Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn
2007-01-01
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.
Approximate error conjugation gradient minimization methods
Kallman, Jeffrey S
2013-05-21
In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.
Du, Shouqiang; Chen, Miao
2018-01-01
We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.
Tsuruta, S; Misztal, I; Strandén, I
2001-05-01
Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is essential.
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.
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.
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.
Frequency-domain beamformers using conjugate gradient techniques for speech enhancement.
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.
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.
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.
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.
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
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
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.
Nested Conjugate Gradient Algorithm with Nested Preconditioning for Non-linear Image Restoration.
Skariah, Deepak G; Arigovindan, Muthuvel
2017-06-19
We develop a novel optimization algorithm, which we call Nested Non-Linear Conjugate Gradient algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient (CG) iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT based non-iterative preconditioner. We prove that the method converges to a stationary point for both convex and non-convex regularization functionals. We demonstrate experimentally that proposed method outperforms the well-known majorization-minimization method used for convex regularization, and a non-convex inertial-proximal method for non-convex regularization functional.
Dai-Kou type conjugate gradient methods with a line search only using gradient.
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.
Conjugate gradient heat bath for ill-conditioned actions.
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.
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.
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
Application of the conjugate-gradient method to ground-water models
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)
Conjugate gradient type methods for linear systems with complex symmetric coefficient matrices
NASA Technical Reports Server (NTRS)
Freund, Roland
1989-01-01
We consider conjugate gradient type methods for the solution of large sparse linear system Ax equals b with complex symmetric coefficient matrices A equals A(T). Such linear systems arise in important applications, such as the numerical solution of the complex Helmholtz equation. Furthermore, most complex non-Hermitian linear systems which occur in practice are actually complex symmetric. We investigate conjugate gradient type iterations which are based on a variant of the nonsymmetric Lanczos algorithm for complex symmetric matrices. We propose a new approach with iterates defined by a quasi-minimal residual property. The resulting algorithm presents several advantages over the standard biconjugate gradient method. We also include some remarks on the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
Momentum-weighted conjugate gradient descent algorithm for gradient coil optimization.
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.
Minimizing inner product data dependencies in conjugate gradient iteration
NASA Technical Reports Server (NTRS)
Vanrosendale, J.
1983-01-01
The amount of concurrency available in conjugate gradient iteration is limited by the summations required in the inner product computations. The inner product of two vectors of length N requires time c log(N), if N or more processors are available. This paper describes an algebraic restructuring of the conjugate gradient algorithm which minimizes data dependencies due to inner product calculations. After an initial start up, the new algorithm can perform a conjugate gradient iteration in time c*log(log(N)).
Solving large test-day models by iteration on data and preconditioned conjugate gradient.
Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A
1999-12-01
A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.
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.
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.
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.
Conjugate gradient method for phase retrieval based on the Wirtinger derivative.
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.
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.
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.
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.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1)β k ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations. PMID:26502409
NASA Technical Reports Server (NTRS)
Freund, Roland
1988-01-01
Conjugate gradient type methods are considered for the solution of large linear systems Ax = b with complex coefficient matrices of the type A = T + i(sigma)I where T is Hermitian and sigma, a real scalar. Three different conjugate gradient type approaches with iterates defined by a minimal residual property, a Galerkin type condition, and an Euclidian error minimization, respectively, are investigated. In particular, numerically stable implementations based on the ideas behind Paige and Saunder's SYMMLQ and MINRES for real symmetric matrices are proposed. Error bounds for all three methods are derived. It is shown how the special shift structure of A can be preserved by using polynomial preconditioning. Results on the optimal choice of the polynomial preconditioner are given. Also, some numerical experiments for matrices arising from finite difference approximations to the complex Helmholtz equation are reported.
Solving large mixed linear models using preconditioned conjugate gradient iteration.
Strandén, I; Lidauer, M
1999-12-01
Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.
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.
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).
Quantifying the Energy Efficiency of Object Recognition and Optical Flow
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
Modified conjugate gradient method for diagonalizing large matrices.
Jie, Quanlin; Liu, Dunhuan
2003-11-01
We present an iterative method to diagonalize large matrices. The basic idea is the same as the conjugate gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroducing errors to the directions of previous gradients. Each iteration step is to find lowest eigenvector of the matrix in a subspace spanned by the current trial vector and the corresponding gradient of the Rayleigh quotient, as well as some previous trial vectors. The gradient, together with the previous trial vectors, play a similar role as the conjugate gradient of the original CG algorithm. Our numeric tests indicate that this method converges significantly faster than the original CG method. And the computational cost of one iteration step is about the same as the original CG method. It is suitable for first principle calculations.
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
Radiofrequency pulse design using nonlinear gradient magnetic fields.
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 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.
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.
A fast pulse design for parallel excitation with gridding conjugate gradient.
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.
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.
NASA Astrophysics Data System (ADS)
Antoine, Xavier; Levitt, Antoine; Tang, Qinglin
2017-08-01
We propose a preconditioned nonlinear conjugate gradient method coupled with a spectral spatial discretization scheme for computing the ground states (GS) of rotating Bose-Einstein condensates (BEC), modeled by the Gross-Pitaevskii Equation (GPE). We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation. Based on this IMT equation, we analyze the forward Euler (FE), Crank-Nicolson (CN) and the classical backward Euler (BE) schemes for linear problems and recognize classical power iterations, allowing us to derive convergence rates. By considering the alternative point of view of minimization problems, we propose the preconditioned steepest descent (PSD) and conjugate gradient (PCG) methods for the GS computation of the GPE. We investigate the choice of the preconditioner, which plays a key role in the acceleration of the convergence process. The performance of the new algorithms is tested in 1D, 2D and 3D. We conclude that the PCG method outperforms all the previous methods, most particularly for 2D and 3D fast rotating BECs, while being simple to implement.
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).
NASA Technical Reports Server (NTRS)
Navon, I. M.
1984-01-01
A Lagrange multiplier method using techniques developed by Bertsekas (1982) was applied to solving the problem of enforcing simultaneous conservation of the nonlinear integral invariants of the shallow water equations on a limited area domain. This application of nonlinear constrained optimization is of the large dimensional type and the conjugate gradient method was found to be the only computationally viable method for the unconstrained minimization. Several conjugate-gradient codes were tested and compared for increasing accuracy requirements. Robustness and computational efficiency were the principal criteria.
RF Pulse Design using Nonlinear Gradient Magnetic Fields
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
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.
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
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.
A forward model and conjugate gradient inversion technique for low-frequency ultrasonic imaging.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Conjugate gradient minimisation approach to generating holographic traps for ultracold atoms.
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.
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.
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.
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.
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.
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.
Missing value imputation in DNA microarrays based on conjugate gradient method.
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.
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.
Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.
Fessler, J A; Booth, S D
1999-01-01
Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.
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.
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.
Joint design of large-tip-angle parallel RF pulses and blipped gradient trajectories.
Cao, Zhipeng; Donahue, Manus J; Ma, Jun; Grissom, William A
2016-03-01
To design multichannel large-tip-angle kT-points and spokes radiofrequency (RF) pulses and gradient waveforms for transmit field inhomogeneity compensation in high field magnetic resonance imaging. An algorithm to design RF subpulse weights and gradient blip areas is proposed to minimize a magnitude least-squares cost function that measures the difference between realized and desired state parameters in the spin domain, and penalizes integrated RF power. The minimization problem is solved iteratively with interleaved target phase updates, RF subpulse weights updates using the conjugate gradient method with optimal control-based derivatives, and gradient blip area updates using the conjugate gradient method. Two-channel parallel transmit simulations and experiments were conducted in phantoms and human subjects at 7 T to demonstrate the method and compare it to small-tip-angle-designed pulses and circularly polarized excitations. The proposed algorithm designed more homogeneous and accurate 180° inversion and refocusing pulses than other methods. It also designed large-tip-angle pulses on multiple frequency bands with independent and joint phase relaxation. Pulses designed by the method improved specificity and contrast-to-noise ratio in a finger-tapping spin echo blood oxygen level dependent functional magnetic resonance imaging study, compared with circularly polarized mode refocusing. A joint RF and gradient waveform design algorithm was proposed and validated to improve large-tip-angle inversion and refocusing at ultrahigh field. © 2015 Wiley Periodicals, Inc.
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.
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.
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
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
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
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.
Application of Conjugate Gradient methods to tidal simulation
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.
Ghosh, A
1988-08-01
Lanczos and conjugate gradient algorithms are important in computational linear algebra. In this paper, a parallel pipelined realization of these algorithms on a ring of optical linear algebra processors is described. The flow of data is designed to minimize the idle times of the optical multiprocessor and the redundancy of computations. The effects of optical round-off errors on the solutions obtained by the optical Lanczos and conjugate gradient algorithms are analyzed, and it is shown that optical preconditioning can improve the accuracy of these algorithms substantially. Algorithms for optical preconditioning and results of numerical experiments on solving linear systems of equations arising from partial differential equations are discussed. Since the Lanczos algorithm is used mostly with sparse matrices, a folded storage scheme to represent sparse matrices on spatial light modulators is also described.
The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.
Yuan, Gonglin; Sheng, Zhou; Liu, Wenjie
2016-01-01
In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).
ONRASIA Scientific Information Bulletin. Volume 8, Number 3, July- September 1993
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
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.
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.
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.
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.
A family of conjugate gradient methods for large-scale nonlinear equations.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
1995-10-15
tensile extension. At each level of externally imposed displacements, internal equilibrium was achieved by a conjugate gradient method of energy...indentation cracks viewed by TEM. This could be due to either weaker grain boundaries or due to grain level internal stresses of misfit. The fact... internally using the conjugate gradient method until the overall elastic strain energy function 4 was minimized for a unit level of border displacement which
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.
Comparing implementations of penalized weighted least-squares sinogram restoration.
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.
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.
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
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
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.
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.
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
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.
Exciton intrachain transport induced by interchain packing configurations in conjugated polymers.
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.
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.
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.
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.
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.
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.
Comparing implementations of penalized weighted least-squares sinogram restoration
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
Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.
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.
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
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.
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.
