient descent methods can be modified using 'regularizers' (terms added to the cost function minimized during gradient descent). This modification solves the 'negative dose' problem in a mathematically sound way. Different techniques are contrasted using a weighted error measure approach. It is shown that the regularization approach leads to the highest quality images. In some cases, ignoring negative doses yields results which are worse than employing an uncorrected dose file.

TEMPERATURE-GRADIENT INCUBATOR FOR DETERMINING THE TEMPERATURE RANGE OF GROWTH OF MICROORGANISMS

PubMed Central

Elliott, R. Paul

1963-01-01

Elliott, R. Paul (U.S. Department of Agriculture, Albany, Calif.). Temperature-gradient incubator for determining the temperature range of growth of microorganisms. J. Bacteriol. 85:889–894. 1963.—The temperature-gradient incubator consists of an aluminum bar with troughs for media, with controlled temperatures at each end, and with insulation to prevent heat transfer. The resulting linear temperature gradient provides a means for determining minimal or maximal growth temperatures of microorganisms in any desired range and at any desired gradient. The operation of the incubator is unaffected by line-voltage variations or by ambient temperature. Media do not dehydrate seriously even during prolonged periods of operation. The incubator can be used to determine water activity of media by an adjustment to permit partial freezing. Either thermocouples or thermistors may be used to measure temperatures. Images PMID:14044959

Role of central and peripheral opiate receptors in the effects of fentanyl on analgesia, ventilation and arterial blood-gas chemistry in conscious rats.

PubMed

Henderson, Fraser; May, Walter J; Gruber, Ryan B; Discala, Joseph F; Puskovic, Veljko; Young, Alex P; Baby, Santhosh M; Lewis, Stephen J

2014-01-15

This study determined the effects of the peripherally restricted μ-opiate receptor (μ-OR) antagonist, naloxone methiodide (NLXmi) on fentanyl (25μg/kg, i.v.)-induced changes in (1) analgesia, (2) arterial blood gas chemistry (ABG) and alveolar-arterial gradient (A-a gradient), and (3) ventilatory parameters, in conscious rats. The fentanyl-induced increase in analgesia was minimally affected by a 1.5mg/kg of NLXmi but was attenuated by a 5.0mg/kg dose. Fentanyl decreased arterial blood pH, pO2 and sO2 and increased pCO2 and A-a gradient. These responses were markedly diminished in NLXmi (1.5mg/kg)-pretreated rats. Fentanyl caused ventilatory depression (e.g., decreases in tidal volume and peak inspiratory flow). Pretreatment with NLXmi (1.5mg/kg, i.v.) antagonized the fentanyl decrease in tidal volume but minimally affected the other responses. These findings suggest that (1) the analgesia and ventilatory depression caused by fentanyl involve peripheral μ-ORs and (2) NLXmi prevents the fentanyl effects on ABG by blocking the negative actions of the opioid on tidal volume and A-a gradient. Copyright © 2013 Elsevier B.V. All rights reserved.

A nonrecursive 'Order N' preconditioned conjugate gradient/range space formulation of MDOF dynamics

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Menon, R.; Sunkel, John

1991-01-01

This paper addresses the requirements of present-day mechanical system simulations of algorithms that induce parallelism on a fine scale and of transient simulation methods which must be automatically load balancing for a wide collection of system topologies and hardware configurations. To this end, a combination range space/preconditioned conjugage gradient formulation of multidegree-of-freedon dynamics is developed, which, by employing regular ordering of the system connectivity graph, makes it possible to derive an extremely efficient preconditioner from the range space metric (as opposed to the system coefficient matrix). Because of the effectiveness of the preconditioner, the method can achieve performance rates that depend linearly on the number of substructures. The method, termed 'Order N' does not require the assembly of system mass or stiffness matrices, and is therefore amenable to implementation on work stations. Using this method, a 13-substructure model of the Space Station was constructed.

DenInv3D: a geophysical software for three-dimensional density inversion of gravity field data

NASA Astrophysics Data System (ADS)

Tian, Yu; Ke, Xiaoping; Wang, Yong

2018-04-01

This paper presents a three-dimensional density inversion software called DenInv3D that operates on gravity and gravity gradient data. The software performs inversion modelling, kernel function calculation, and inversion calculations using the improved preconditioned conjugate gradient (PCG) algorithm. In the PCG algorithm, due to the uncertainty of empirical parameters, such as the Lagrange multiplier, we use the inflection point of the L-curve as the regularisation parameter. The software can construct unequally spaced grids and perform inversions using such grids, which enables changing the resolution of the inversion results at different depths. Through inversion of airborne gradiometry data on the Australian Kauring test site, we discovered that anomalous blocks of different sizes are present within the study area in addition to the central anomalies. The software of DenInv3D can be downloaded from http://159.226.162.30.

Multimodal magnetic nano-carriers for cancer treatment: Challenges and advancements

NASA Astrophysics Data System (ADS)

Aadinath, W.; Ghosh, Triroopa; Anandharamakrishnan, C.

2016-03-01

Iron oxide nanoparticles (IONPs) have been a propitious topic for cancer treatment in recent years because of its multifunctional theranostic applications under magnetic field. Two such widely used applications in cancer biology are gradient magnetic field guided targeting and alternative magnetic field (AMF) induced local hyperthermia. Gradient magnetic field guided targeting is a mode of active targeting of therapeutics conjugated with iron oxide nanoparticles. These particles also dissipate heat in presence of AMF which causes thermal injury to the cells of interest, for example tumour cells and subsequent death. Clinical trials divulge the feasibility of such magnetic nano-carrier as a promising candidate in cancer biology. However, these techniques need further investigations to curtail certain limitations manifested. Recent progresses in response have shrunken the barricade to certain extent. In this context, principles, challenges associated with these applications and recent efforts made in response will be discussed.

Generation of Plasma Density Irregularities in the Midlatitude/Subauroral F Region

NASA Astrophysics Data System (ADS)

Mishin, E. V.

2017-12-01

A concise review is given of the current state of the theoretical understanding of the creation of small- and meso-scale plasma density irregularities in the midlatitude/subauroral F region during quiet and disturbed periods. The former are discussed in terms of the temperature gradient instability (TGI) in the vicinity of the ionospheric projection of the plasmapause and the Perkins instability. During active conditions some part of the midlatitude ionosphere becomes the subauroral region dominated by enhanced westward flows (SAPS and SAID) driven by poleward electric fields. Their irregular, often nonlinear wave structure leads to the formation of plasma density irregularities in the plasmasphere and conjugate ionosphere. Here, meso-scale irregularities are due to the positive feedback magnetosphere-ionosphere coupling instability, while small scales resulted from the gradient drift instability (GDI), temperature GDI, and the ion frictional heating instability. The theoretical predictions are compared with satellite observations in the perturbed subauroral geospace.

Numerical Study of Hydrothermal Wave Suppression in Thermocapillary Flow Using a Predictive Control Method

NASA Astrophysics Data System (ADS)

Muldoon, F. H.

2018-04-01

Hydrothermal waves in flows driven by thermocapillary and buoyancy effects are suppressed by applying a predictive control method. Hydrothermal waves arise in the manufacturing of crystals, including the "open boat" crystal growth process, and lead to undesirable impurities in crystals. The open boat process is modeled using the two-dimensional unsteady incompressible Navier-Stokes equations under the Boussinesq approximation and the linear approximation of the surface thermocapillary force. The flow is controlled by a spatially and temporally varying heat flux density through the free surface. The heat flux density is determined by a conjugate gradient optimization algorithm. The gradient of the objective function with respect to the heat flux density is found by solving adjoint equations derived from the Navier-Stokes ones in the Boussinesq approximation. Special attention is given to heat flux density distributions over small free-surface areas and to the maximum admissible heat flux density.

Axial compartmentation of descending and ascending thin limbs of Henle's loops

PubMed Central

Westrick, Kristen Y.; Serack, Bradley; Dantzler, William H.

2013-01-01

In the inner medulla, radial organization of nephrons and blood vessels around collecting duct (CD) clusters leads to two lateral interstitial regions and preferential intersegmental fluid and solute flows. As the descending (DTLs) and ascending thin limbs (ATLs) pass through these regions, their transepithelial fluid and solute flows are influenced by variable transepithelial solute gradients and structure-to-structure interactions. The goal of this study was to quantify structure-to-structure interactions, so as to better understand compartmentation and flows of transepithelial water, NaCl, and urea and generation of the axial osmotic gradient. To accomplish this, we determined lateral distances of AQP1-positive and AQP1-negative DTLs and ATLs from their nearest CDs, so as to gauge interactions with intercluster and intracluster lateral regions and interactions with interstitial nodal spaces (INSs). DTLs express reduced AQP1 and low transepithelial water permeability along their deepest segments. Deep AQP1-null segments, prebend segments, and ATLs lie equally near to CDs. Prebend segments and ATLs abut CDs and INSs throughout much of their descent and ascent, respectively; however, the distal 30% of ATLs of the longest loops lie distant from CDs as they approach the outer medullary boundary and have minimal interaction with INSs. These relationships occur regardless of loop length. Finally, we show that ascending vasa recta separate intercluster AQP1-positive DTLs from descending vasa recta, thereby minimizing dilution of gradients that drive solute secretion. We hypothesize that DTLs and ATLs enter and exit CD clusters in an orchestrated fashion that is important for generation of the corticopapillary solute gradient by minimizing NaCl and urea loss. PMID:23195680

Axial compartmentation of descending and ascending thin limbs of Henle's loops.

PubMed

Westrick, Kristen Y; Serack, Bradley; Dantzler, William H; Pannabecker, Thomas L

2013-02-01

In the inner medulla, radial organization of nephrons and blood vessels around collecting duct (CD) clusters leads to two lateral interstitial regions and preferential intersegmental fluid and solute flows. As the descending (DTLs) and ascending thin limbs (ATLs) pass through these regions, their transepithelial fluid and solute flows are influenced by variable transepithelial solute gradients and structure-to-structure interactions. The goal of this study was to quantify structure-to-structure interactions, so as to better understand compartmentation and flows of transepithelial water, NaCl, and urea and generation of the axial osmotic gradient. To accomplish this, we determined lateral distances of AQP1-positive and AQP1-negative DTLs and ATLs from their nearest CDs, so as to gauge interactions with intercluster and intracluster lateral regions and interactions with interstitial nodal spaces (INSs). DTLs express reduced AQP1 and low transepithelial water permeability along their deepest segments. Deep AQP1-null segments, prebend segments, and ATLs lie equally near to CDs. Prebend segments and ATLs abut CDs and INSs throughout much of their descent and ascent, respectively; however, the distal 30% of ATLs of the longest loops lie distant from CDs as they approach the outer medullary boundary and have minimal interaction with INSs. These relationships occur regardless of loop length. Finally, we show that ascending vasa recta separate intercluster AQP1-positive DTLs from descending vasa recta, thereby minimizing dilution of gradients that drive solute secretion. We hypothesize that DTLs and ATLs enter and exit CD clusters in an orchestrated fashion that is important for generation of the corticopapillary solute gradient by minimizing NaCl and urea loss.

Stepwise Assembly and Characterization of DNA Linked Two-Color Quantum Dot Clusters.