Vacuolar transport of the glutathione conjugate of trans-cinnamic acid.
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.
Pixel-based OPC optimization based on conjugate gradients.
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.
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.
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.
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.
Performance of Nonlinear Finite-Difference Poisson-Boltzmann Solvers
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.
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.
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
A modified three-term PRP conjugate gradient algorithm for optimization models.
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.
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.
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.
New hybrid conjugate gradient methods with the generalized Wolfe line search.
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.
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.
NASA Technical Reports Server (NTRS)
Burrows, R. R.
1972-01-01
A particular type of three-impulse transfer between two circular orbits is analyzed. The possibility of three plane changes is recognized, and the problem is to optimally distribute these plane changes to minimize the sum of the individual impulses. Numerical difficulties and their solution are discussed. Numerical results obtained from a conjugate gradient technique are presented for both the case where the individual plane changes are unconstrained and for the case where they are constrained. Possibly not unexpectedly, multiple minima are found. The techniques presented could be extended to the finite burn case, but primarily the contents are addressed to preliminary mission design and vehicle sizing.
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
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.
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.
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.
QMR: A Quasi-Minimal Residual method for non-Hermitian linear systems
NASA Technical Reports Server (NTRS)
Freund, Roland W.; Nachtigal, Noel M.
1990-01-01
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. A novel BCG like approach is presented called the quasi-minimal residual (QMR) method, which overcomes the problems of BCG. An implementation of QMR based on a look-ahead version of the nonsymmetric Lanczos algorithm is proposed. It is shown how BCG iterates can be recovered stably from the QMR process. Some further properties of the QMR approach are given and an error bound is presented. Finally, numerical experiments are reported.
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.
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).
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.
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.
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.
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.
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.
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.
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
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.
Algorithms for accelerated convergence of adaptive PCA.
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.
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.
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.
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.
Speed and convergence properties of gradient algorithms for optimization of IMRT.
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.
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.
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.
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.
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.
Local gravity field modeling using spherical radial basis functions and a genetic algorithm
NASA Astrophysics Data System (ADS)
Mahbuby, Hany; Safari, Abdolreza; Foroughi, Ismael
2017-05-01
Spherical Radial Basis Functions (SRBFs) can express the local gravity field model of the Earth if they are parameterized optimally on or below the Bjerhammar sphere. This parameterization is generally defined as the shape of the base functions, their number, center locations, bandwidths, and scale coefficients. The number/location and bandwidths of the base functions are the most important parameters for accurately representing the gravity field; once they are determined, the scale coefficients can then be computed accordingly. In this study, the point-mass kernel, as the simplest shape of SRBFs, is chosen to evaluate the synthesized free-air gravity anomalies over the rough area in Auvergne and GNSS/Leveling points (synthetic height anomalies) are used to validate the results. A two-step automatic approach is proposed to determine the optimum distribution of the base functions. First, the location of the base functions and their bandwidths are found using the genetic algorithm; second, the conjugate gradient least squares method is employed to estimate the scale coefficients. The proposed methodology shows promising results. On the one hand, when using the genetic algorithm, the base functions do not need to be set to a regular grid and they can move according to the roughness of topography. In this way, the models meet the desired accuracy with a low number of base functions. On the other hand, the conjugate gradient method removes the bias between derived quasigeoid heights from the model and from the GNSS/leveling points; this means there is no need for a corrector surface. The numerical test on the area of interest revealed an RMS of 0.48 mGal for the differences between predicted and observed gravity anomalies, and a corresponding 9 cm for the differences in GNSS/leveling points.
LC-NMR Technique in the Analysis of Phytosterols in Natural Extracts
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
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].
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.
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.
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.
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.
Separation of antibody drug conjugate species by RPLC: A generic method development approach.
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.
A modified conjugate gradient method based on the Tikhonov system for computerized tomography (CT).
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
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.
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.
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
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.
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
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 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.
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.
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.
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.
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.
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.
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.
Velocity Gradient Power Functional for Brownian Dynamics.
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.
NASA Astrophysics Data System (ADS)
Ramlau, R.; Saxenhuber, D.; Yudytskiy, M.
2014-07-01
The problem of atmospheric tomography arises in ground-based telescope imaging with adaptive optics (AO), where one aims to compensate in real-time for the rapidly changing optical distortions in the atmosphere. Many of these systems depend on a sufficient reconstruction of the turbulence profiles in order to obtain a good correction. Due to steadily growing telescope sizes, there is a strong increase in the computational load for atmospheric reconstruction with current methods, first and foremost the MVM. In this paper we present and compare three novel iterative reconstruction methods. The first iterative approach is the Finite Element- Wavelet Hybrid Algorithm (FEWHA), which combines wavelet-based techniques and conjugate gradient schemes to efficiently and accurately tackle the problem of atmospheric reconstruction. The method is extremely fast, highly flexible and yields superior quality. Another novel iterative reconstruction algorithm is the three step approach which decouples the problem in the reconstruction of the incoming wavefronts, the reconstruction of the turbulent layers (atmospheric tomography) and the computation of the best mirror correction (fitting step). For the atmospheric tomography problem within the three step approach, the Kaczmarz algorithm and the Gradient-based method have been developed. We present a detailed comparison of our reconstructors both in terms of quality and speed performance in the context of a Multi-Object Adaptive Optics (MOAO) system for the E-ELT setting on OCTOPUS, the ESO end-to-end simulation tool.
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.
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.
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.
Energy minimization in medical image analysis: Methodologies and applications.
Zhao, Feng; Xie, Xianghua
2016-02-01
Energy minimization is of particular interest in medical image analysis. In the past two decades, a variety of optimization schemes have been developed. In this paper, we present a comprehensive survey of the state-of-the-art optimization approaches. These algorithms are mainly classified into two categories: continuous method and discrete method. The former includes Newton-Raphson method, gradient descent method, conjugate gradient method, proximal gradient method, coordinate descent method, and genetic algorithm-based method, while the latter covers graph cuts method, belief propagation method, tree-reweighted message passing method, linear programming method, maximum margin learning method, simulated annealing method, and iterated conditional modes method. We also discuss the minimal surface method, primal-dual method, and the multi-objective optimization method. In addition, we review several comparative studies that evaluate the performance of different minimization techniques in terms of accuracy, efficiency, or complexity. These optimization techniques are widely used in many medical applications, for example, image segmentation, registration, reconstruction, motion tracking, and compressed sensing. We thus give an overview on those applications as well. Copyright © 2015 John Wiley & Sons, Ltd.
Comparison of SIRT and SQS for Regularized Weighted Least Squares Image Reconstruction
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
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.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Monteiller, Vadim; Chevrot, Sébastien; Komatitsch, Dimitri; Wang, Yi
2015-08-01
We present a method for high-resolution imaging of lithospheric structures based on full waveform inversion of teleseismic waveforms. We model the propagation of seismic waves using our recently developed direct solution method/spectral-element method hybrid technique, which allows us to simulate the propagation of short-period teleseismic waves through a regional 3-D model. We implement an iterative quasi-Newton method based upon the L-BFGS algorithm, where the gradient of the misfit function is computed using the adjoint-state method. Compared to gradient or conjugate-gradient methods, the L-BFGS algorithm has a much faster convergence rate. We illustrate the potential of this method on a synthetic test case that consists of a crustal model with a crustal discontinuity at 25 km depth and a sharp Moho jump. This model contains short- and long-wavelength heterogeneities along the lateral and vertical directions. The iterative inversion starts from a smooth 1-D model derived from the IASP91 reference Earth model. We invert both radial and vertical component waveforms, starting from long-period signals filtered at 10 s and gradually decreasing the cut-off period down to 1.25 s. This multiscale algorithm quickly converges towards a model that is very close to the true model, in contrast to inversions involving short-period waveforms only, which always get trapped into a local minimum of the cost function.
Application of COMSOL to Acoustic Imaging
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.
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).
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.
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.
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.
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.
Deconvolution of astronomical images using SOR with adaptive relaxation.
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.
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.
Saleh, M; Karfoul, A; Kachenoura, A; Senhadji, L; Albera, L
2016-08-01
Improving the execution time and the numerical complexity of the well-known kurtosis-based maximization method, the RobustICA, is investigated in this paper. A Newton-based scheme is proposed and compared to the conventional RobustICA method. A new implementation using the nonlinear Conjugate Gradient one is investigated also. Regarding the Newton approach, an exact computation of the Hessian of the considered cost function is provided. The proposed approaches and the considered implementations inherit the global plane search of the initial RobustICA method for which a better convergence speed for a given direction is still guaranteed. Numerical results on Magnetic Resonance Spectroscopy (MRS) source separation show the efficiency of the proposed approaches notably the quasi-Newton one using the BFGS method.
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.
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
NASA Astrophysics Data System (ADS)
Lukyanenko, D. V.; Shishlenin, M. A.; Volkov, V. T.
2018-01-01
We propose the numerical method for solving coefficient inverse problem for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time observation data based on the asymptotic analysis and the gradient method. Asymptotic analysis allows us to extract a priory information about interior layer (moving front), which appears in the direct problem, and boundary layers, which appear in the conjugate problem. We describe and implement the method of constructing a dynamically adapted mesh based on this a priory information. The dynamically adapted mesh significantly reduces the complexity of the numerical calculations and improve the numerical stability in comparison with the usual approaches. Numerical example shows the effectiveness of the proposed method.
Application of Support Vector Machine to Forex Monitoring
NASA Astrophysics Data System (ADS)
Kamruzzaman, Joarder; Sarker, Ruhul A.
Previous studies have demonstrated superior performance of artificial neural network (ANN) based forex forecasting models over traditional regression models. This paper applies support vector machines to build a forecasting model from the historical data using six simple technical indicators and presents a comparison with an ANN based model trained by scaled conjugate gradient (SCG) learning algorithm. The models are evaluated and compared on the basis of five commonly used performance metrics that measure closeness of prediction as well as correctness in directional change. Forecasting results of six different currencies against Australian dollar reveal superior performance of SVM model using simple linear kernel over ANN-SCG model in terms of all the evaluation metrics. The effect of SVM parameter selection on prediction performance is also investigated and analyzed.
An Advanced One-Dimensional Finite Element Model for Incompressible Thermally Expandable Flow
Hu, Rui
2017-03-27
Here, this paper provides an overview of a new one-dimensional finite element flow model for incompressible but thermally expandable flow. The flow model was developed for use in system analysis tools for whole-plant safety analysis of sodium fast reactors. Although the pressure-based formulation was implemented, the use of integral equations in the conservative form ensured the conservation laws of the fluid. A stabilization scheme based on streamline-upwind/Petrov-Galerkin and pressure-stabilizing/Petrov-Galerkin formulations is also introduced. The flow model and its implementation have been verified by many test problems, including density wave propagation, steep gradient problems, discharging between tanks, and the conjugate heatmore » transfer in a heat exchanger.« less
An Advanced One-Dimensional Finite Element Model for Incompressible Thermally Expandable Flow
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Rui
Here, this paper provides an overview of a new one-dimensional finite element flow model for incompressible but thermally expandable flow. The flow model was developed for use in system analysis tools for whole-plant safety analysis of sodium fast reactors. Although the pressure-based formulation was implemented, the use of integral equations in the conservative form ensured the conservation laws of the fluid. A stabilization scheme based on streamline-upwind/Petrov-Galerkin and pressure-stabilizing/Petrov-Galerkin formulations is also introduced. The flow model and its implementation have been verified by many test problems, including density wave propagation, steep gradient problems, discharging between tanks, and the conjugate heatmore » transfer in a heat exchanger.« less
Measurement of the gravity-field curvature by atom interferometry.
Rosi, G; Cacciapuoti, L; Sorrentino, F; Menchetti, M; Prevedelli, M; Tino, G M
2015-01-09
We present the first direct measurement of the gravity-field curvature based on three conjugated atom interferometers. Three atomic clouds launched in the vertical direction are simultaneously interrogated by the same atom interferometry sequence and used to probe the gravity field at three equally spaced positions. The vertical component of the gravity-field curvature generated by nearby source masses is measured from the difference between adjacent gravity gradient values. Curvature measurements are of interest in geodesy studies and for the validation of gravitational models of the surrounding environment. The possibility of using such a scheme for a new determination of the Newtonian constant of gravity is also discussed.
Yang, Ping; Ning, Yu; Lei, Xiang; Xu, Bing; Li, Xinyang; Dong, Lizhi; Yan, Hu; Liu, Wenjing; Jiang, Wenhan; Liu, Lei; Wang, Chao; Liang, Xingbo; Tang, Xiaojun
2010-03-29
We present a slab laser amplifier beam cleanup experimental system based on a 39-actuator rectangular piezoelectric deformable mirror. Rather than use a wave-front sensor to measure distortions in the wave-front and then apply a conjugation wave-front for compensating them, the system uses a Stochastic Parallel Gradient Descent algorithm to maximize the power contained within a far-field designated bucket. Experimental results demonstrate that at the output power of 335W, more than 30% energy concentrates in the 1x diffraction-limited area while the beam quality is enhanced greatly.
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.
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.
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.
An Introduction to the Conjugate Gradient Method that Even an Idiot Can Understand
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.
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 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.
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.
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.
Angelis, G I; Reader, A J; Kotasidis, F A; Lionheart, W R; Matthews, J C
2011-07-07
Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [(11)C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for many applications, especially given that in practice convergence is often not desired for algorithms seeking ML estimates.
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.
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.
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.
Ferritin conjugates as specific magnetic labels. Implications for cell separation.
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
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.
Modeling of Propagation of Interacting Cracks Under Hydraulic Pressure Gradient
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Hai; Mattson, Earl Douglas; Podgorney, Robert Karl
A robust and reliable numerical model for fracture initiation and propagation, which includes the interactions among propagating fractures and the coupling between deformation, fracturing and fluid flow in fracture apertures and in the permeable rock matrix, would be an important tool for developing a better understanding of fracturing behaviors of crystalline brittle rocks driven by thermal and (or) hydraulic pressure gradients. In this paper, we present a physics-based hydraulic fracturing simulator based on coupling a quasi-static discrete element model (DEM) for deformation and fracturing with conjugate lattice network flow model for fluid flow in both fractures and porous matrix. Fracturingmore » is represented explicitly by removing broken bonds from the network to represent microcracks. Initiation of new microfractures and growth and coalescence of the microcracks leads to the formation of macroscopic fractures when external and/or internal loads are applied. The coupled DEM-network flow model reproduces realistic growth pattern of hydraulic fractures. In particular, simulation results of perforated horizontal wellbore clearly demonstrate that elastic interactions among multiple propagating fractures, fluid viscosity, strong coupling between fluid pressure fluctuations within fractures and fracturing, and lower length scale heterogeneities, collectively lead to complicated fracturing patterns.« less
Numerical optimization methods for controlled systems with parameters
NASA Astrophysics Data System (ADS)
Tyatyushkin, A. I.
2017-10-01
First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.
NASA Technical Reports Server (NTRS)
Jiang, Bo-Nan; Sonnad, Vijay
1991-01-01
A p-version of the least squares finite element method, based on the velocity-pressure-vorticity formulation, is developed for solving steady state incompressible viscous flow problems. The resulting system of symmetric and positive definite linear equations can be solved satisfactorily with the conjugate gradient method. In conjunction with the use of rapid operator application which avoids the formation of either element of global matrices, it is possible to achieve a highly compact and efficient solution scheme for the incompressible Navier-Stokes equations. Numerical results are presented for two-dimensional flow over a backward facing step. The effectiveness of simple outflow boundary conditions is also demonstrated.
A Parallel Nonrigid Registration Algorithm Based on B-Spline for Medical Images.
Du, Xiaogang; Dang, Jianwu; Wang, Yangping; Wang, Song; Lei, Tao
2016-01-01
The nonrigid registration algorithm based on B-spline Free-Form Deformation (FFD) plays a key role and is widely applied in medical image processing due to the good flexibility and robustness. However, it requires a tremendous amount of computing time to obtain more accurate registration results especially for a large amount of medical image data. To address the issue, a parallel nonrigid registration algorithm based on B-spline is proposed in this paper. First, the Logarithm Squared Difference (LSD) is considered as the similarity metric in the B-spline registration algorithm to improve registration precision. After that, we create a parallel computing strategy and lookup tables (LUTs) to reduce the complexity of the B-spline registration algorithm. As a result, the computing time of three time-consuming steps including B-splines interpolation, LSD computation, and the analytic gradient computation of LSD, is efficiently reduced, for the B-spline registration algorithm employs the Nonlinear Conjugate Gradient (NCG) optimization method. Experimental results of registration quality and execution efficiency on the large amount of medical images show that our algorithm achieves a better registration accuracy in terms of the differences between the best deformation fields and ground truth and a speedup of 17 times over the single-threaded CPU implementation due to the powerful parallel computing ability of Graphics Processing Unit (GPU).
NASA Astrophysics Data System (ADS)
Mönkölä, Sanna
2013-06-01
This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement. Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problems directly. The time-dependent equations can be simulated with respect to time until a time-harmonic solution is reached, but the approach suffers from poor convergence. To overcome this challenge, we follow the approach first suggested and developed for the acoustic wave equations by Bristeau, Glowinski, and Périaux. Thus, we accelerate the convergence rate by employing a controllability method. The problem is formulated as a least-squares optimization problem, which is solved with the conjugate gradient (CG) algorithm. Computation of the gradient of the functional is done directly for the discretized problem. A graph-based multigrid method is used for preconditioning the CG algorithm.
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.
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.
Trajectory optimization for an asymmetric launch vehicle. M.S. Thesis - MIT
NASA Technical Reports Server (NTRS)
Sullivan, Jeanne Marie
1990-01-01
A numerical optimization technique is used to fully automate the trajectory design process for an symmetric configuration of the proposed Advanced Launch System (ALS). The objective of the ALS trajectory design process is the maximization of the vehicle mass when it reaches the desired orbit. The trajectories used were based on a simple shape that could be described by a small set of parameters. The use of a simple trajectory model can significantly reduce the computation time required for trajectory optimization. A predictive simulation was developed to determine the on-orbit mass given an initial vehicle state, wind information, and a set of trajectory parameters. This simulation utilizes an idealized control system to speed computation by increasing the integration time step. The conjugate gradient method is used for the numerical optimization of on-orbit mass. The method requires only the evaluation of the on-orbit mass function using the predictive simulation, and the gradient of the on-orbit mass function with respect to the trajectory parameters. The gradient is approximated with finite differencing. Prelaunch trajectory designs were carried out using the optimization procedure. The predictive simulation is used in flight to redesign the trajectory to account for trajectory deviations produced by off-nominal conditions, e.g., stronger than expected head winds.
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.
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.
Algorithms for the optimization of RBE-weighted dose in particle therapy.
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.
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.
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.
Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M.; El Fakhri, Georges
2013-01-01
Purpose: Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Methods: Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. Results: At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%–29% and 32%–70% for 50 × 106 and 10 × 106 detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40–50 iterations), while more than 500 iterations were needed for CG. Conclusions: The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method. PMID:24089922
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.
Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges
2013-10-01
Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.
Wideband dichroic-filter design for LED-phosphor beam-combining
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.
On adaptive weighted polynomial preconditioning for Hermitian positive definite matrices
NASA Technical Reports Server (NTRS)
Fischer, Bernd; Freund, Roland W.
1992-01-01
The conjugate gradient algorithm for solving Hermitian positive definite linear systems is usually combined with preconditioning in order to speed up convergence. In recent years, there has been a revival of polynomial preconditioning, motivated by the attractive features of the method on modern architectures. Standard techniques for choosing the preconditioning polynomial are based only on bounds for the extreme eigenvalues. Here a different approach is proposed, which aims at adapting the preconditioner to the eigenvalue distribution of the coefficient matrix. The technique is based on the observation that good estimates for the eigenvalue distribution can be derived after only a few steps of the Lanczos process. This information is then used to construct a weight function for a suitable Chebyshev approximation problem. The solution of this problem yields the polynomial preconditioner. In particular, we investigate the use of Bernstein-Szego weights.
Broiler weight estimation based on machine vision and artificial neural network.