PubMed

Coopersmith, Kaitlin; Han, Hyunjoo; Maye, Mathew M

2015-07-14

The DNA-mediated self-assembly of multicolor quantum dot (QD) clusters via a stepwise approach is described. The CdSe/ZnS QDs were synthesized and functionalized with an amphiphilic copolymer, followed by ssDNA conjugation. At each functionalization step, the QDs were purified via gradient ultracentrifugation, which was found to remove excess polymer and QD aggregates, allowing for improved conjugation yields and assembly reactivity. The QDs were then assembled and disassembled in a stepwise manner at a ssDNA functionalized magnetic colloid, which provided a convenient way to remove unreacted QDs and ssDNA impurities. After assembly/disassembly, the clusters' optical characteristics were studied by fluorescence spectroscopy and the assembly morphology and stoichiometry was imaged via electron microscopy. The results indicate that a significant amount of QD-to-QD energy transfer occurred in the clusters, which was studied as a function of increasing acceptor-to-donor ratios, resulting in increased QD acceptor emission intensities compared to controls.

Hamiltonian and Thermodynamic Modeling of Quantum Turbulence

NASA Astrophysics Data System (ADS)

Grmela, Miroslav

2010-10-01

The state variables in the novel model introduced in this paper are the fields playing this role in the classical Landau-Tisza model and additional fields of mass, entropy (or temperature), superfluid velocity, and gradient of the superfluid velocity, all depending on the position vector and another tree dimensional vector labeling the scale, describing the small-scale structure developed in 4He superfluid experiencing turbulent motion. The fluxes of mass, momentum, energy, and entropy in the position space as well as the fluxes of energy and entropy in scales, appear in the time evolution equations as explicit functions of the state variables and of their conjugates. The fundamental thermodynamic relation relating the fields to their conjugates is left in this paper undetermined. The GENERIC structure of the equations serves two purposes: (i) it guarantees that solutions to the governing equations, independently of the choice of the fundamental thermodynamic relation, agree with the observed compatibility with thermodynamics, and (ii) it is used as a guide in the construction of the novel model.

COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM.

PubMed

Andén, Joakim; Katsevich, Eugene; Singer, Amit

2015-04-01

Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1984-01-01

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.

A superlinear convergence estimate for an iterative method for the biharmonic equation

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

Horn, M.A.

In [CDH] a method for the solution of boundary value problems for the biharmonic equation using conformal mapping was investigated. The method is an implementation of the classical method of Muskhelishvili. In [CDH] it was shown, using the Hankel structure, that the linear system in [Musk] is the discretization of the identify plus a compact operator, and therefore the conjugate gradient method will converge superlinearly. The purpose of this paper is to give an estimate of the superlinear convergence in the case when the boundary curve is in a Hoelder class.

Optimal control of population and coherence in three-level Λ systems

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Malinovskaya, Svetlana A.; Malinovsky, Vladimir S.

2011-08-01

Optimal control theory (OCT) implementations for an efficient population transfer and creation of maximum coherence in a three-level system are considered. We demonstrate that the half-stimulated Raman adiabatic passage scheme for creation of the maximum Raman coherence is the optimal solution according to the OCT. We also present a comparative study of several implementations of OCT applied to the complete population transfer and creation of the maximum coherence. Performance of the conjugate gradient method, the Zhu-Rabitz method and the Krotov method has been analysed.

Lattice QCD calculation using VPP500

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

Kim, Seyong; Ohta, Shigemi

1995-02-01

A new vector parallel supercomputer, Fujitsu VPP500, was installed at RIKEN earlier this year. It consists of 30 vector computers, each with 1.6 GFLOPS peak speed and 256 MB memory, connected by a crossbar switch with 400 MB/s peak data transfer rate each way between any pair of nodes. The authors developed a Fortran lattice QCD simulation code for it. It runs at about 1.1 GFLOPS sustained per node for Metropolis pure-gauge update, and about 0.8 GFLOPS sustained per node for conjugate gradient inversion of staggered fermion matrix.

News on Seeking Gaia's Astrometric Core Solution with AGIS

NASA Astrophysics Data System (ADS)

Lammers, U.; Lindegren, L.

We report on recent new developments around the Astrometric Global Iterative Solution system. This includes the availability of an efficient Conjugate Gradient solver and the Generic Astrometric Calibration scheme that had been proposed a while ago. The number of primary stars to be included in the core solution is now believed to be significantly higher than the 100 Million that served as baseline until now. Cloud computing services are being studied as a possible cost-effective alternative to running AGIS on dedicated computing hardware at ESAC during the operational phase.

Design and characterization of nanomaterial-biomolecule conjugates

NASA Astrophysics Data System (ADS)

Yim, Tae-Jin

In the field of nanobiotechnology, nanoscale dimensions result in physical properties that differ from more conventional bulk material state. The integration of nanomaterials with biomolecules has begun to be used for unique physical properties, and for biological specific recognition, thereby leading to novel nanomaterial-biomolecule conjugates. The direction of this dissertation is to develop biocatalytic nanomaterial-biomolecule conjugates and to characterize them. For this, biological catalysts are employed to combine with nanomaterials. Two large parts include functional ization of nanomaterials with biomolecules and assembly of nanomaterials using a biological catalyst. First part of this thesis work is the exploration of the biocatalytic properties of nanomaterial-biomolecule conjugates. Si nanocolumns have higher surface area which leads more amount of biocatalytis immobilization than flat Si wafer with the same projected area. The enhanced activity of soybean peroxidase (SBP) immobilized onto Si nanocolumns as novel nanostructured supports is focused. Next, the catalytic activity of immobilized DNAzyme onto multiwalled carbon nanotubes (MWNTs) is compared to that in solution phase, and multiple turnovers are examined. The relationship between hybridization efficiency and activity is investigated as a function of surface density of DNAzyme on MWNTs. Then, cellular delivery of silica nanoparticle-protein conjugates is visually confirmed and therefore the intracellular function of a protein delivered by silica nanoparticle-protein conjugates is proved. For one example of the intracellular function, stable SBP immobilized onto silica nanoparticles to activate a prodrug is demonstrated. Second part of this thesis work is the formation of nanostructured materials through the enzymatic assembly of single-walled carbon nanotubes (SWNTs). Enzymatic polymerization of a phenol compound is applied to the bridging of two or more SWNTs functionalized with phenol monomers. Next, future work based on previous works is proposed; first, the cellular delivery of DNAzyme using SWNTs is proposed to be a promising nonviral nanovehicle for gene silencing. Second, hydrophobic/hydrophilic switchable surface using DNAzyme is suggested to expand its usage to hydrophobically gradient surface. Finally, reversible assembly and disassembly of poly-L-histidine coated MWNTs can be applied to a reversible nanotube patterning on surface. And, the expansion of the works presented in this thesis to "nanomedicine" is suggested.

Numerical methods for the design of gradient-index optical coatings.

PubMed

Anzengruber, Stephan W; Klann, Esther; Ramlau, Ronny; Tonova, Diana

2012-12-01

We formulate the problem of designing gradient-index optical coatings as the task of solving a system of operator equations. We use iterative numerical procedures known from the theory of inverse problems to solve it with respect to the coating refractive index profile and thickness. The mathematical derivations necessary for the application of the procedures are presented, and different numerical methods (Landweber, Newton, and Gauss-Newton methods, Tikhonov minimization with surrogate functionals) are implemented. Procedures for the transformation of the gradient coating designs into quasi-gradient ones (i.e., multilayer stacks of homogeneous layers with different refractive indices) are also developed. The design algorithms work with physically available coating materials that could be produced with the modern coating technologies.

Single-pipetting microfluidic assay device for rapid detection of Salmonella from poultry package.

PubMed

Fronczek, Christopher F; You, David J; Yoon, Jeong-Yeol

2013-02-15

A direct, sensitive, near-real-time, handheld optical immunoassay device was developed to detect Salmonella typhimurium in the naturally occurring liquid from fresh poultry packages (hereafter "chicken matrix"), with just single pipetting of sample (i.e., no filtration, culturing and/or isolation, thus reducing the assay time and the error associated with them). Carboxylated, polystyrene microparticles were covalently conjugated with anti-Salmonella, and the immunoagglutination due to the presence of Salmonella was detected by reading the Mie scatter signals from the microfluidic channels using a handheld device. The presence of chicken matrix did not affect the light scatter signal, since the optical parameters (particle size d, wavelength of incident light λ and scatter angle θ) were optimized to minimize the effect of sample matrix (animal tissues and blood proteins, etc.). The sample was loaded into a microfluidic chip that was split into two channels, one pre-loaded with vacuum-dried, antibody-conjugated particles and the other with vacuum-dried, bovine serum albumin-conjugated particles. This eliminated the need for a separate negative control, effectively minimizing chip-to-chip and sample-to-sample variations. Particles and the sample were diffused in-channel through chemical agitation by Tween 80, also vacuum-dried within the microchannels. Sequential mixing of the sample to the reagents under a strict laminar flow condition synergistically improved the reproducibility and linearity of the assay. In addition, dried particles were shown to successfully detect lower Salmonella concentrations for up to 8 weeks. The handheld device contains simplified circuitry eliminating unnecessary adjustment stages, providing a stable signal, thus maximizing sensitivity. Total assay time was 10 min, and the detection limit 10 CFU mL(-1) was observed in all matrices, demonstrating the suitability of this device for field assays. Copyright © 2012 Elsevier B.V. All rights reserved.

Artificial Bee Colony Optimization of Capping Potentials for Hybrid Quantum Mechanical/Molecular Mechanical Calculations.

PubMed

Schiffmann, Christoph; Sebastiani, Daniel

2011-05-10

We present an algorithmic extension of a numerical optimization scheme for analytic capping potentials for use in mixed quantum-classical (quantum mechanical/molecular mechanical, QM/MM) ab initio calculations. Our goal is to minimize bond-cleavage-induced perturbations in the electronic structure, measured by means of a suitable penalty functional. The optimization algorithm-a variant of the artificial bee colony (ABC) algorithm, which relies on swarm intelligence-couples deterministic (downhill gradient) and stochastic elements to avoid local minimum trapping. The ABC algorithm outperforms the conventional downhill gradient approach, if the penalty hypersurface exhibits wiggles that prevent a straight minimization pathway. We characterize the optimized capping potentials by computing NMR chemical shifts. This approach will increase the accuracy of QM/MM calculations of complex biomolecules.

Multimodal medical image fusion by combining gradient minimization smoothing filter and non-subsampled directional filter bank

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Wenbo, Mei; Huiqian, Du; Zexian, Wang

2018-04-01

A new algorithm was proposed for medical images fusion in this paper, which combined gradient minimization smoothing filter (GMSF) with non-sampled directional filter bank (NSDFB). In order to preserve more detail information, a multi scale edge preserving decomposition framework (MEDF) was used to decompose an image into a base image and a series of detail images. For the fusion of base images, the local Gaussian membership function is applied to construct the fusion weighted factor. For the fusion of detail images, NSDFB was applied to decompose each detail image into multiple directional sub-images that are fused by pulse coupled neural network (PCNN) respectively. The experimental results demonstrate that the proposed algorithm is superior to the compared algorithms in both visual effect and objective assessment.

Classical Optimal Control for Energy Minimization Based On Diffeomorphic Modulation under Observable-Response-Preserving Homotopy.