Amraei, S; Abdanan Mehdizadeh, S; Salari, S
2017-04-01
1. Machine vision and artificial neural network (ANN) procedures were used to estimate live body weight of broiler chickens in 30 1-d-old broiler chickens reared for 42 d. 2. Imaging was performed two times daily. To localise chickens within the pen, an ellipse fitting algorithm was used and the chickens' head and tail removed using the Chan-Vese method. 3. The correlations between the body weight and 6 physical extracted features indicated that there were strong correlations between body weight and the 5 features including area, perimeter, convex area, major and minor axis length. 5. According to statistical analysis there was no significant difference between morning and afternoon data over 42 d. 6. In an attempt to improve the accuracy of live weight approximation different ANN techniques, including Bayesian regulation, Levenberg-Marquardt, Scaled conjugate gradient and gradient descent were used. Bayesian regulation with R 2 value of 0.98 was the best network for prediction of broiler weight. 7. The accuracy of the machine vision technique was examined and most errors were less than 50 g.
NASA Astrophysics Data System (ADS)
Bai, Bing
2012-03-01
There has been a lot of work on total variation (TV) regularized tomographic image reconstruction recently. Many of them use gradient-based optimization algorithms with a differentiable approximation of the TV functional. In this paper we apply TV regularization in Positron Emission Tomography (PET) image reconstruction. We reconstruct the PET image in a Bayesian framework, using Poisson noise model and TV prior functional. The original optimization problem is transformed to an equivalent problem with inequality constraints by adding auxiliary variables. Then we use an interior point method with logarithmic barrier functions to solve the constrained optimization problem. In this method, a series of points approaching the solution from inside the feasible region are found by solving a sequence of subproblems characterized by an increasing positive parameter. We use preconditioned conjugate gradient (PCG) algorithm to solve the subproblems directly. The nonnegativity constraint is enforced by bend line search. The exact expression of the TV functional is used in our calculations. Simulation results show that the algorithm converges fast and the convergence is insensitive to the values of the regularization and reconstruction parameters.
Ionospheric-thermospheric UV tomography: 1. Image space reconstruction algorithms
NASA Astrophysics Data System (ADS)
Dymond, K. F.; Budzien, S. A.; Hei, M. A.
2017-03-01
We present and discuss two algorithms of the class known as Image Space Reconstruction Algorithms (ISRAs) that we are applying to the solution of large-scale ionospheric tomography problems. ISRAs have several desirable features that make them useful for ionospheric tomography. In addition to producing nonnegative solutions, ISRAs are amenable to sparse-matrix formulations and are fast, stable, and robust. We present the results of our studies of two types of ISRA: the Least Squares Positive Definite and the Richardson-Lucy algorithms. We compare their performance to the Multiplicative Algebraic Reconstruction and Conjugate Gradient Least Squares algorithms. We then discuss the use of regularization in these algorithms and present our new approach based on regularization to a partial differential equation.
Quantitative characterization of turbidity by radiative transfer based reflectance imaging
Tian, Peng; Chen, Cheng; Jin, Jiahong; Hong, Heng; Lu, Jun Q.; Hu, Xin-Hua
2018-01-01
A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of μa, the scattering coefficient of μs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging. PMID:29760971
Saad, E W; Prokhorov, D V; Wunsch, D C
1998-01-01
Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenience.
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
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
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
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.
Finite-temperature stress calculations in atomic models using moments of position.
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.
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.
Wang, Wen-Yong; Ma, Na-Na; Sun, Shi-Ling; Qiu, Yong-Qing
2014-03-14
The studies of geometrical structures, thermal stabilities, redox properties, nonlinear responses and optoelectronic properties have been carried out on a series of novel ferrocenyl (Fc) chromophores with the view of assessing their switchable and tailorable second order nonlinear optics (NLO). The use of a constant Fc donor and a 4,4'-bipyridinium acceptor and varied conjugated bridges makes it possible to systematically determine the contribution of organic connectors to chromophore nonlinear optical activities. The structures reveal that both the reduction reactions and organic connectors have a significant influence on 4,4'-bipyridinium. The potential energy surface maps along with plots of reduced density gradient mirror the thermal stabilities of the Fc-based chromophores. The first and second reductions take place preferentially at the 4,4'-bipyridinium moieties. Significantly, the reduction processes result in the molecular switches with large NLO contrast varying from zero or very small to a large value. Moreover, time-dependent density functional theory results indicate that the absorption peaks are mainly attributed to Fc to 4,4'-bipyridinium charge transfer and the mixture of intramolecular charge transfer within the two respective 4,4'-bipyridinium moieties coupled with interlayer charge transfer between the two 4,4'-bipyridinium moieties. This provides us with comprehensive information on the effect of organic connectors on the NLO properties.
Duan, Jizhong; Liu, Yu; Jing, Peiguang
2018-02-01
Self-consistent parallel imaging (SPIRiT) is an auto-calibrating model for the reconstruction of parallel magnetic resonance imaging, which can be formulated as a regularized SPIRiT problem. The Projection Over Convex Sets (POCS) method was used to solve the formulated regularized SPIRiT problem. However, the quality of the reconstructed image still needs to be improved. Though methods such as NonLinear Conjugate Gradients (NLCG) can achieve higher spatial resolution, these methods always demand very complex computation and converge slowly. In this paper, we propose a new algorithm to solve the formulated Cartesian SPIRiT problem with the JTV and JL1 regularization terms. The proposed algorithm uses the operator splitting (OS) technique to decompose the problem into a gradient problem and a denoising problem with two regularization terms, which is solved by our proposed split Bregman based denoising algorithm, and adopts the Barzilai and Borwein method to update step size. Simulation experiments on two in vivo data sets demonstrate that the proposed algorithm is 1.3 times faster than ADMM for datasets with 8 channels. Especially, our proposal is 2 times faster than ADMM for the dataset with 32 channels. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Qiao, Yao-Bin; Qi, Hong; Zhao, Fang-Zhou; Ruan, Li-Ming
2016-12-01
Reconstructing the distribution of optical parameters in the participating medium based on the frequency-domain radiative transfer equation (FD-RTE) to probe the internal structure of the medium is investigated in the present work. The forward model of FD-RTE is solved via the finite volume method (FVM). The regularization term formatted by the generalized Gaussian Markov random field model is used in the objective function to overcome the ill-posed nature of the inverse problem. The multi-start conjugate gradient (MCG) method is employed to search the minimum of the objective function and increase the efficiency of convergence. A modified adjoint differentiation technique using the collimated radiative intensity is developed to calculate the gradient of the objective function with respect to the optical parameters. All simulation results show that the proposed reconstruction algorithm based on FD-RTE can obtain the accurate distributions of absorption and scattering coefficients. The reconstructed images of the scattering coefficient have less errors than those of the absorption coefficient, which indicates the former are more suitable to probing the inner structure. Project supported by the National Natural Science Foundation of China (Grant No. 51476043), the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51121004).
A Parallel Nonrigid Registration Algorithm Based on B-Spline for Medical Images
Wang, Yangping; Wang, Song
2016-01-01
The nonrigid registration algorithm based on B-spline Free-Form Deformation (FFD) plays a key role and is widely applied in medical image processing due to the good flexibility and robustness. However, it requires a tremendous amount of computing time to obtain more accurate registration results especially for a large amount of medical image data. To address the issue, a parallel nonrigid registration algorithm based on B-spline is proposed in this paper. First, the Logarithm Squared Difference (LSD) is considered as the similarity metric in the B-spline registration algorithm to improve registration precision. After that, we create a parallel computing strategy and lookup tables (LUTs) to reduce the complexity of the B-spline registration algorithm. As a result, the computing time of three time-consuming steps including B-splines interpolation, LSD computation, and the analytic gradient computation of LSD, is efficiently reduced, for the B-spline registration algorithm employs the Nonlinear Conjugate Gradient (NCG) optimization method. Experimental results of registration quality and execution efficiency on the large amount of medical images show that our algorithm achieves a better registration accuracy in terms of the differences between the best deformation fields and ground truth and a speedup of 17 times over the single-threaded CPU implementation due to the powerful parallel computing ability of Graphics Processing Unit (GPU). PMID:28053653
Swart, Marcel; Bickelhaupt, F Matthias
2006-03-01
We have carried out an extensive exploration of the gas-phase basicity of archetypal anionic bases across the periodic system using the generalized gradient approximation of density functional theory (DFT) at BP86/QZ4P//BP86/TZ2P. First, we validate DFT as a reliable tool for computing proton affinities and related thermochemical quantities: BP86/QZ4P//BP86/TZ2P is shown to yield a mean absolute deviation of 1.6 kcal/mol for the proton affinity at 0 K with respect to high-level ab initio benchmark data. The main purpose of this work is to provide the proton affinities (and corresponding entropies) at 298 K of the anionic conjugate bases of all main-group-element hydrides of groups 14-17 and periods 2-6. We have also studied the effect of stepwise methylation of the protophilic center of the second- and third-period bases.
L-Valine appended PLGA nanoparticles for oral insulin delivery.
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.
Governing equations for electro-conjugate fluid flow
NASA Astrophysics Data System (ADS)
Hosoda, K.; Takemura, K.; Fukagata, K.; Yokota, S.; Edamura, K.
2013-12-01
An electro-conjugation fluid (ECF) is a kind of dielectric liquid, which generates a powerful flow when high DC voltage is applied with tiny electrodes. This study deals with the derivation of the governing equations for electro-conjugate fluid flow based on the Korteweg-Helmholtz (KH) equation which represents the force in dielectric liquid subjected to high DC voltage. The governing equations consist of the Gauss's law, charge conservation with charge recombination, the KH equation, the continuity equation and the incompressible Navier-Stokes equations. The KH equation consists of coulomb force, dielectric constant gradient force and electrostriction force. The governing equation gives the distribution of electric field, charge density and flow velocity. In this study, direct numerical simulation (DNS) is used in order to get these distribution at arbitrary time. Successive over-relaxation (SOR) method is used in analyzing Gauss's law and constrained interpolation pseudo-particle (CIP) method is used in analyzing charge conservation with charge recombination. The third order Runge-Kutta method and conservative second-order-accurate finite difference method is used in analyzing the Navier-Stokes equations with the KH equation. This study also deals with the measurement of ECF ow generated with a symmetrical pole electrodes pair which are made of 0.3 mm diameter piano wire. Working fluid is FF-1EHA2 which is an ECF family. The flow is observed from the both electrodes, i.e., the flow collides in between the electrodes. The governing equation successfully calculates mean flow velocity in between the collector pole electrode and the colliding region by the numerical simulation.
SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space
Lustig, Michael; Pauly, John M.
2010-01-01
A new approach to autocalibrating, coil-by-coil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k-space sampling patterns. The formulation can flexibly incorporate additional image priors such as off-resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k-space domain are presented. These are based on a projection over convex sets (POCS) and a conjugate gradient (CG) algorithms. Phantom and in-vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off-resonance correction and nonlinear ℓ1-wavelet regularization are also demonstrated. PMID:20665790
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…
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.
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.
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.
Assessment of Linear Finite-Difference Poisson-Boltzmann Solvers
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
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.
2-Deoxystreptamine Conjugates by Truncation–Derivatization of Neomycin
Aslam, M. Waqar; Tabares, Leandro C.; Andreoni, Alessio; Canters, Gerard W.; Rutjes, Floris P.J.T.; van Delft, Floris L.
2010-01-01
A small library of truncated neomycin-conjugates is prepared by consecutive removal of 2,6-diaminoglucose rings, oxidation-reductive amination of ribose, oxidation-conjugation of aminopyridine/aminoquinoline and finally dimerization. The dimeric conjugates were evaluated for antibacterial activity with a unique hemocyanin-based biosensor. Based on the outcome of these results, a second-generation set of monomeric conjugates was prepared and found to display significant antibacterial activity, in particular with respect to kanamycin-resistant E. coli. PMID:27713274
The Conjugate Acid-Base Chart.
ERIC Educational Resources Information Center
Treptow, Richard S.
1986-01-01
Discusses the difficulties that beginning chemistry students have in understanding acid-base chemistry. Describes the use of conjugate acid-base charts in helping students visualize the conjugate relationship. Addresses chart construction, metal ions, buffers and pH titrations, and the organic functional groups and nonaqueous solvents. (TW)
Calixarene-Mediated Liquid-Membrane Transport of Choline Conjugates.
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.
Forward model with space-variant of source size for reconstruction on X-ray radiographic image
NASA Astrophysics Data System (ADS)
Liu, Jin; Liu, Jun; Jing, Yue-feng; Xiao, Bo; Wei, Cai-hua; Guan, Yong-hong; Zhang, Xuan
2018-03-01
The Forward Imaging Technique is a method to solve the inverse problem of density reconstruction in radiographic imaging. In this paper, we introduce the forward projection equation (IFP model) for the radiographic system with areal source blur and detector blur. Our forward projection equation, based on X-ray tracing, is combined with the Constrained Conjugate Gradient method to form a new method for density reconstruction. We demonstrate the effectiveness of the new technique by reconstructing density distributions from simulated and experimental images. We show that for radiographic systems with source sizes larger than the pixel size, the effect of blur on the density reconstruction is reduced through our method and can be controlled within one or two pixels. The method is also suitable for reconstruction of non-homogeneousobjects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zou, Shiyang; Song, Peng; Pei, Wenbing
2013-09-15
Based on the conjugate gradient method, a simple algorithm is presented for deconvolving the temporal response of photoelectric x-ray detectors (XRDs) to reconstruct the resolved time-dependent x-ray fluxes. With this algorithm, we have studied the impact of temporal response of XRD on the radiation diagnosis of hohlraum heated by a short intense laser pulse. It is found that the limiting temporal response of XRD not only postpones the rising edge and peak position of x-ray pulses but also smoothes the possible fluctuations of radiation fluxes. Without a proper consideration of the temporal response of XRD, the measured radiation flux canmore » be largely misinterpreted for radiation pulses of a hohlraum heated by short or shaped laser pulses.« less
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.
Development of iterative techniques for the solution of unsteady compressible viscous flows
NASA Technical Reports Server (NTRS)
Sankar, Lakshmi N.; Hixon, Duane
1992-01-01
The development of efficient iterative solution methods for the numerical solution of two- and three-dimensional compressible Navier-Stokes equations is discussed. Iterative time marching methods have several advantages over classical multi-step explicit time marching schemes, and non-iterative implicit time marching schemes. Iterative schemes have better stability characteristics than non-iterative explicit and implicit schemes. In this work, another approach based on the classical conjugate gradient method, known as the Generalized Minimum Residual (GMRES) algorithm is investigated. The GMRES algorithm has been used in the past by a number of researchers for solving steady viscous and inviscid flow problems. Here, we investigate the suitability of this algorithm for solving the system of non-linear equations that arise in unsteady Navier-Stokes solvers at each time step.
Programmable Regulation of DNA Conjugation to Gold Nanoparticles via Strand Displacement.
Zhang, Cheng; Wu, Ranfeng; Li, Yifan; Zhang, Qiang; Yang, Jing
2017-10-31
Methods for conjugating DNA to gold nanoparticles (AuNPs) have recently attracted considerable attention. The ability to control such conjugation in a programmable way is of great interest. Here, we have developed a logic-based method for manipulating the conjugation of thiolated DNA species to AuNPs via cascading DNA strand displacement. Using this method, several logic-based operation systems are established and up to three kinds of DNA signals are introduced at the same time. In addition, a more sensitive catalytic logic-based operation is also achieved based on an entropy-driven process. In the experiment, all of the DNA/AuNPs conjugation results are verified by agrose gel. This strategy promises great potential for automatically conjugating DNA stands onto label-free gold nanoparticles and can be extended to constructing DNA/nanoparticle devices for applications in diagnostics, biosensing, and molecular robotics.
Self-assembling peptide-based building blocks in medical applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Acar, Handan; Srivastava, Samanvaya; Chung, Eun Ji
Peptides and peptide-conjugates, comprising natural and synthetic building blocks, are an increasingly popular class of biomaterials. Self-assembled nanostructures based on peptides and peptide-conjugates offer advantages such as precise selectivity and multifunctionality that can address challenges and limitations in the clinic. In this review article, we discuss recent developments in the design and self-assembly of various nanomaterials based on peptides and peptide-conjugates for medical applications, and categorize them into two themes based on the driving forces of molecular self-assembly. First, we present the self-assembled nanostructures driven by the supramolecular interactions between the peptides, with or without the presence of conjugates. Themore » studies where nanoassembly is driven by the interactions between the conjugates of peptide-conjugates are then presented. Particular emphasis is given to in vivo studies focusing on therapeutics, diagnostics, immune modulation and regenerative medicine. Finally, challenges and future perspectives are presented.« less
Ye, Long; Zhang, Shaoqing; Huo, Lijun; Zhang, Maojie; Hou, Jianhui
2014-05-20
As researchers continue to develop new organic materials for solar cells, benzo[1,2-b:4,5-b']dithiophene (BDT)-based polymers have come to the fore. To improve the photovoltaic properties of BDT-based polymers, researchers have developed and applied various strategies leading to the successful molecular design of highly efficient photovoltaic polymers. Novel polymer materials composed of two-dimensional conjugated BDT (2D-conjugated BDT) have boosted the power conversion efficiency of polymer solar cells (PSCs) to levels that exceed 9%. In this Account, we summarize recent progress related to the design and synthesis of 2D-conjugated BDT-based polymers and discuss their applications in highly efficient photovoltaic devices. We introduce the basic considerations for the construction of 2D-conjugated BDT-based polymers and systematic molecular design guidelines. For example, simply modifying an alkoxyl-substituted BDT to form an alkylthienyl-substituted BDT can improve the polymer hole mobilities substantially with little effect on their molecular energy level. Secondly, the addition of a variety of chemical moieties to the polymer can produce a 2D-conjugated BDT unit with more functions. For example, the introduction of a conjugated side chain with electron deficient groups (such as para-alkyl-phenyl, meta-alkoxyl-phenyl, and 2-alkyl-3-fluoro-thienyl) allowed us to modulate the molecular energy levels of 2D-conjugated BDT-based polymers. Through the rational design of BDT analogues such as dithienobenzodithiophene (DTBDT) or the insertion of larger π bridges, we can tune the backbone conformations of these polymers and modulate their photovoltaic properties. We also discuss the influence of 2D-conjugated BDT on polymer morphology and the blends of these polymers with phenyl-C61 (or C71)-butyric acid methyl ester (PCBM). Finally, we summarize the various applications of the 2D-conjugated BDT-based polymers in highly efficient PSC devices. Overall, this Account correlates the molecular structures of the 2D-conjugated BDT-based polymers with their photovoltaic properties. As a result, this Account can guide the molecular design of organic photovoltaic materials and the development of organic materials for other types of optoelectronic devices.
Usonis, Vytautas; Bakasenas, Vytautas; Lockhart, Stephen; Baker, Sherryl; Gruber, William; Laudat, France
2008-08-18
CRM(197) is a carrier protein in certain conjugate vaccines. When multiple conjugate vaccines with the same carrier protein are administered simultaneously, reduced response to vaccines and/or antigens related to the carrier protein may occur. This study examined responses of infants who, in addition to diphtheria toxoid/tetanus toxoid/acellular pertussis vaccine (DTaP) received either diphtheria CRM(197)-based Haemophilus influenzae type b conjugate vaccine (HbOC) or HbOC and a diphtheria CRM(197)-based combination 9-valent pneumococcal conjugate vaccine/meningococcal group C conjugate vaccine. Administration of conjugate vaccines with CRM(197) carrier protein load >50 microg did not reduce response to CRM(197) conjugate vaccines or immunogenicity to immunologically cross-reactive diphtheria toxoid.
Toward an Integrated Framwork for Data-Efficient Parametric Adaptive Detection
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)
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
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.
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
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
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.
Direct and accelerated parameter mapping using the unscented Kalman filter.