PubMed

Soley, Micheline B; Markmann, Andreas; Batista, Victor S

2018-06-12

We introduce the so-called "Classical Optimal Control Optimization" (COCO) method for global energy minimization based on the implementation of the diffeomorphic modulation under observable-response-preserving homotopy (DMORPH) gradient algorithm. A probe particle with time-dependent mass m( t;β) and dipole μ( r, t;β) is evolved classically on the potential energy surface V( r) coupled to an electric field E( t;β), as described by the time-dependent density of states represented on a grid, or otherwise as a linear combination of Gaussians generated by the k-means clustering algorithm. Control parameters β defining m( t;β), μ( r, t;β), and E( t;β) are optimized by following the gradients of the energy with respect to β, adapting them to steer the particle toward the global minimum energy configuration. We find that the resulting COCO algorithm is capable of resolving near-degenerate states separated by large energy barriers and successfully locates the global minima of golf potentials on flat and rugged surfaces, previously explored for testing quantum annealing methodologies and the quantum optimal control optimization (QuOCO) method. Preliminary results show successful energy minimization of multidimensional Lennard-Jones clusters. Beyond the analysis of energy minimization in the specific model systems investigated, we anticipate COCO should be valuable for solving minimization problems in general, including optimization of parameters in applications to machine learning and molecular structure determination.

Theoretical analysis of single molecule spectroscopy lineshapes of conjugated polymers

NASA Astrophysics Data System (ADS)

Devi, Murali

Conjugated Polymers(CPs) exhibit a wide range of highly tunable optical properties. Quantitative and detailed understanding of the nature of excitons responsible for such a rich optical behavior has significant implications for better utilization of CPs for more efficient plastic solar cells and other novel optoelectronic devices. In general, samples of CPs are plagued with substantial inhomogeneous broadening due to various sources of disorder. Single molecule emission spectroscopy (SMES) offers a unique opportunity to investigate the energetics and dynamics of excitons and their interactions with phonon modes. The major subject of the present thesis is to analyze and understand room temperature SMES lineshapes for a particular CP, called poly(2,5-di-(2'-ethylhexyloxy)-1,4-phenylenevinylene) (DEH-PPV). A minimal quantum mechanical model of a two-level system coupled to a Brownian oscillator bath is utilized. The main objective is to identify the set of model parameters best fitting a SMES lineshape for each of about 200 samples of DEH-PPV, from which new insight into the nature of exciton-bath coupling can be gained. This project also entails developing a reliable computational methodology for quantum mechanical modeling of spectral lineshapes in general. Well-known optimization techniques such as gradient descent, genetic algorithms, and heuristic searches have been tested, employing an L2 measure between theoretical and experimental lineshapes for guiding the optimization. However, all of these tend to result in theoretical lineshapes qualitatively different from experimental ones. This is attributed to the ruggedness of the parameter space and inadequateness of the L2 measure. On the other hand, when the dynamic reduction of the original parameter space to a 2-parameter space through feature searching and visualization of the search space paths using directed acyclic graphs(DAGs), the qualitative nature of the fitting improved significantly. For a more satisfactory fitting, it is shown that the inclusion of an additional energetic disorder is essential, representing the effect of quasi-static disorder accumulated during the SMES of each polymer. Various technical details, ambiguous issues, and implication of the present work are discussed.

Computational study of the effect of gradient magnetic field in navigation of spherical particles

NASA Astrophysics Data System (ADS)

Karvelas, E. G.; Lampropoulos, N. K.; Papadimitriou, D. I.; Karakasidis, T. E.; Sarris, I. E.

2017-11-01

The use of spherical magnetic nanoparticles that are coated with drugs and can be navigated in arteries to attack tumors is proposed as an alternative to chemotherapy. Navigation of particles is due to magnetic field gradients that may be produced in an MRI device. In the present work, a computational study for the evaluation of the magnitude of the gradient magnetic field for particles navigation in Y bifurcations is presented. For this purpose, the presented method solves for the fluid flow and includes all the important forces that act on the particles in their discrete motion. The method is based on an iteration algorithm that adjusts the gradient magnetic field to minimize the particles’ deviation from a desired trajectory. Using the above mentioned method, the appropriate range of the gradient magnetic field for optimum navigation of nanoparticles’s aggregation is found.

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

PubMed

Gilles, Luc; Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Ellerbroek, Brent

2013-05-01

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

PubMed

Qiu, W; Titley-Peloquin, D; Soleimani, M

2012-11-01

Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics

NASA Astrophysics Data System (ADS)

Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

2003-09-01

Multiconjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wave-front control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10-2 Hz, i.e., 4-5 orders of magnitude lower than the typical 103 Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.

Use of general purpose graphics processing units with MODFLOW

USGS Publications Warehouse

Hughes, Joseph D.; White, Jeremy T.

2013-01-01

To evaluate the use of general-purpose graphics processing units (GPGPUs) to improve the performance of MODFLOW, an unstructured preconditioned conjugate gradient (UPCG) solver has been developed. The UPCG solver uses a compressed sparse row storage scheme and includes Jacobi, zero fill-in incomplete, and modified-incomplete lower-upper (LU) factorization, and generalized least-squares polynomial preconditioners. The UPCG solver also includes options for sequential and parallel solution on the central processing unit (CPU) using OpenMP. For simulations utilizing the GPGPU, all basic linear algebra operations are performed on the GPGPU; memory copies between the central processing unit CPU and GPCPU occur prior to the first iteration of the UPCG solver and after satisfying head and flow criteria or exceeding a maximum number of iterations. The efficiency of the UPCG solver for GPGPU and CPU solutions is benchmarked using simulations of a synthetic, heterogeneous unconfined aquifer with tens of thousands to millions of active grid cells. Testing indicates GPGPU speedups on the order of 2 to 8, relative to the standard MODFLOW preconditioned conjugate gradient (PCG) solver, can be achieved when (1) memory copies between the CPU and GPGPU are optimized, (2) the percentage of time performing memory copies between the CPU and GPGPU is small relative to the calculation time, (3) high-performance GPGPU cards are utilized, and (4) CPU-GPGPU combinations are used to execute sequential operations that are difficult to parallelize. Furthermore, UPCG solver testing indicates GPGPU speedups exceed parallel CPU speedups achieved using OpenMP on multicore CPUs for preconditioners that can be easily parallelized.

A microfluidic chip with a staircase pH gradient generator, a packed column and a fraction collector for chromatofocusing of proteins.

PubMed

Rho, Hoon Suk; Hanke, Alexander Thomas; Ottens, Marcel; Gardeniers, Han J G E

2018-04-01

A microfluidic device for pH gradient chromatofocusing is presented, which performs creation of a micro-column, pH gradient generation, and fraction collection in a single device. Using a sieve micro-valve, anion exchange particles were packed into a microchannel in order to realize a solid-phase absorption column. To fractionate proteins according to their isoelectric points, elution buffer solutions with a stepwise pH gradient were prepared in 16 parallel mixing reactors and flowed through the micro-column, wherein a protein mixture was previously loaded. The volume of the column is only 20 nL, hence it allows extremely low sample consumption and fast analysis compared with a conventional system. We demonstrated separation of two proteins, albumin-fluorescein isothiocyanate conjugate (FITC-BSA) and R-Phycoerythrin (R-PE), by using a microcolumn of commercial charged polymeric particles (Source 15Q). The microfluidic device can be used as a rapid diagnostic tool to analyse crude mixtures of proteins or nucleic acids and determine adsorption/desorption characteristics of various biochemical products, which can be helpful for scientific fundamental understanding as well as instrumental in various industrial applications, especially in early stage screening and process development. © 2018 The Authors Electrophoresis Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stability issues in the determination of 19 urinary (free and conjugated) monohydroxy polycyclic aromatic hydrocarbons.

PubMed

Gaudreau, Éric; Bérubé, René; Bienvenu, Jean-François; Fleury, Normand

2016-06-01

Data on the stability of monohydroxy polycyclic aromatic hydrocarbons (OH-PAHs; metabolites of PAHs) in urine are needed in order to effectively study the effects of PAHs in the body, but the relevant data are not available in the literature. Therefore, in this work, we investigated the stability of OH-PAHs in urine. For each OH-PAH studied, the free form (as opposed to the conjugated form) comprised <10 % of the total OH-PAH in urine samples obtained from a normal population, except for 9-OH-phenanthrene (where the free form represented 22.2 % of the total 9-OH-phenanthrene). 1-Naphthol and 9-OH-phenanthrene were found to be less stable in their free forms in urine than in their conjugated forms when the urine samples were stored at 4 °C or room temperature. Free 3-OH-fluoranthene was also very unstable at 4 °C or room temperature. The conjugated forms of the OH-PAHs were more stable than their corresponding free forms. However, the free and conjugated forms of all the OH-PAHs were stable in urine at -20 °C and -80 °C. A freeze and thaw assay also revealed that freezing and thawing had minimal impact on the stability of the OH-PAHs in urine. For the derivatized extracts, storing the samples under an argon atmosphere at 4 °C was found to maintain sample integrity. In order to measure the stabilities of 19 hydroxylated metabolites of PAHs in urine, we developed a method with sensitivity in the low pg/mL range using nine labeled internal standards. This method combined enzymatic deconjugation with liquid-liquid extraction, derivatization with N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA), and gas chromatography/tandem mass spectrometry (GC-MS/MS). Graphical abstract Stability of the conjugated forms of the OH-PAHs versus free forms (e.g. 1-naphthol).

Effect of mannose targeting of hydroxyl PAMAM dendrimers on cellular and organ biodistribution in a neonatal brain injury model.

PubMed

Sharma, Anjali; Porterfield, Joshua E; Smith, Elizabeth; Sharma, Rishi; Kannan, Sujatha; Kannan, Rangaramanujam M

2018-06-05

Neurotherapeutics for the treatment of central nervous system (CNS) disorders must overcome challenges relating to the blood-brain barrier (BBB), brain tissue penetration, and the targeting of specific cells. Neuroinflammation mediated by activated microglia is a major hallmark of several neurological disorders, making these cells a desirable therapeutic target. Building on the promise of hydroxyl-terminated generation four polyamidoamine (PAMAM) dendrimers (D4-OH) for penetrating the injured BBB and targeting activated glia, we explored if conjugation of targeting ligands would enhance and modify brain and organ uptake. Since mannose receptors [cluster of differentiation (CD) 206] are typically over-expressed on injured microglia, we conjugated mannose to the surface of multifunctional D4-OH using highly efficient, atom-economical, and orthogonal Cu(I)-catalyzed alkyne-azide cycloaddition (CuAAC) click chemistry and evaluated the effect of mannose conjugation on the specific cell uptake of targeted and non-targeted dendrimers both in vitro and in vivo. In vitro results indicate that the conjugation of mannose as a targeting ligand significantly changes the mechanism of dendrimer internalization, giving mannosylated dendrimer a preference for mannose receptor-mediated endocytosis as opposed to non-specific fluid phase endocytosis. We further investigated the brain uptake and biodistribution of targeted and non-targeted fluorescently labeled dendrimers in a maternal intrauterine inflammation-induced cerebral palsy (CP) rabbit model using quantification methods based on fluorescence spectroscopy and confocal microscopy. We found that the conjugation of mannose modified the distribution of D4-OH throughout the body in this neonatal rabbit CP model without lowering the amount of dendrimer delivered to injured glia in the brain, even though significantly higher glial uptake was not observed in this model. Mannose conjugation to the dendrimer modifies the dendrimer's interaction with cells, but does not minimize its inherent inflammation-targeting abilities. Copyright © 2018 Elsevier B.V. All rights reserved.