Zhao, Li; Feng, Xue; Meyer, Craig H
2016-05-01
To accelerate parameter mapping using a new paradigm that combines image reconstruction and model regression as a parameter state-tracking problem. In T2 mapping, the T2 map is first encoded in parameter space by multi-TE measurements and then encoded by Fourier transformation with readout/phase encoding gradients. Using a state transition function and a measurement function, the unscented Kalman filter can describe T2 mapping as a dynamic system and directly estimate the T2 map from the k-space data. The proposed method was validated with a numerical brain phantom and volunteer experiments with a multiple-contrast spin echo sequence. Its performance was compared with a conjugate-gradient nonlinear inversion method at undersampling factors of 2 to 8. An accelerated pulse sequence was developed based on this method to achieve prospective undersampling. Compared with the nonlinear inversion reconstruction, the proposed method had higher precision, improved structural similarity and reduced normalized root mean squared error, with acceleration factors up to 8 in numerical phantom and volunteer studies. This work describes a new perspective on parameter mapping by state tracking. The unscented Kalman filter provides a highly accelerated and efficient paradigm for T2 mapping. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Inochkin, F. M.; Kruglov, S. K.; Bronshtein, I. G.; Kompan, T. A.; Kondratjev, S. V.; Korenev, A. S.; Pukhov, N. F.
2017-06-01
A new method for precise subpixel edge estimation is presented. The principle of the method is the iterative image approximation in 2D with subpixel accuracy until the appropriate simulated is found, matching the simulated and acquired images. A numerical image model is presented consisting of three parts: an edge model, object and background brightness distribution model, lens aberrations model including diffraction. The optimal values of model parameters are determined by means of conjugate-gradient numerical optimization of a merit function corresponding to the L2 distance between acquired and simulated images. Computationally-effective procedure for the merit function calculation along with sufficient gradient approximation is described. Subpixel-accuracy image simulation is performed in a Fourier domain with theoretically unlimited precision of edge points location. The method is capable of compensating lens aberrations and obtaining the edge information with increased resolution. Experimental method verification with digital micromirror device applied to physically simulate an object with known edge geometry is shown. Experimental results for various high-temperature materials within the temperature range of 1000°C..2400°C are presented.
Multifunctional Diketopyrrolopyrrole-Based Conjugated Polymers with Perylene Bisimide Side Chains.
Li, Cheng; Yu, Changshi; Lai, Wenbin; Liang, Shijie; Jiang, Xudong; Feng, Guitao; Zhang, Jianqi; Xu, Yunhua; Li, Weiwei
2017-11-24
Two conjugated polymers based on diketopyrrolopyrrole (DPP) in the main chain with different content of perylene bisimide (PBI) side chains are developed. The influence of PBI side chain on the photovoltaic performance of these DPP-based conjugated polymers is systematically investigated. This study suggests that the PBI side chains can not only alter the absorption spectrum and energy level but also enhance the crystallinity of conjugated polymers. As a result, such polymers can act as electron donor, electron acceptor, and single-component active layer in organic solar cells. These findings provide a new guideline for the future molecular design of multifunctional conjugated polymers. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
NASA Astrophysics Data System (ADS)
Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José; Liu, Qinya; Zhou, Bing
2017-05-01
We carry out full waveform inversion (FWI) in time domain based on an alternative frequency-band selection strategy that allows us to implement the method with success. This strategy aims at decomposing the seismic data within partially overlapped frequency intervals by carrying out a concatenated treatment of the wavelet to largely avoid redundant frequency information to adapt to wavelength or wavenumber coverage. A pertinent numerical test proves the effectiveness of this strategy. Based on this strategy, we comparatively analyze the effects of update parameters for the nonlinear conjugate gradient (CG) method and step-length formulas on the multiscale FWI through several numerical tests. The investigations of up to eight versions of the nonlinear CG method with and without Gaussian white noise make clear that the HS (Hestenes and Stiefel in J Res Natl Bur Stand Sect 5:409-436, 1952), CD (Fletcher in Practical methods of optimization vol. 1: unconstrained optimization, Wiley, New York, 1987), and PRP (Polak and Ribière in Revue Francaise Informat Recherche Opertionelle, 3e Année 16:35-43, 1969; Polyak in USSR Comput Math Math Phys 9:94-112, 1969) versions are more efficient among the eight versions, while the DY (Dai and Yuan in SIAM J Optim 10:177-182, 1999) version always yields inaccurate result, because it overestimates the deeper parts of the model. The application of FWI algorithms using distinct step-length formulas, such as the direct method ( Direct), the parabolic search method ( Search), and the two-point quadratic interpolation method ( Interp), proves that the Interp is more efficient for noise-free data, while the Direct is more efficient for Gaussian white noise data. In contrast, the Search is less efficient because of its slow convergence. In general, the three step-length formulas are robust or partly insensitive to Gaussian white noise and the complexity of the model. When the initial velocity model deviates far from the real model or the data are contaminated by noise, the objective function values of the Direct and Interp are oscillating at the beginning of the inversion, whereas that of the Search decreases consistently.
Microfluidic immunomagnetic cell separation from whole blood.
Bhuvanendran Nair Gourikutty, Sajay; Chang, Chia-Pin; Puiu, Poenar Daniel
2016-02-01
Immunomagnetic-based separation has become a viable technique for the separation of cells and biomolecules. Here we report on the design and analysis of a simple and efficient microfluidic device for high throughput and high efficiency capture of cells tagged with magnetic particles. This is made possible by using a microfluidic chip integrated with customized arrays of permanent magnets capable of creating large magnetic field gradients, which determine the effective capturing of the tagged cells. This method is based on manipulating the cells which are under the influence of a combination of magnetic and fluid dynamic forces in a fluid under laminar flow through a microfluidic chip. A finite element analysis (FEA) model is developed to analyze the cell separation process and predict its behavior, which is validated subsequently by the experimental results. The magnetic field gradients created by various arrangements of magnetic arrays have been simulated using FEA and the influence of these field gradients on cell separation has been studied with the design of our microfluidic chip. The proof-of-concept for the proposed technique is demonstrated by capturing white blood cells (WBCs) from whole human blood. CD45-conjugated magnetic particles were added into whole blood samples to label WBCs and the mixture was flown through our microfluidic device to separate the labeled cells. After the separation process, the remaining WBCs in the elute were counted to determine the capture efficiency, and it was found that more than 99.9% WBCs have been successfully separated from whole blood. The proposed design can be used for positive selection as well as for negative enrichment of rare cells. Copyright © 2015 Elsevier B.V. All rights reserved.
Dynamical Approach to Multiequilibria Problems for Mixtures of Acids and Their Conjugated Bases
ERIC Educational Resources Information Center
Glaser, Rainer E.; Delarosa, Marco A.; Salau, Ahmed Olasunkanmi; Chicone, Carmen
2014-01-01
Mathematical methods are described for the determination of steady-state concentrations of all species in multiequilibria systems consisting of several acids and their conjugated bases in aqueous solutions. The main example consists of a mixture of a diprotic acid H[subscript 2]A, a monoprotic acid HB, and their conjugate bases. The reaction…
Wang, Yuyuan; Wang, Yidan; Chen, Guojun; Li, Yitong; Xu, Wei; Gong, Shaoqin
2017-09-13
A quantum-dot (QD)-based micelle conjugated with an anti-epidermal growth factor receptor (EGFR) nanobody (Nb) and loaded with an anticancer drug, aminoflavone (AF), has been engineered for EGFR-overexpressing cancer theranostics. The near-infrared (NIR) fluorescence of the indium phosphate core/zinc sulfide shell QDs (InP/ZnS QDs) allowed for in vivo nanoparticle biodistribution studies. The anti-EGFR nanobody 7D12 conjugation improved the cellular uptake and cytotoxicity of the QD-based micelles in EGFR-overexpressing MDA-MB-468 triple-negative breast cancer (TNBC) cells. In comparison with the AF-encapsulated nontargeted (i.e., without Nb conjugation) micelles, the AF-encapsulated Nb-conjugated (i.e., targeted) micelles accumulated in tumors at higher concentrations, leading to more effective tumor regression in an orthotopic triple-negative breast cancer xenograft mouse model. Furthermore, there was no systemic toxicity observed with the treatments. Thus, this QD-based Nb-conjugated micelle may serve as an effective theranostic nanoplatform for EGFR-overexpressing cancers such as TNBCs.
Primal-dual and forward gradient implementation for quantitative susceptibility mapping.
Kee, Youngwook; Deh, Kofi; Dimov, Alexey; Spincemaille, Pascal; Wang, Yi
2017-12-01
To investigate the computational aspects of the prior term in quantitative susceptibility mapping (QSM) by (i) comparing the Gauss-Newton conjugate gradient (GNCG) algorithm that uses numerical conditioning (ie, modifies the prior term) with a primal-dual (PD) formulation that avoids this, and (ii) carrying out a comparison between a central and forward difference scheme for the discretization of the prior term. A spatially continuous formulation of the regularized QSM inversion problem and its PD formulation were derived. The Chambolle-Pock algorithm for PD was implemented and its convergence behavior was compared with that of GNCG for the original QSM. Forward and central difference schemes were compared in terms of the presence of checkerboard artifacts. All methods were tested and validated on a gadolinium phantom, ex vivo brain blocks, and in vivo brain MRI data with respect to COSMOS. The PD approach provided a faster convergence rate than GNCG. The GNCG convergence rate slowed considerably with smaller (more accurate) values of the conditioning parameter. Using a forward difference suppressed the checkerboard artifacts in QSM, as compared with the central difference. The accuracy of PD and GNCG were validated based on excellent correlation with COSMOS. The PD approach with forward difference for the gradient showed improved convergence and accuracy over the GNCG method using central difference. Magn Reson Med 78:2416-2427, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Towards the automatization of the Foucault knife-edge quantitative test
NASA Astrophysics Data System (ADS)
Rodríguez, G.; Villa, J.; Martínez, G.; de la Rosa, I.; Ivanov, R.