Effective oral delivery of insulin in animal models using vitamin B12-coated dextran nanoparticles.

PubMed

Chalasani, Kishore B; Russell-Jones, Gregory J; Jain, Akhlesh K; Diwan, Prakash V; Jain, Sanjay K

2007-09-26

The potential utility of vitamin B12 carrier system for the oral delivery of conjugated peptides/proteins and enhancement of nanoparticles (NPs) transport has been demonstrated. The present study aims to optimize the effectiveness of VB12-NPs conjugates using different levels of cross-linking, linked with different VB(12)-coatings and evaluates in animal models to investigate an efficient insulin carrier. Amino alkyl VB12 derivatives suitable for oral delivery were synthesized at 5'hydoxy ribose and e-propionamide sites via carbamate and ester/amide linkages, and were coupled to succinic acid modified dextran NPs of varied cross-linking. VB12 binding was confirmed by XPS analysis, and was quantified by HPLC (4.0 to 5.7% w/w of NPs). These polydisperse NPs conjugates showed higher size, high insulin entrapment and faster insulin release with low levels of cross-linking. These VB12-NPs conjugates (150-300 nm) showed profound (70-75% blood glucose reductions) and prolonged (54 h) anti-diabetic effects with biphasic behaviour in STZ diabetic rats. NPs with the low levels of cross-linking were found to be superior carriers, and were more effective with VB12 derivatives of carbamate linkage. The pharmacological availability relative to SC insulin was found to be 29.4%, which was superior compared to NPs conjugate of ester linked VB12 (1.5 fold) and relatively higher cross-linked particles (1.1 fold). Further, the NPs carrier demonstrated a similar oral insulin efficacy in congenital diabetic mice (60% reduction at 20 h). Significant quantities of plasma insulin were found in both animal models (231 and 197 muIU/ml). At two investigated doses, the carrier system shows dose response. Pre-dosing with a large excess of free VB12 minimized the observed activity, indicating predominance of VB12 mediated uptake. It is concluded that VB12-dextran NPs conjugate is a viable carrier for peroral insulin delivery to treat diabetics.

Nanodiamond-DGEA peptide conjugates for enhanced delivery of doxorubicin to prostate cancer

PubMed Central

Hwang, Patrick; McIntosh, Roberus; Green, Hadiyah N; Jun, Ho-Wook; Dean, Derrick

2014-01-01

Summary The field of nanomedicine has emerged as an approach to enhance the specificity and efficacy of cancer treatments as stand-alone therapies and in combination with standard chemotherapeutic treatment regimens. The current standard of care for metastatic cancer, doxorubicin (DOX), is presented with challenges, namely toxicity due to a lack of specificity and targeted delivery. Nano-enabled targeted drug delivery systems can provide an avenue to overcome these issues. Nanodiamonds (ND), in particular, have been researched over the past five years for use in various drug delivery systems but minimal work has been done that incorporates targeting capability. In this study, a novel targeted drug delivery system for bone metastatic prostate cancer was developed, characterized, and evaluated in vitro. NDs were conjugated with the Asp–Gly–Glu–Ala (DGEA) peptide to target α2β1 integrins over-expressed in prostate cancers during metastasis. To facilitate drug delivery, DOX was adsorbed to the surface of the ND-DGEA conjugates. Successful preparation of the ND-DGEA conjugates and the ND-DGEA+DOX system was confirmed with transmission electron microscopy, hydrodynamic size, and zeta potential measurements. Since traditional DOX treatment regimens lack specificity and increased toxicity to normal tissues, the ND-DGEA conjugates were designed to distinguish between cells that overexpress α2β1 integrin, bone metastatic prostate cancers cells (PC3), and cells that do not, human mesenchymal stem cells (hMSC). Utilizing the ND-DGEA+DOX system, the efficacy of 1 µg/mL and 2 µg/mL DOX doses increased from 2.5% to 12% cell death and 11% to 34% cell death, respectively. These studies confirmed that the delivery and efficacy of DOX were enhanced by ND-DGEA conjugates. Thus, the targeted ND-DGEA+DOX system provides a novel approach for decreasing toxicity and drug doses. PMID:25161829

Accelerating atomic structure search with cluster regularization

NASA Astrophysics Data System (ADS)

Sørensen, K. H.; Jørgensen, M. S.; Bruix, A.; Hammer, B.

2018-06-01

We present a method for accelerating the global structure optimization of atomic compounds. The method is demonstrated to speed up the finding of the anatase TiO2(001)-(1 × 4) surface reconstruction within a density functional tight-binding theory framework using an evolutionary algorithm. As a key element of the method, we use unsupervised machine learning techniques to categorize atoms present in a diverse set of partially disordered surface structures into clusters of atoms having similar local atomic environments. Analysis of more than 1000 different structures shows that the total energy of the structures correlates with the summed distances of the atomic environments to their respective cluster centers in feature space, where the sum runs over all atoms in each structure. Our method is formulated as a gradient based minimization of this summed cluster distance for a given structure and alternates with a standard gradient based energy minimization. While the latter minimization ensures local relaxation within a given energy basin, the former enables escapes from meta-stable basins and hence increases the overall performance of the global optimization.

Containment of groundwater contamination plumes: minimizing drawdown by aligning capture wells parallel to regional flow

NASA Astrophysics Data System (ADS)

Christ, John A.; Goltz, Mark N.

2004-01-01

Pump-and-treat systems that are installed to contain contaminated groundwater migration typically involve placement of extraction wells perpendicular to the regional groundwater flow direction at the down gradient edge of a contaminant plume. These wells capture contaminated water for above ground treatment and disposal, thereby preventing further migration of contaminated water down gradient. In this work, examining two-, three-, and four-well systems, we compare well configurations that are parallel and perpendicular to the regional groundwater flow direction. We show that orienting extraction wells co-linearly, parallel to regional flow, results in (1) a larger area of aquifer influenced by the wells at a given total well flow rate, (2) a center and ultimate capture zone width equal to the perpendicular configuration, and (3) more flexibility with regard to minimizing drawdown. Although not suited for some scenarios, we found orienting extraction wells parallel to regional flow along a plume centerline, when compared to a perpendicular configuration, reduces drawdown by up to 7% and minimizes the fraction of uncontaminated water captured.

Sequentially reweighted TV minimization for CT metal artifact reduction.

PubMed

Zhang, Xiaomeng; Xing, Lei

2013-07-01

Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions. A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach. Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties. The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

A Targeting Microbubble for Ultrasound Molecular Imaging

PubMed Central

Yeh, James Shue-Min; Sennoga, Charles A.; McConnell, Ellen; Eckersley, Robert; Tang, Meng-Xing; Nourshargh, Sussan; Seddon, John M.; Haskard, Dorian O.; Nihoyannopoulos, Petros

2015-01-01

Rationale Microbubbles conjugated with targeting ligands are used as contrast agents for ultrasound molecular imaging. However, they often contain immunogenic (strept)avidin, which impedes application in humans. Although targeting bubbles not employing the biotin-(strept)avidin conjugation chemistry have been explored, only a few reached the stage of ultrasound imaging in vivo, none were reported/evaluated to show all three of the following properties desired for clinical applications: (i) low degree of non-specific bubble retention in more than one non-reticuloendothelial tissue; (ii) effective for real-time imaging; and (iii) effective for acoustic quantification of molecular targets to a high degree of quantification. Furthermore, disclosures of the compositions and methodologies enabling reproduction of the bubbles are often withheld. Objective To develop and evaluate a targeting microbubble based on maleimide-thiol conjugation chemistry for ultrasound molecular imaging. Methods and Results Microbubbles with a previously unreported generic (non-targeting components) composition were grafted with anti-E-selectin F(ab’)2 using maleimide-thiol conjugation, to produce E-selectin targeting microbubbles. The resulting targeting bubbles showed high specificity to E-selectin in vitro and in vivo. Non-specific bubble retention was minimal in at least three non-reticuloendothelial tissues with inflammation (mouse heart, kidneys, cremaster). The bubbles were effective for real-time ultrasound imaging of E-selectin expression in the inflamed mouse heart and kidneys, using a clinical ultrasound scanner. The acoustic signal intensity of the targeted bubbles retained in the heart correlated strongly with the level of E-selectin expression (|r|≥0.8), demonstrating a high degree of non-invasive molecular quantification. Conclusions Targeting microbubbles for ultrasound molecular imaging, based on maleimide-thiol conjugation chemistry and the generic composition described, may possess properties (i)–(iii) desired for clinical applications. PMID:26161541

Synthesis of Thiolated Alginate and Evaluation of Mucoadhesiveness, Cytotoxicity and Release Retardant Properties

PubMed Central

Jindal, A. B.; Wasnik, M. N.; Nair, Hema A.

2010-01-01

Modification of polymers by covalent attachment of thiol bearing pendant groups is reported to impart many beneficial properties to them. Hence in the present study, sodium alginate–cysteine conjugate was synthesized by carbodiimide mediated coupling under varying reaction conditions and the derivatives characterized for thiol content. The thiolated alginate species synthesized had bound thiol content ranging from 247.8±11.03–324.54±10.107 ΅mol/g of polymer depending on the reaction conditions. Matrix tablets based on sodium alginate-cysteine conjugate and native sodium alginate containing tramadol hydrochloride as a model drug were prepared and mucoadhesive strength and in vitro drug release from the tablets were compared. Tablets containing 75 mg sodium alginate-cysteine conjugate could sustain release of 10 mg of model drug for 3 h, whereas 90% of the drug was released within 1 h from corresponding tablets prepared using native sodium alginate. An approximately 2-fold increase in the minimal detachment force of the tablets from an artificial mucin film was observed for sodium alginate–cysteine conjugate as compared to native sodium alginate. In vitro cytotoxicity studies in L-929 mouse fibroblast cells studied using an MTT assay revealed that at low concentrations of polymer, sodium alginate–cysteine conjugate was less toxic to L-929 mouse fibroblast cell line when compared to native sodium alginate. Hence, thiolation is found to be a simple route to improving polymer performance. The combination of improved controlled drug release and mucoadhesive properties coupled with the low toxicity of these new excipients builds up immense scope for the use of thiolated polymers in mucoadhesive drug delivery systems. PMID:21969750

Site-selective conjugation of an anticoagulant aptamer to recombinant albumins and maintenance of neonatal Fc receptor binding

NASA Astrophysics Data System (ADS)

Schmøkel, Julie; Voldum, Anders; Tsakiridou, Georgia; Kuhlmann, Matthias; Cameron, Jason; Sørensen, Esben S.; Wengel, Jesper; Howard, Kenneth A.