2017-08-01
Given the increasing necessity of simple, economical and reliable methods and instruments for performing quality tests of optical surfaces such as mirrors and lenses, in the recent years we resumed the study of the long forgotten Foucault knife-edge test from the point of view of the physical optics, ultimately achieving a closed mathematical expression that directly relates the knife-edge position along the displacement paraxial axis with the observable irradiance pattern, which later allowed us to propose a quantitative methodology for estimating the wavefront error of an aspherical mirror with precision akin to interferometry. In this work, we present a further improved digital image processing algorithm in which the sigmoidal cost-function for calculating the transient slope-point of each associated intensity-illumination profile is replaced for a simplified version of it, thus making the whole process of estimating the wavefront gradient remarkably more stable and efficient, at the same time, the Fourier based algorithm employed for gradient integration has been replaced as well for a regularized quadratic cost-function that allows a considerably easier introduction of the region of interest (ROI) of the function, which solved by means of a linear gradient conjugate method largely increases the overall accuracy and efficiency of the algorithm. This revised approach of our methodology can be easily implemented and handled by most single-board microcontrollers in the market, hence enabling the implementation of a full-integrated automatized test apparatus, opening a realistic path for even the proposal of a stand-alone optical mirror analyzer prototype.
Motoba, T.; Ohtani, S.; Anderson, B. J.; ...
2015-10-27
In this study, magnetotail processes and structures related to substorm growth phase/onset auroral arcs remain poorly understood mostly due to the lack of adequate observations. In this study we make a comparison between ground-based optical measurements of the premidnight growth phase/onset arcs at subauroral latitudes and magnetically conjugate measurements made by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) at ~780 km in altitude and by the Van Allen Probe B (RBSP-B) spacecraft crossing L values of ~5.0–5.6 in the premidnight inner tail region. The conjugate observations offer a unique opportunity to examine the detailed features of the arcmore » location relative to large-scale Birkeland currents and of the magnetospheric counterpart. Our main findings include (1) at the early stage of the growth phase the quiet auroral arc emerged ~4.3° equatorward of the boundary between the downward Region 2 (R2) and upward Region 1 (R1) currents; (2) shortly before the auroral breakup (poleward auroral expansion) the latitudinal separation between the arc and the R1/R2 demarcation narrowed to ~1.0°; (3) RBSP-B observed a magnetic field signature of a local upward field-aligned current (FAC) connecting the arc with the near-Earth tail when the spacecraft footprint was very close to the arc; and (4) the upward FAC signature was located on the tailward side of a local plasma pressure increase confined near L ~5.2–5.4. These findings strongly suggest that the premidnight arc is connected to highly localized pressure gradients embedded in the near-tail R2 source region via the local upward FAC.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Motoba, T.; Ohtani, S.; Anderson, B. J.
In this study, magnetotail processes and structures related to substorm growth phase/onset auroral arcs remain poorly understood mostly due to the lack of adequate observations. In this study we make a comparison between ground-based optical measurements of the premidnight growth phase/onset arcs at subauroral latitudes and magnetically conjugate measurements made by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) at ~780 km in altitude and by the Van Allen Probe B (RBSP-B) spacecraft crossing L values of ~5.0–5.6 in the premidnight inner tail region. The conjugate observations offer a unique opportunity to examine the detailed features of the arcmore » location relative to large-scale Birkeland currents and of the magnetospheric counterpart. Our main findings include (1) at the early stage of the growth phase the quiet auroral arc emerged ~4.3° equatorward of the boundary between the downward Region 2 (R2) and upward Region 1 (R1) currents; (2) shortly before the auroral breakup (poleward auroral expansion) the latitudinal separation between the arc and the R1/R2 demarcation narrowed to ~1.0°; (3) RBSP-B observed a magnetic field signature of a local upward field-aligned current (FAC) connecting the arc with the near-Earth tail when the spacecraft footprint was very close to the arc; and (4) the upward FAC signature was located on the tailward side of a local plasma pressure increase confined near L ~5.2–5.4. These findings strongly suggest that the premidnight arc is connected to highly localized pressure gradients embedded in the near-tail R2 source region via the local upward FAC.« less
NASA Astrophysics Data System (ADS)
Chen, Lin; Yueming, Li
2018-06-01
In this paper, a coupled mechanical-chemical model is established based on the thermodynamic framework, in which the contribution of chemical expansion to free energy is introduced. The stress-dependent chemical potential equilibrium at the gas-solid interface and the stress gradient-dependent diffusion equation as well as a so-called generalized force which is conjugate to the oxidation rate are derived from the proposed model, which could reflect the influence of stresses on the oxidation reaction. Based on the proposed coupled mechanical-chemical model, a user element subroutine is developed in ABAQUS. The numerical simulation of the high temperature oxidation in the thermal barrier coating is carried out to verify the accuracy of the proposed model, and then the influence of stresses on the oxidation reaction is investigated. In thermally grown oxide, the considerable stresses would be induced by permanent volumetric swelling during the oxidation. The stresses play an important role in the chemical potential equilibrium at the gas-solid interface and strongly affect the oxidation reaction. The gradient of the stresses, however, only occurs in the extremely thin oxidation front layer, which plays a very limited role in the oxidation reaction. The generalized force could be divided into the stress-dependent and the stress-independent parts. Comparing with the stress-independent part, the stress-dependent part is smaller, which has little influence on oxidation reaction.
Targeting Tumor Associated Phosphatidylserine with New Zinc Dipicolylamine-Based Drug Conjugates.
Liu, Yu-Wei; Shia, Kak-Shan; Wu, Chien-Huang; Liu, Kuan-Liang; Yeh, Yu-Cheng; Lo, Chen-Fu; Chen, Chiung-Tong; Chen, Yun-Yu; Yeh, Teng-Kuang; Chen, Wei-Han; Jan, Jiing-Jyh; Huang, Yu-Chen; Huang, Chen-Lung; Fang, Ming-Yu; Gray, Brian D; Pak, Koon Y; Hsu, Tsu-An; Huang, Kuan-Hsun; Tsou, Lun K
2017-07-19
A series of zinc(II) dipicolylamine (ZnDPA)-based drug conjugates have been synthesized to probe the potential of phosphatidylserine (PS) as a new antigen for small molecule drug conjugate (SMDC) development. Using in vitro cytotoxicity and plasma stability studies, PS-binding assay, in vivo pharmacokinetic studies, and maximum tolerated dose profiles, we provided a roadmap and the key parameters required for the development of the ZnDPA based drug conjugate. In particular, conjugate 24 induced tumor regression in the COLO 205 xenograft model and exhibited a more potent antitumor effect with a 70% reduction of cytotoxic payload compared to that of the marketed irinotecan when dosed at the same regimen. In addition to the validation of PS as an effective pharmacodelivery target for SMDC, our work also provided the foundation that, if applicable, a variety of therapeutic agents could be conjugated in the same manner to treat other PS-associated diseases.
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.
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
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
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.
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.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Meng, Zhaohai; Li, Fengting; Xu, Xuechun; Huang, Danian; Zhang, Dailei
2017-02-01
The subsurface three-dimensional (3D) model of density distribution is obtained by solving an under-determined linear equation that is established by gravity data. Here, we describe a new fast gravity inversion method to recover a 3D density model from gravity data. The subsurface will be divided into a large number of rectangular blocks, each with an unknown constant density. The gravity inversion method introduces a stabiliser model norm with a depth weighting function to produce smooth models. The depth weighting function is combined with the model norm to counteract the skin effect of the gravity potential field. As the numbers of density model parameters is NZ (the number of layers in the vertical subsurface domain) times greater than the observed gravity data parameters, the inverse density parameter is larger than the observed gravity data parameters. Solving the full set of gravity inversion equations is very time-consuming, and applying a new algorithm to estimate gravity inversion can significantly reduce the number of iterations and the computational time. In this paper, a new symmetric successive over-relaxation (SSOR) iterative conjugate gradient (CG) method is shown to be an appropriate algorithm to solve this Tikhonov cost function (gravity inversion equation). The new, faster method is applied on Gaussian noise-contaminated synthetic data to demonstrate its suitability for 3D gravity inversion. To demonstrate the performance of the new algorithm on actual gravity data, we provide a case study that includes ground-based measurement of residual Bouguer gravity anomalies over the Humble salt dome near Houston, Gulf Coast Basin, off the shore of Louisiana. A 3D distribution of salt rock concentration is used to evaluate the inversion results recovered by the new SSOR iterative method. In the test model, the density values in the constructed model coincide with the known location and depth of the salt dome.
Free terminal time optimal control problem of an HIV model based on a conjugate gradient method.
Jang, Taesoo; Kwon, Hee-Dae; Lee, Jeehyun
2011-10-01
The minimum duration of treatment periods and the optimal multidrug therapy for human immunodeficiency virus (HIV) type 1 infection are considered. We formulate an optimal tracking problem, attempting to drive the states of the model to a "healthy" steady state in which the viral load is low and the immune response is strong. We study an optimal time frame as well as HIV therapeutic strategies by analyzing the free terminal time optimal tracking control problem. The minimum duration of treatment periods and the optimal multidrug therapy are found by solving the corresponding optimality systems with the additional transversality condition for the terminal time. We demonstrate by numerical simulations that the optimal dynamic multidrug therapy can lead to the long-term control of HIV by the strong immune response after discontinuation of therapy.
Multigrid accelerated simulations for Twisted Mass fermions
NASA Astrophysics Data System (ADS)
Bacchio, Simone; Alexandrou, Constantia; Finkerath, Jacob
2018-03-01
Simulations at physical quark masses are affected by the critical slowing down of the solvers. Multigrid preconditioning has proved to deal effectively with this problem. Multigrid accelerated simulations at the physical value of the pion mass are being performed to generate Nf = 2 and Nf = 2 + 1 + 1 gauge ensembles using twisted mass fermions. The adaptive aggregation-based domain decomposition multigrid solver, referred to as DD-αAMG method, is employed for these simulations. Our simulation strategy consists of an hybrid approach of different solvers, involving the Conjugate Gradient (CG), multi-mass-shift CG and DD-αAMG solvers. We present an analysis of the multigrid performance during the simulations discussing the stability of the method. This significant speeds up the Hybrid Monte Carlo simulation by more than a factor 4 at physical pion mass compared to the usage of the CG solver.