2017-05-01

Aptamers are an attractive molecular medicine that offers high target specificity. Nucleic acid-based aptamers, however, are prone to nuclease degradation and rapid renal excretion that require blood circulatory half-life extension enabling technologies. The long circulatory half-life, predominately facilitated by engagement with the cellular recycling neonatal Fc receptor (FcRn), and ligand transport properties of albumin promote it as an attractive candidate to improve the pharmacokinetic profile of aptamers. This study investigates the effect of Cys34 site-selective covalent attachment of a factor IXa anticoagulant aptamer on aptamer functionality and human FcRn (hFcRn) engagement using recombinant human albumin (rHA) of either a wild type (WT) or an engineered human FcRn high binding variant (HB). Albumin-aptamer conjugates, connected covalently through a heterobifunctional succinimidyl 4-(N-maleimidomethyl)cyclohexane-1-carboxylate linker, were successfully prepared and purified by high performance liquid chromatography as confirmed by gel electrophoresis band-shift analysis and matrix-assisted laser desorption/ionization time of flight. Minimal reduction (∼25%) in activity of WT-linked aptamer to that of aptamer alone was found using an anticoagulant activity assay measuring temporal levels of activated partial thrombin. Covalent albumin-aptamer conjugation, however, substantially compromized binding to hFcRn, to 10% affinity of that of non-conjugated WT, determined by biolayer interferometry. Binding could be rescued by aptamer conjugation to recombinant albumin engineered for higher FcRn affinity (HB) that exhibited an 8-fold affinity compared to WT alone. This work describes a novel albumin-based aptamer delivery system whose hFcRn binding can be increased using a HB engineered albumin.

Site-selective conjugation of an anticoagulant aptamer to recombinant albumins and maintenance of neonatal Fc receptor binding.

PubMed

Schmøkel, Julie; Voldum, Anders; Tsakiridou, Georgia; Kuhlmann, Matthias; Cameron, Jason; Sørensen, Esben S; Wengel, Jesper; Howard, Kenneth A

2017-05-19

Aptamers are an attractive molecular medicine that offers high target specificity. Nucleic acid-based aptamers, however, are prone to nuclease degradation and rapid renal excretion that require blood circulatory half-life extension enabling technologies. The long circulatory half-life, predominately facilitated by engagement with the cellular recycling neonatal Fc receptor (FcRn), and ligand transport properties of albumin promote it as an attractive candidate to improve the pharmacokinetic profile of aptamers. This study investigates the effect of Cys34 site-selective covalent attachment of a factor IXa anticoagulant aptamer on aptamer functionality and human FcRn (hFcRn) engagement using recombinant human albumin (rHA) of either a wild type (WT) or an engineered human FcRn high binding variant (HB). Albumin-aptamer conjugates, connected covalently through a heterobifunctional succinimidyl 4-(N-maleimidomethyl)cyclohexane-1-carboxylate linker, were successfully prepared and purified by high performance liquid chromatography as confirmed by gel electrophoresis band-shift analysis and matrix-assisted laser desorption/ionization time of flight. Minimal reduction (∼25%) in activity of WT-linked aptamer to that of aptamer alone was found using an anticoagulant activity assay measuring temporal levels of activated partial thrombin. Covalent albumin-aptamer conjugation, however, substantially compromized binding to hFcRn, to 10% affinity of that of non-conjugated WT, determined by biolayer interferometry. Binding could be rescued by aptamer conjugation to recombinant albumin engineered for higher FcRn affinity (HB) that exhibited an 8-fold affinity compared to WT alone. This work describes a novel albumin-based aptamer delivery system whose hFcRn binding can be increased using a HB engineered albumin.

A low-cost, mechanically simple apparatus for measuring eddy current-induced magnetic fields in MRI.

PubMed

Gilbert, Kyle M; Martyn Klassen, L; Menon, Ravi S

2013-10-01

The fidelity of gradient waveforms in MRI pulse sequences is essential to the acquisition of images and spectra with minimal distortion artefacts. Gradient waveforms can become nonideal when eddy currents are created in nearby conducting structures; however, the resultant magnetic fields can be characterised and compensated for by measuring the spatial and temporal field response following a gradient impulse. This can be accomplished using a grid of radiofrequency (RF) coils. The RF coils must adhere to strict performance requirements: they must achieve a high sensitivity and signal-to-noise ratio (SNR), have minimal susceptibility field gradients between the sample and surrounding material interfaces and be highly decoupled from each other. In this study, an apparatus is presented that accomplishes these tasks with a low-cost, mechanically simple solution. The coil system consists of six transmit/receive RF coils immersed in a high-molarity saline solution. The sensitivity and SNR following an excitation pulse are sufficiently high to allow accurate phase measurements during free-induction decays; the intrinsic susceptibility matching of the materials, because of the unique design of the coil system, results in sufficiently narrow spectral line widths (mean of 19 Hz), and adjacent RF coils are highly decoupled (mean S12 of -47 dB). The temporal and spatial distributions of eddy currents following a gradient pulse are measured to validate the efficacy of the design, and the resultant amplitudes and time constants required for zeroth- and first-order compensation are provided. Copyright © 2013 John Wiley & Sons, Ltd.

Chromosomal transfers in mycoplasmas: when minimal genomes go mobile.

PubMed

Dordet-Frisoni, Emilie; Sagné, Eveline; Baranowski, Eric; Breton, Marc; Nouvel, Laurent Xavier; Blanchard, Alain; Marenda, Marc Serge; Tardy, Florence; Sirand-Pugnet, Pascal; Citti, Christine

2014-11-25

Horizontal gene transfer (HGT) is a main driving force of bacterial evolution and innovation. This phenomenon was long thought to be marginal in mycoplasmas, a large group of self-replicating bacteria characterized by minute genomes as a result of successive gene losses during evolution. Recent comparative genomic analyses challenged this paradigm, but the occurrence of chromosomal exchanges had never been formally addressed in mycoplasmas. Here, we demonstrated the conjugal transfer of large chromosomal regions within and among ruminant mycoplasma species, with the incorporation of the incoming DNA occurring by homologous recombination into the recipient chromosome. By combining classical mating experiments with high-throughput next-generation sequencing, we documented the transfer of almost every position of the mycoplasma chromosome. Mycoplasma conjugation relies on the occurrence of an integrative conjugative element (ICE) in at least one parent cell. While ICE propagates horizontally from ICE-positive to ICE-negative cells, chromosomal transfers (CTs) occurred in the opposite direction, from ICE-negative to ICE-positive cells, independently of ICE movement. These findings challenged the classical mechanisms proposed for other bacteria in which conjugative CTs are driven by conjugative elements, bringing into the spotlight a new means for rapid mycoplasma innovation. Overall, they radically change our current views concerning the evolution of mycoplasmas, with particularly far-reaching implications given that over 50 species are human or animal pathogens. Horizontal gene transfers (HGT) shape bacterial genomes and are key contributors to microbial diversity and innovation. One main mechanism involves conjugation, a process that allows the simultaneous transfer of significant amounts of DNA upon cell-to-cell contact. Recognizing and deciphering conjugal mechanisms are thus essential in understanding the impact of gene flux on bacterial evolution. We addressed this issue in mycoplasmas, the smallest and simplest self-replicating bacteria. In these organisms, HGT was long thought to be marginal. We showed here that nearly every position of the Mycoplasma agalactiae chromosome could be transferred via conjugation, using an unconventional mechanism. The transfer involved DNA blocks containing up to 80 genes that were incorporated into the host chromosome by homologous recombination. These findings radically change our views concerning mycoplasma evolution and adaptation with particularly far-reaching implications given that over 50 species are human or animal pathogens. Copyright © 2014 Dordet-Frisoni et al.

Improving Global Mass Flux Solutions from Gravity Recovery and Climate Experiment (GRACE) Through Forward Modeling and Continuous Time Correlation

NASA Technical Reports Server (NTRS)

Sabaka, T. J.; Rowlands, D. D.; Luthcke, S. B.; Boy, J.-P.

2010-01-01

We describe Earth's mass flux from April 2003 through November 2008 by deriving a time series of mas cons on a global 2deg x 2deg equal-area grid at 10 day intervals. We estimate the mass flux directly from K band range rate (KBRR) data provided by the Gravity Recovery and Climate Experiment (GRACE) mission. Using regularized least squares, we take into account the underlying process dynamics through continuous space and time-correlated constraints. In addition, we place the mascon approach in the context of other filtering techniques, showing its equivalence to anisotropic, nonsymmetric filtering, least squares collocation, and Kalman smoothing. We produce mascon time series from KBRR data that have and have not been corrected (forward modeled) for hydrological processes and fmd that the former produce superior results in oceanic areas by minimizing signal leakage from strong sources on land. By exploiting the structure of the spatiotemporal constraints, we are able to use a much more efficient (in storage and computation) inversion algorithm based upon the conjugate gradient method. This allows us to apply continuous rather than piecewise continuous time-correlated constraints, which we show via global maps and comparisons with ocean-bottom pressure gauges, to produce time series with reduced random variance and full systematic signal. Finally, we present a preferred global model, a hybrid whose oceanic portions are derived using forward modeling of hydrology but whose land portions are not, and thus represent a pure GRACE-derived signal.

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

PubMed

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

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

HFEM3D

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

Weiss, Chester J

Software solves the three-dimensional Poisson equation div(k(grad(u)) = f, by the finite element method for the case when material properties, k, are distributed over hierarchy of edges, facets and tetrahedra in the finite element mesh. Method is described in Weiss, CJ, Finite element analysis for model parameters distributed on a hierarchy of geometric simplices, Geophysics, v82, E155-167, doi:10.1190/GEO2017-0058.1 (2017). A standard finite element method for solving Poisson’s equation is augmented by including in the 3D stiffness matrix additional 2D and 1D stiffness matrices representing the contributions from material properties associated with mesh faces and edges, respectively. The resulting linear systemmore » is solved iteratively using the conjugate gradient method with Jacobi preconditioning. To minimize computer storage for program execution, the linear solver computes matrix-vector contractions element-by-element over the mesh, without explicit storage of the global stiffness matrix. Program output vtk compliant for visualization and rendering by 3rd party software. Program uses dynamic memory allocation and as such there are no hard limits on problem size outside of those imposed by the operating system and configuration on which the software is run. Dimension, N, of the finite element solution vector is constrained by the the addressable space in 32-vs-64 bit operating systems. Total storage requirements for the problem. Total working space required for the program is approximately 13*N double precision words.« less

Dynamic Changes of IsiA-Containing Complexes during Long-Term Iron Deficiency in Synechocystis sp. PCC 6803.

PubMed

Ma, Fei; Zhang, Xin; Zhu, Xi; Li, Tianpei; Zhan, Jiao; Chen, Hui; He, Chenliu; Wang, Qiang

2017-01-09

Iron stress-induced protein A (IsiA), a major chlorophyll-binding protein in the thylakoid membrane, is significantly induced under iron deficiency conditions. Using immunoblot analysis and 77 K fluorescence spectroscopy combined with sucrose gradient fractionation, we monitored dynamic changes of IsiA-containing complexes in Synechocystis sp. PCC 6803 during exposure to long-term iron deficiency. Within 3 days of exposure to iron deficiency conditions, the initially induced free IsiA proteins preferentially conjugated to PS I trimer to form IsiA 18 -PS I trimers, which serve as light energy collectors for efficiently transmitting energy to PS I. With prolonged iron deficiency, IsiA proteins assembled either into IsiA aggregates or into two other types of IsiA-PS I supercomplexes, namely IsiA-PS I high fluorescence supercomplex (IHFS) and IsiA-PS I low fluorescence supercomplex (ILFS). Further analysis revealed a role for IsiA as an energy dissipater in the IHFS and as an energy collector in the ILFS. The trimeric structure of PS I mediated by PsaL was found to be indispensable for the formation of IHFS/ILFS. Dynamic changes in IsiA-containing complexes in cyanobacteria during long-term iron deficiency may represent an adaptation to iron limitation stress for flexible light energy distribution, which balances electron transfer between PS I and PS II, thus minimizing photooxidative damage. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.

Behaviour and physiology: the thermal strategy of leatherback turtles.

PubMed

Bostrom, Brian L; Jones, T Todd; Hastings, Mervin; Jones, David R

2010-11-10

Adult leatherback turtles (Dermochelys coriacea) exhibit thermal gradients between their bodies and the environment of ≥8°C in sub-polar waters and ≤4°C in the tropics. There has been no direct evidence for thermoregulation in leatherbacks although modelling and morphological studies have given an indication of how thermoregulation may be achieved. We show for the first time that leatherbacks are indeed capable of thermoregulation from studies on juvenile leatherbacks of 16 and 37 kg. In cold water (< 25°C), flipper stroke frequency increased, heat loss through the plastron, carapace and flippers was minimized, and a positive thermal gradient of up to 2.3°C was maintained between body and environment. In warm water (25 - 31°C), turtles were inactive and heat loss through their plastron, carapace and flippers increased. The thermal gradient was minimized (0.5°C). Using a scaling model, we estimate that a 300 kg adult leatherback is able to maintain a maximum thermal gradient of 18.2°C in cold sub-polar waters. In juvenile leatherbacks, heat gain is controlled behaviourally by increasing activity while heat flux is regulated physiologically, presumably by regulation of blood flow distribution. Hence, harnessing physiology and behaviour allows leatherbacks to keep warm while foraging in cold sub-polar waters and to prevent overheating in a tropical environment.

Behaviour and Physiology: The Thermal Strategy of Leatherback Turtles

PubMed Central

Bostrom, Brian L.; Jones, T. Todd; Hastings, Mervin; Jones, David R.

2010-01-01

Background Adult leatherback turtles (Dermochelys coriacea) exhibit thermal gradients between their bodies and the environment of ≥8°C in sub-polar waters and ≤4°C in the tropics. There has been no direct evidence for thermoregulation in leatherbacks although modelling and morphological studies have given an indication of how thermoregulation may be achieved. Methodology/Principal Findings We show for the first time that leatherbacks are indeed capable of thermoregulation from studies on juvenile leatherbacks of 16 and 37 kg. In cold water (< 25°C), flipper stroke frequency increased, heat loss through the plastron, carapace and flippers was minimized, and a positive thermal gradient of up to 2.3°C was maintained between body and environment. In warm water (25 – 31°C), turtles were inactive and heat loss through their plastron, carapace and flippers increased. The thermal gradient was minimized (0.5°C). Using a scaling model, we estimate that a 300 kg adult leatherback is able to maintain a maximum thermal gradient of 18.2°C in cold sub-polar waters. Conclusions/Significance In juvenile leatherbacks, heat gain is controlled behaviourally by increasing activity while heat flux is regulated physiologically, presumably by regulation of blood flow distribution. Hence, harnessing physiology and behaviour allows leatherbacks to keep warm while foraging in cold sub-polar waters and to prevent overheating in a tropical environment. PMID:21085716

Use of optimization to predict the effect of selected parameters on commuter aircraft performance

NASA Technical Reports Server (NTRS)

Wells, V. L.; Shevell, R. S.

1982-01-01

The relationships between field length and cruise speed and aircraft direct operating cost were determined. A gradient optimizing computer program was developed to minimize direct operating cost (DOC) as a function of airplane geometry. In this way, the best airplane operating under one set of constraints can be compared with the best operating under another. A constant 30-passenger fuselage and rubberized engines based on the General Electric CT-7 were used as a baseline. All aircraft had to have a 600 nautical mile maximum range and were designed to FAR part 25 structural integrity and climb gradient regulations. Direct operating cost was minimized for a typical design mission of 150 nautical miles. For purposes of C sub L sub max calculation, all aircraft had double-slotted flaps but with no Fowler action.

Ghost circles in lattice Aubry-Mather theory

NASA Astrophysics Data System (ADS)

Mramor, Blaz; Rink, Bob

Monotone lattice recurrence relations such as the Frenkel-Kontorova lattice, arise in Hamiltonian lattice mechanics, as models for ferromagnetism and as discretization of elliptic PDEs. Mathematically, they are a multi-dimensional counterpart of monotone twist maps. Such recurrence relations often admit a variational structure, so that the solutions x:Z→R are the stationary points of a formal action function W(x). Given any rotation vector ω∈R, classical Aubry-Mather theory establishes the existence of a large collection of solutions of ∇W(x)=0 of rotation vector ω. For irrational ω, this is the well-known Aubry-Mather set. It consists of global minimizers and it may have gaps. In this paper, we study the parabolic gradient flow {dx}/{dt}=-∇W(x) and we will prove that every Aubry-Mather set can be interpolated by a continuous gradient-flow invariant family, the so-called 'ghost circle'. The existence of these ghost circles is known in dimension d=1, for rational rotation vectors and Morse action functions. The main technical result of this paper is therefore a compactness theorem for lattice ghost circles, based on a parabolic Harnack inequality for the gradient flow. This implies the existence of lattice ghost circles of arbitrary rotation vectors and for arbitrary actions. As a consequence, we can give a simple proof of the fact that when an Aubry-Mather set has a gap, then this gap must be filled with minimizers, or contain a non-minimizing solution.

Transferrin-Conjugated Nanocarriers as Active-Targeted Drug Delivery Platforms for Cancer Therapy.

PubMed

Nogueira-Librelotto, Daniele R; Codevilla, Cristiane F; Farooqi, Ammad; Rolim, Clarice M B

2017-01-01

A lot of effort has been devoted to achieving active targeting for cancer therapy in order to reach the right cells. Hence, increasingly it is being realized that active-targeted nanocarriers notably reduce off-target effects, mainly because of targeted localization in tumors and active cellular uptake. In this context, by taking advantage of the overexpression of transferrin receptors on the surface of tumor cells, transferrin-conjugated nanodevices have been designed, in hope that the biomarker grafting would help to maximize the therapeutic benefit and to minimize the side effects. Notably, active targeting nanoparticles have shown improved therapeutic performances in different tumor models as compared to their passive targeting counterparts. In this review, current development of nano-based devices conjugated with transferrin for active tumor-targeting drug delivery are highlighted and discussed. The main objective of this review is to provide a summary of the vast types of nanomaterials that have been used to deliver different chemotherapeutics into tumor cells, and to ultimately evaluate the progression on the strategies for cancer therapy in view of the future research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Azide–Alkyne Click Conjugation on Quantum Dots by Selective Copper Coordination

PubMed Central

Mann, Victor R.; Powers, Alexander S.; Tilley, Drew C.; Sack, Jon T.; Cohen, Bruce E.

2018-01-01

Functionalization of nanocrystals is essential for their practical application, but synthesis on nanocrystal surfaces is limited by incompatibilities with certain key reagents. The copper-catalyzed azide-alkyne cycloaddition (CuAAC) is among the most useful methods for ligating molecules to surfaces, but has been largely useless for semiconductor quantum dots (QDs) because Cu+ ions quickly and irreversibly quench QD fluorescence. To discover non-quenching synthetic conditions for Cu-catalyzed click reactions on QD surfaces, we developed a combinatorial fluorescence assay to screen >2000 reaction conditions to maximize cycloaddition efficiency while minimizing QD quenching. We identify conditions for complete coupling without significant quenching, which are compatible with common QD polymer surfaces and various azide/alkyne pairs. Based on insight from the combinatorial screen and mechanistic studies of Cu coordination and quenching, we find that superstoichiometric concentrations of Cu can promote full coupling if accompanied by ligands that selectively compete the Cu from the QD surface but allow it to remain catalytically active. Applied to the conjugation of a K+ channel-specific peptidyl toxin to CdSe/ZnS QDs, we synthesize unquenched QD conjugates and image their specific and voltage-dependent affinity for K+ channels in live cells. PMID:29608274

Synthesis and Structure of Fully Conjugated Block Copolymers Utilized in Organic Photovoltaics

NASA Astrophysics Data System (ADS)

Lee, Youngmin; Aplan, Melissa; Wang, Qing; Gomez, Enrique D.

2015-03-01

Fully conjugated block copolymers have the potential to overcome many of the limitations of mixtures and blends as photoactive layers in solar cells; furthermore, they may serve as model systems to study fundamental questions regarding optoelectric properties and charge transfer. However, the synthesis of fully conjugated block copolymers remains a challenging issue in the fieldchallenge. We have optimized the two-step synthesis of P3HT-b-PFTBT, which is composed comprised of Grignard metathesis for polymerization of P3HT followed by chain extension through a Suzuki-Miyaura polycondenstation. We find that the concentration of the Grignard reagent is critical for end-group control such that P3HT is terminated by H at one end and Br at the other. Furthermore, we can utilize an asymmetric feed ratio of monomers for the Suzuki-Miyaura reaction to minimize the amount of uncoupled homopolymers and to control the molecular weight of the second block. We investigated the chemical composition, structure and electrical characteristics of the polymers prepared by the different synthetic methods, and demonstrate that we can utilize these strategies for the synthesis of block copolymers beyond P3HT-b-PFTBT.

Targeting single-walled carbon nanotubes for the treatment of breast cancer using photothermal therapy

NASA Astrophysics Data System (ADS)

Neves, Luís F. F.; Krais, John J.; Van Rite, Brent D.; Ramesh, Rajagopal; Resasco, Daniel E.; Harrison, Roger G.

2013-09-01

This paper focuses on the targeting of single-walled carbon nanotubes (SWNTs) for the treatment of breast cancer with minimal side effects using photothermal therapy. The human protein annexin V (AV) binds specifically to anionic phospholipids expressed externally on the surface of tumour cells and endothelial cells that line the tumour vasculature. A 2 h incubation of the SWNT-AV conjugate with proliferating endothelial cells followed by washing and near-infrared (NIR) irradiation at a wavelength of 980 nm was enough to induce significant cell death; there was no significant cell death with irradiation or the conjugate alone. Administration of the same conjugate i.v. in BALB/c female mice with implanted 4T1 murine mammary at a dose of 0.8 mg SWNT kg-1 and followed one day later by NIR irradiation of the tumour at a wavelength of 980 nm led to complete disappearance of implanted 4T1 mouse mammary tumours for the majority of the animals by 11 days since the irradiation. The combination of the photothermal therapy with the immunoadjuvant cyclophosphamide resulted in increased survival. The in vivo results suggest the SWNT-AV/NIR treatment is a promising approach to treat breast cancer.

Guiding neuron development with planar surface gradients of substrate cues deposited using microfluidic devices.

PubMed

Millet, Larry J; Stewart, Matthew E; Nuzzo, Ralph G; Gillette, Martha U

2010-06-21

Wiring the nervous system relies on the interplay of intrinsic and extrinsic signaling molecules that control neurite extension, neuronal polarity, process maturation and experience-dependent refinement. Extrinsic signals establish and enrich neuron-neuron interactions during development. Understanding how such extrinsic cues direct neurons to establish neural connections in vitro will facilitate the development of organized neural networks for investigating the development and function of nervous system networks. Producing ordered networks of neurons with defined connectivity in vitro presents special technical challenges because the results must be compliant with the biological requirements of rewiring neural networks. Here we demonstrate the ability to form stable, instructive surface-bound gradients of laminin that guide postnatal hippocampal neuron development in vitro. Our work uses a three-channel, interconnected microfluidic device that permits the production of adlayers of planar substrates through the combination of laminar flow, diffusion and physisorption. Through simple flow modifications, a variety of patterns and gradients of laminin (LN) and fluorescein isothiocyanate-conjugated poly-l-lysine (FITC-PLL) were deposited to present neurons with an instructive substratum to guide neuronal development. We present three variations in substrate design that produce distinct growth regimens for postnatal neurons in dispersed cell cultures. In the first approach, diffusion-mediated gradients of LN were formed on cover slips to guide neurons toward increasing LN concentrations. In the second approach, a combined gradient of LN and FITC-PLL was produced using aspiration-driven laminar flow to restrict neuronal growth to a 15 microm wide growth zone at the center of the two superimposed gradients. The last approach demonstrates the capacity to combine binary lines of FITC-PLL in conjunction with surface gradients of LN and bovine serum albumin (BSA) to produce substrate adlayers that provide additional levels of control over growth. This work demonstrates the advantages of spatio-temporal fluid control for patterning surface-bound gradients using a simple microfluidics-based substrate deposition procedure. We anticipate that this microfluidics-based patterning approach will provide instructive patterns and surface-bound gradients to enable a new level of control in guiding neuron development and network formation.

A refined model of sedimentary rock cover in the southeastern part of the Congo basin from GOCE gravity and vertical gravity gradient observations

NASA Astrophysics Data System (ADS)

Martinec, Zdeněk; Fullea, Javier

2015-03-01

We aim to interpret the vertical gravity and vertical gravity gradient of the GOCE-GRACE combined gravity model over the southeastern part of the Congo basin to refine the published model of sedimentary rock cover. We use the GOCO03S gravity model and evaluate its spherical harmonic representation at or near the Earth's surface. In this case, the gradiometry signals are enhanced as compared to the original measured GOCE gradients at satellite height and better emphasize the spatial pattern of sedimentary geology. To avoid aliasing, the omission error of the modelled gravity induced by the sedimentary rocks is adjusted to that of the GOCO03S gravity model. The mass-density Green's functions derived for the a priori structure of the sediments show a slightly greater sensitivity to the GOCO03S vertical gravity gradient than to the vertical gravity. Hence, the refinement of the sedimentary model is carried out for the vertical gravity gradient over the basin, such that a few anomalous values of the GOCO03S-derived vertical gravity gradient are adjusted by refining the model. We apply the 5-parameter Helmert's transformation, defined by 2 translations, 1 rotation and 2 scale parameters that are searched for by the steepest descent method. The refined sedimentary model is only slightly changed with respect to the original map, but it significantly improves the fit of the vertical gravity and vertical gravity gradient over the basin. However, there are still spatial features in the gravity and gradiometric data that remain unfitted by the refined model. These may be due to lateral density variation that is not contained in the model, a density contrast at the Moho discontinuity, lithospheric density stratifications or mantle convection. In a second step, the refined sedimentary model is used to find the vertical density stratification of sedimentary rocks. Although the gravity data can be interpreted by a constant sedimentary density, such a model does not correspond to the gravitational compaction of sedimentary rocks. Therefore, the density model is extended by including a linear increase in density with depth. Subsequent L2 and L∞ norm minimization procedures are applied to find the density parameters by adjusting both the vertical gravity and the vertical gravity gradient. We found that including the vertical gravity gradient in the interpretation of the GOCO03S-derived data reduces the non-uniqueness of the inverse gradiometric problem for density determination. The density structure of the sedimentary formations that provide the optimum predictions of the GOCO03S-derived gravity and vertical gradient of gravity consists of a surface density contrast with respect to surrounding rocks of 0.24-0.28 g/cm3 and its decrease with depth of 0.05-0.25 g/cm3 per 10 km. Moreover, the case where the sedimentary rocks are gravitationally completely compacted in the deepest parts of the basin is supported by L∞ norm minimization. However, this minimization also allows a remaining density contrast at the deepest parts of the sedimentary basin of about 0.1 g/cm3.

Spiral Gradient Coil Design for Use in Cylindrical MRI Systems.

PubMed

Wang, Yaohui; Xin, Xuegang; Liu, Feng; Crozier, Stuart

2018-04-01

In magnetic resonance imaging, the stream function based method is commonly used in the design of gradient coils. However, this method can be prone to errors associated with the discretization of continuous current density and wire connections. In this paper, we propose a novel gradient coil design scheme that works directly in the wire space, avoiding the system errors that may appear in the stream function approaches. Specifically, the gradient coil pattern is described with dedicated spiral functions adjusted to allow the coil to produce the required field gradients in the imaging area, minimal stray field, and other engineering terms. The performance of a designed spiral gradient coil was compared with its stream-function counterpart. The numerical evaluation shows that when compared with the conventional solution, the inductance and resistance was reduced by 20.9 and 10.5%, respectively. The overall coil performance (evaluated by the figure of merit (FoM)) was improved up to 26.5% for the x -gradient coil design; for the z-gradient coil design, the inductance and resistance were reduced by 15.1 and 6.7% respectively, and the FoM was increased by 17.7%. In addition, by directly controlling the wire distributions, the spiral gradient coil design was much sparser than conventional coils.

Minimally Informative Prior Distributions for PSA

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

Dana L. Kelly; Robert W. Youngblood; Kurt G. Vedros

2010-06-01

A salient feature of Bayesian inference is its ability to incorporate information from a variety of sources into the inference model, via the prior distribution (hereafter simply “the prior”). However, over-reliance on old information can lead to priors that dominate new data. Some analysts seek to avoid this by trying to work with a minimally informative prior distribution. Another reason for choosing a minimally informative prior is to avoid the often-voiced criticism of subjectivity in the choice of prior. Minimally informative priors fall into two broad classes: 1) so-called noninformative priors, which attempt to be completely objective, in that themore » posterior distribution is determined as completely as possible by the observed data, the most well known example in this class being the Jeffreys prior, and 2) priors that are diffuse over the region where the likelihood function is nonnegligible, but that incorporate some information about the parameters being estimated, such as a mean value. In this paper, we compare four approaches in the second class, with respect to their practical implications for Bayesian inference in Probabilistic Safety Assessment (PSA). The most commonly used such prior, the so-called constrained noninformative prior, is a special case of the maximum entropy prior. This is formulated as a conjugate distribution for the most commonly encountered aleatory models in PSA, and is correspondingly mathematically convenient; however, it has a relatively light tail and this can cause the posterior mean to be overly influenced by the prior in updates with sparse data. A more informative prior that is capable, in principle, of dealing more effectively with sparse data is a mixture of conjugate priors. A particular diffuse nonconjugate prior, the logistic-normal, is shown to behave similarly for some purposes. Finally, we review the so-called robust prior. Rather than relying on the mathematical abstraction of entropy, as does the constrained noninformative prior, the robust prior places a heavy-tailed Cauchy prior on the canonical parameter of the aleatory model.« less

Montanide, Poly I:C and nanoparticle based vaccines promote differential suppressor and effector cell expansion: a study of induction of CD8 T cells to a minimal Plasmodium berghei epitope.

PubMed

Wilson, Kirsty L; Xiang, Sue D; Plebanski, Magdalena

2015-01-01

The development of practical and flexible vaccines to target liver stage malaria parasites would benefit from an ability to induce high levels of CD8 T cells to minimal peptide epitopes. Herein we compare different adjuvant and carrier systems in a murine model for induction of interferon gamma (IFN-γ) producing CD8 T cells to the minimal immuno-dominant peptide epitope from the circumsporozoite protein (CSP) of Plasmodium berghei, pb9 (SYIPSAEKI, referred to as KI). Two pro-inflammatory adjuvants, Montanide and Poly I:C, and a non-classical, non-inflammatory nanoparticle based carrier (polystyrene nanoparticles, PSNPs), were compared side-by-side for their ability to induce potentially protective CD8 T cell responses after two immunizations. KI in Montanide (Montanide + KI) or covalently conjugated to PSNPs (PSNPs-KI) induced such high responses, whereas adjuvanting with Poly I:C or PSNPs without conjugation was ineffective. This result was consistent with an observed induction of an immunosuppressed environment by Poly I:C in the draining lymph node (dLN) 48 h post injection, which was reflected by increased frequencies of myeloid derived suppressor cells (MDSCs) and a proportion of inflammation reactive regulatory T cells (Treg) expressing the tumor necrosis factor receptor 2 (TNFR2), as well as decreased dendritic cell (DC) maturation. The other inflammatory adjuvant, Montanide, also promoted proportional increases in the TNFR2(+) Treg subpopulation, but not MDSCs, in the dLN. By contrast, injection with non-inflammatory PSNPs did not cause these changes. Induction of high CD8 T cell responses, using minimal peptide epitopes, can be achieved by non-inflammatory carrier nanoparticles, which in contrast to some conventional inflammatory adjuvants, do not expand either MDSCs or inflammation reactive Tregs at the site of priming.

An improved conjugate gradient scheme to the solution of least squares SVM.

PubMed

Chu, Wei; Ong, Chong Jin; Keerthi, S Sathiya

2005-03-01

The least square support vector machines (LS-SVM) formulation corresponds to the solution of a linear system of equations. Several approaches to its numerical solutions have been proposed in the literature. In this letter, we propose an improved method to the numerical solution of LS-SVM and show that the problem can be solved using one reduced system of linear equations. Compared with the existing algorithm for LS-SVM, the approach used in this letter is about twice as efficient. Numerical results using the proposed method are provided for comparisons with other existing algorithms.

Inversion of Robin coefficient by a spectral stochastic finite element approach

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

Jin Bangti; Zou Jun

2008-03-01

This paper investigates a variational approach to the nonlinear stochastic inverse problem of probabilistically calibrating the Robin coefficient from boundary measurements for the steady-state heat conduction. The problem is formulated into an optimization problem, and mathematical properties relevant to its numerical computations are investigated. The spectral stochastic finite element method using polynomial chaos is utilized for the discretization of the optimization problem, and its convergence is analyzed. The nonlinear conjugate gradient method is derived for the optimization system. Numerical results for several two-dimensional problems are presented to illustrate the accuracy and efficiency of the stochastic finite element method.

Subauditory Speech Recognition based on EMG/EPG Signals

NASA Technical Reports Server (NTRS)

Jorgensen, Charles; Lee, Diana Dee; Agabon, Shane; Lau, Sonie (Technical Monitor)

2003-01-01

Sub-vocal electromyogram/electro palatogram (EMG/EPG) signal classification is demonstrated as a method for silent speech recognition. Recorded electrode signals from the larynx and sublingual areas below the jaw are noise filtered and transformed into features using complex dual quad tree wavelet transforms. Feature sets for six sub-vocally pronounced words are trained using a trust region scaled conjugate gradient neural network. Real time signals for previously unseen patterns are classified into categories suitable for primitive control of graphic objects. Feature construction, recognition accuracy and an approach for extension of the technique to a variety of real world application areas are presented.

Numerical Simulation of Convective Heat and Mass Transfer in a Two-Layer System

NASA Astrophysics Data System (ADS)

Myznikova, B. I.; Kazaryan, V. A.; Tarunin, E. L.; Wertgeim, I. I.

The results are presented of mathematical and computer modeling of natural convection in the “liquid-gas” two-layer system, filling a vertical cylinder surrounded by solid heat conductive tract. The model describes approximately the conjugate heat and mass transfer in the underground oil product storage, filled partially by a hydrocarbon liquid, with natural gas layer above the liquid surface. The geothermal gradient in a rock mass gives rise to the intensive convection in the liquid-gas system. The consideration is worked out for laminar flows, laminar-turbulent transitional regimes, and developed turbulent flows.

3D near-to-surface conductivity reconstruction by inversion of VETEM data using the distorted Born iterative method

USGS Publications Warehouse

Wang, G.L.; Chew, W.C.; Cui, T.J.; Aydiner, A.A.; Wright, D.L.; Smith, D.V.

2004-01-01

Three-dimensional (3D) subsurface imaging by using inversion of data obtained from the very early time electromagnetic system (VETEM) was discussed. The study was carried out by using the distorted Born iterative method to match the internal nonlinear property of the 3D inversion problem. The forward solver was based on the total-current formulation bi-conjugate gradient-fast Fourier transform (BCCG-FFT). It was found that the selection of regularization parameter follow a heuristic rule as used in the Levenberg-Marquardt algorithm so that the iteration is stable.

An exterior Poisson solver using fast direct methods and boundary integral equations with applications to nonlinear potential flow

NASA Technical Reports Server (NTRS)

Young, D. P.; Woo, A. C.; Bussoletti, J. E.; Johnson, F. T.

1986-01-01

A general method is developed combining fast direct methods and boundary integral equation methods to solve Poisson's equation on irregular exterior regions. The method requires O(N log N) operations where N is the number of grid points. Error estimates are given that hold for regions with corners and other boundary irregularities. Computational results are given in the context of computational aerodynamics for a two-dimensional lifting airfoil. Solutions of boundary integral equations for lifting and nonlifting aerodynamic configurations using preconditioned conjugate gradient are examined for varying degrees of thinness.

Complexity of parallel implementation of domain decomposition techniques for elliptic partial differential equations

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

Gropp, W.D.; Keyes, D.E.

1988-03-01

The authors discuss the parallel implementation of preconditioned conjugate gradient (PCG)-based domain decomposition techniques for self-adjoint elliptic partial differential equations in two dimensions on several architectures. The complexity of these methods is described on a variety of message-passing parallel computers as a function of the size of the problem, number of processors and relative communication speeds of the processors. They show that communication startups are very important, and that even the small amount of global communication in these methods can significantly reduce the performance of many message-passing architectures.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

Amplitude and phase controlled adaptive optics system

NASA Astrophysics Data System (ADS)

Pham, Ich; Ma, Sam

2006-06-01

An adaptive optics (AO) system is used to control the deformable mirror (DM) actuators for compensating the optical effects introduced by the turbulence in the Earth's atmosphere and distortions produced by the optical elements between the distant object and its local sensor. The typical AO system commands the DM actuators while minimizing the measured wave front (WF) phase error. This is known as the phase conjugator system, which does not work well in the strong scintillation condition because both amplitude and phase are corrupted along the propagation path. In order to compensate for the wave front amplitude, a dual DM field conjugator system may be used. The first and second DM compensate for the amplitude and the phase respectively. The amplitude controller requires the mapping from DM1 actuator command to DM2 intensity. This can be obtained from either a calibration routine or an intensity transport equation, which relates the phase to the intensity. Instead of a dual-DM, a single Spatial Light Modulator (SLM) may control the amplitude and phase independently. The technique uses the spatial carrier frequency and the resulting intensity is related to the carrier modulation, while the phase is the average carrier phase. The dynamical AO performance using the carrier modulation is limited by the actuator frequency response and not by the computational load of the controller algorithm. Simulation of the proposed field conjugator systems show significant improvement for the on-axis performance compared to the phase conjugator system.

Single-walled carbon nanohorns decorated with semiconductor quantum dots to evaluate intracellular transport

NASA Astrophysics Data System (ADS)

Zimmermann, Kristen A.; Inglefield, David L.; Zhang, Jianfei; Dorn, Harry C.; Long, Timothy E.; Rylander, Christopher G.; Rylander, M. Nichole

2014-01-01

Single-walled carbon nanohorns (SWNHs) have great potential to enhance thermal and chemotherapeutic drug efficiencies for cancer therapies. Despite their diverse capabilities, minimal research has been conducted so far to study nanoparticle intracellular transport, which is an important step in designing efficient therapies. SWNHs, like many other carbon nanomaterials, do not have inherent fluorescence properties making intracellular transport information difficult to obtain. The goals of this project were to (1) develop a simple reaction scheme to decorate the exohedral surface of SWNHs with fluorescent quantum dots (QDs) and improve conjugate stability, and (2) evaluate SWNH-QD conjugate cellular uptake kinetics and localization in various cancer cell lines of differing origins and morphologies. In this study, SWNHs were conjugated to CdSe/ZnS core/shell QDs using a unique approach to carbodiimide chemistry. Transmission electron microscopy and electron dispersive spectroscopy verified the conjugation of SWNHs and QDs. Cellular uptake kinetics and efficiency were characterized in three malignant cell lines: U-87 MG (glioblastoma), MDA-MB-231 (breast cancer), and AY-27 (bladder transitional cell carcinoma) using flow cytometry. Cellular distribution was verified by confocal microscopy, and cytotoxicity was also evaluated using an alamarBlue assay. Results indicate that cellular uptake kinetics and efficiency are highly dependent on cell type, highlighting the significance of studying nanoparticle transport at the cellular level. Nanoparticle intracellular transport investigations may provide information to optimize treatment parameters (e.g., SWNH concentration, treatment time, etc.) depending on tumor etiology.

ANOTHER LOOK AT THE FAST ITERATIVE SHRINKAGE/THRESHOLDING ALGORITHM (FISTA)*

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2017-01-01

This paper provides a new way of developing the “Fast Iterative Shrinkage/Thresholding Algorithm (FISTA)” [3] that is widely used for minimizing composite convex functions with a nonsmooth term such as the ℓ1 regularizer. In particular, this paper shows that FISTA corresponds to an optimized approach to accelerating the proximal gradient method with respect to a worst-case bound of the cost function. This paper then proposes a new algorithm that is derived by instead optimizing the step coefficients of the proximal gradient method with respect to a worst-case bound of the composite gradient mapping. The proof is based on the worst-case analysis called Performance Estimation Problem in [11]. PMID:29805242

Using time-dependent density functional theory in real time for calculating electronic transport

NASA Astrophysics Data System (ADS)

Schaffhauser, Philipp; Kümmel, Stephan

2016-01-01

We present a scheme for calculating electronic transport within the propagation approach to time-dependent density functional theory. Our scheme is based on solving the time-dependent Kohn-Sham equations on grids in real space and real time for a finite system. We use absorbing and antiabsorbing boundaries for simulating the coupling to a source and a drain. The boundaries are designed to minimize the effects of quantum-mechanical reflections and electrical polarization build-up, which are the major obstacles when calculating transport by applying an external bias to a finite system. We show that the scheme can readily be applied to real molecules by calculating the current through a conjugated molecule as a function of time. By comparing to literature results for the conjugated molecule and to analytic results for a one-dimensional model system we demonstrate the reliability of the concept.

Bistetrazine-cyanines as double-clicking fluorogenic two-point binder or crosslinker probes.

PubMed

Kormos, Attila; Koehler, Christine; Fodor, Eszter; Rutkai, Zsófia; Martin, Maddison; Mező, Gábor; Lemke, Edward; Kele, Péter

2018-04-20

Fluorogenic probes are capable of minimizing background fluorescence of unreacted and non-specifically adsorbed reagents. The preceding years have brought substantial developments in the design and synthesis of bioorthogonally applicable fluorogenic systems mainly based on the quenching effects of azide and tetrazine moieties. The modulation power exerted by these bioorthogonal motifs typically becomes less efficient on more conjugated systems, i.e. on probes with red-shifted emission wavelength. In order to reach efficient quenching, i.e. fluorogenicity even in the red range of the spectrum, We present the synthesis, fluorogenic and conjugation characterization of bistetrazine-cyanine probes with emission maxima between 600-620 nm. The probes can bind to genetically altered proteins harboring an 11-amino acid peptide tag with two appending cyclooctyne motifs. Moreover, we also demonstrate the use of these bistetrazines as fluorogenic, covalent cross-linkers between monocyclooctynylated proteins. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Liver-selective glucocorticoid antagonists: a novel treatment for type 2 diabetes.

PubMed

von Geldern, Thomas W; Tu, Noah; Kym, Philip R; Link, James T; Jae, Hwan-Soo; Lai, Chunqiu; Apelqvist, Theresa; Rhonnstad, Patrik; Hagberg, Lars; Koehler, Konrad; Grynfarb, Marlena; Goos-Nilsson, Annika; Sandberg, Johnny; Osterlund, Marie; Barkhem, Tomas; Höglund, Marie; Wang, Jiahong; Fung, Steven; Wilcox, Denise; Nguyen, Phong; Jakob, Clarissa; Hutchins, Charles; Färnegårdh, Mathias; Kauppi, Björn; Ohman, Lars; Jacobson, Peer B

2004-08-12

Hepatic blockade of glucocorticoid receptors (GR) suppresses glucose production and thus decreases circulating glucose levels, but systemic glucocorticoid antagonism can produce adrenal insufficiency and other undesirable side effects. These hepatic and systemic responses might be dissected, leading to liver-selective pharmacology, when a GR antagonist is linked to a bile acid in an appropriate manner. Bile acid conjugation can be accomplished with a minimal loss of binding affinity for GR. The resultant conjugates remain potent in cell-based functional assays. A novel in vivo assay has been developed to simultaneously evaluate both hepatic and systemic GR blockade; this assay has been used to optimize the nature and site of the linker functionality, as well as the choice of the GR antagonist and the bile acid. This optimization led to the identification of A-348441, which reduces glucose levels and improves lipid profiles in an animal model of diabetes. Copyright 2004 American Chemical Society

Enzymatic production of single-molecule FISH and RNA capture probes.

PubMed

Gaspar, Imre; Wippich, Frank; Ephrussi, Anne

2017-10-01

Arrays of singly labeled short oligonucleotides that hybridize to a specific target revolutionized RNA biology, enabling quantitative, single-molecule microscopy analysis and high-efficiency RNA/RNP capture. Here, we describe a simple and efficient method that allows flexible functionalization of inexpensive DNA oligonucleotides by different fluorescent dyes or biotin using terminal deoxynucleotidyl transferase and custom-made functional group conjugated dideoxy-UTP. We show that (i) all steps of the oligonucleotide labeling-including conjugation, enzymatic synthesis, and product purification-can be performed in a standard biology laboratory, (ii) the process yields >90%, often >95% labeled product with minimal carryover of impurities, and (iii) the oligonucleotides can be labeled with different dyes or biotin, allowing single-molecule FISH, RNA affinity purification, and Northern blot analysis to be performed. © 2017 Gaspar et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.