Digital transceiver design for two-way AF-MIMO relay systems with imperfect CSI
NASA Astrophysics Data System (ADS)
Hu, Chia-Chang; Chou, Yu-Fei; Chen, Kui-He
2013-09-01
In the paper, combined optimization of the terminal precoders/equalizers and single-relay precoder is proposed for an amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-way single-relay system with correlated channel uncertainties. Both terminal transceivers and relay precoding matrix are designed based on the minimum mean square error (MMSE) criterion when terminals are unable to erase completely self-interference due to imperfect correlated channel state information (CSI). This robust joint optimization problem of beamforming and precoding matrices under power constraints belongs to neither concave nor convex so that a nonlinear matrix-form conjugate gradient (MCG) algorithm is applied to explore local optimal solutions. Simulation results show that the robust transceiver design is able to overcome effectively the loss of bit-error-rate (BER) due to inclusion of correlated channel uncertainties and residual self-interference.
Comparison of four stable numerical methods for Abel's integral equation
NASA Technical Reports Server (NTRS)
Murio, Diego A.; Mejia, Carlos E.
1991-01-01
The 3-D image reconstruction from cone-beam projections in computerized tomography leads naturally, in the case of radial symmetry, to the study of Abel-type integral equations. If the experimental information is obtained from measured data, on a discrete set of points, special methods are needed in order to restore continuity with respect to the data. A new combined Regularized-Adjoint-Conjugate Gradient algorithm, together with two different implementations of the Mollification Method (one based on a data filtering technique and the other on the mollification of the kernal function) and a regularization by truncation method (initially proposed for 2-D ray sample schemes and more recently extended to 3-D cone-beam image reconstruction) are extensively tested and compared for accuracy and numerical stability as functions of the level of noise in the data.
Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
2014-01-01
Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful sparse representation of the object. The inverse problem of UDT is iteratively resolved by conjugate gradient with nonuniform fast Fourier transform. Simulation results show the effectiveness of the proposed method that the main characteristics of the object can be properly presented with only 16 views. Compared to interpolation and multiband method, the proposed method can provide higher resolution and lower artifacts with the same view number. The robustness to noise and the computation complexity are also discussed. PMID:24868241
NASA Astrophysics Data System (ADS)
Li, Qiang; Popov, Valentin L.
2018-03-01
Recently proposed formulation of the boundary element method for adhesive contacts has been generalized for contacts of power-law graded materials with and without adhesion. Proceeding from the fundamental solution for single force acting on the surface of an elastic half space, first the influence matrix is obtained for a rectangular grid. The inverse problem for the calculation of required stress in the contact area from a known surface displacement is solved using the conjugate-gradient technique. For the transformation between the stresses and displacements, the Fast Fourier Transformation is used. For the adhesive contact of graded material, the detachment criterion based on the energy balance is proposed. The method is validated by comparison with known exact analytical solutions as well as by proving the independence of the mesh size and the grid orientation.
NASA Astrophysics Data System (ADS)
Liang, Li-Feng; Zhang, Hong-Bing; Dan, Zhi-Wei; Xu, Zi-Qiang; Liu, Xiu-Juan; Cao, Cheng-Hao
2017-03-01
Simultaneous prestack inversion is based on the modified Fatti equation and uses the ratio of the P- and S-wave velocity as constraints. We use the relation of P-wave impedance and density (PID) and S-wave impedance and density (SID) to replace the constant Vp/Vs constraint, and we propose the improved constrained Fatti equation to overcome the effect of P-wave impedance on density. We compare the sensitivity of both methods using numerical simulations and conclude that the density inversion sensitivity improves when using the proposed method. In addition, the random conjugate-gradient method is used in the inversion because it is fast and produces global solutions. The use of synthetic and field data suggests that the proposed inversion method is effective in conventional and nonconventional lithologies.
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.
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.
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).
NASA Technical Reports Server (NTRS)
Pandya, Mohagna J.; Baysal, Oktay
1997-01-01
A gradient-based shape optimization based on quasi-analytical sensitivities has been extended for practical three-dimensional aerodynamic applications. The flow analysis has been rendered by a fully implicit, finite-volume formulation of the Euler and Thin-Layer Navier-Stokes (TLNS) equations. Initially, the viscous laminar flow analysis for a wing has been compared with an independent computational fluid dynamics (CFD) code which has been extensively validated. The new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4 with coarse- and fine-grid based computations performed with Euler and TLNS equations. The influence of the initial constraints on the geometry and aerodynamics of the optimized shape has been explored. Various final shapes generated for an identical initial problem formulation but with different optimization path options (coarse or fine grid, Euler or TLNS), have been aerodynamically evaluated via a common fine-grid TLNS-based analysis. The initial constraint conditions show significant bearing on the optimization results. Also, the results demonstrate that to produce an aerodynamically efficient design, it is imperative to include the viscous physics in the optimization procedure with the proper resolution. Based upon the present results, to better utilize the scarce computational resources, it is recommended that, a number of viscous coarse grid cases using either a preconditioned bi-conjugate gradient (PbCG) or an alternating-direction-implicit (ADI) method, should initially be employed to improve the optimization problem definition, the design space and initial shape. Optimized shapes should subsequently be analyzed using a high fidelity (viscous with fine-grid resolution) flow analysis to evaluate their true performance potential. Finally, a viscous fine-grid-based shape optimization should be conducted, using an ADI method, to accurately obtain the final optimized shape.
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.
Molecular diodes based on conjugated diblock co-oligomers.
Ng, Man-Kit; Lee, Dong-Chan; Yu, Luping
2002-10-09
This report describes synthesis and characterization of a molecular diode based upon a diblock conjugated oligomer system. This system consists of two conjugated blocks with opposite electronic demand. The molecular structure exhibits a built-in electronic asymmetry, much like a semiconductor p-n junction. Electrical measurements by scanning tunneling spectroscopy (STS) clearly revealed a pronounced rectifying effect. Definitive proof for the molecular nature of the rectifying effect in this conjugated diblock molecule is provided by control experiments with a structurally similar reference compound.
New Langevin and gradient thermostats for rigid body dynamics.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lonergan, Mark
Final technical report for Conjugated ionomers for photovoltaic applications, electric field driven charge separation in organic photovoltaics. The central goal of the work we completed was been to understand the photochemical and photovoltaic properties of ionically functionalized conjugated polymers (conjugated ionomers or polyelectrolytes) and energy conversion systems based on them. We primarily studied two classes of conjugated polymer interfaces that we developed based either upon undoped conjugated polymers with an asymmetry in ionic composition (the ionic junction) or doped conjugated polymers with an asymmetry in doping type (the p-n junction). The materials used for these studies have primarily been themore » polyacetylene ionomers. We completed a detailed study of p-n junctions with systematically varying dopant density, photochemical creation of doped junctions, and experimental and theoretical work on charge transport and injection in polyacetylene ionomers. We have also completed related work on the use of conjugated ionomers as interlayers that improve the efficiency or organic photovoltaic systems and studied several important aspects of the chemistry of ionically functionalized semiconductors, including mechanisms of so-called "anion-doping", the formation of charge transfer complexes with oxygen, and the synthesis of new polyfluorene polyelectrolytes. We also worked worked with the Haley group at the University of Oregon on new indenofluorene-based organic acceptors.« less
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.
D4Z - a new renumbering for iterative solution of ground-water flow and solute- transport equations
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
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
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
Effect of the strong coupling on the exchange bias field in IrMn/Py/Ru/Co spin valves
NASA Astrophysics Data System (ADS)
Tarazona, H. S.; Alayo, W.; Landauro, C. V.; Quispe-Marcatoma, J.
2018-01-01
The IrMn/Py/Ru/Co (Py = Ni81Fe19) spin valves have been produced by sputtering deposition and analyzed by magnetization measurements and a theoretical modelling of their exchange interactions, based on the macro-spin model. The Ru thickness was grown between 6 and 22 Å, which is small enough to promote strong indirect coupling between Py and Co. Results of measurements showed a large and gradual change in the shape of hysteresis loops when the Ru thickness was varied. The theoretical analysis, using numerical calculations based on the gradient conjugate method, provides the exchange coupling constants (bilinear and biquadratic), the exchange anisotropy fields and the magnetic anisotropy fields (uniaxial and rotatable). The exchange bias fields of spin valves were compared to that of a IrMn/Py bilayer. We found that the difference between these fields oscillates with Ru thickness in the same manner as the bilinear coupling constants.
Metaheuristic and Machine Learning Models for TFE-731-2, PW4056, and JT8D-9 Cruise Thrust
NASA Astrophysics Data System (ADS)
Baklacioglu, Tolga
2017-08-01
The requirement for an accurate engine thrust model has a major antecedence in airline fuel saving programs, assessment of environmental effects of fuel consumption, emissions reduction studies, and air traffic management applications. In this study, utilizing engine manufacturers' real data, a metaheuristic model based on genetic algorithms (GAs) and a machine learning model based on neural networks (NNs) trained with Levenberg-Marquardt (LM), delta-bar-delta (DBD), and conjugate gradient (CG) algorithms were accomplished to incorporate the effect of both flight altitude and Mach number in the estimation of thrust. For the GA model, the analysis of population size impact on the model's accuracy and effect of number of data on model coefficients were also performed. For the NN model, design of optimum topology was searched for one- and two-hidden-layer networks. Predicted thrust values presented a close agreement with real thrust data for both models, among which LM trained NNs gave the best accuracies.
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.
NASA Astrophysics Data System (ADS)
Rewieński, M.; Lamecki, A.; Mrozowski, M.
2013-09-01
This paper proposes a technique, based on the Inexact Shift-Invert Lanczos (ISIL) method with Inexact Jacobi Orthogonal Component Correction (IJOCC) refinement, and a preconditioned conjugate-gradient (PCG) linear solver with multilevel preconditioner, for finding several eigenvalues for generalized symmetric eigenproblems. Several eigenvalues are found by constructing (with the ISIL process) an extended projection basis. Presented results of numerical experiments confirm the technique can be effectively applied to challenging, large-scale problems characterized by very dense spectra, such as resonant cavities with spatial dimensions which are large with respect to wavelengths of the resonating electromagnetic fields. It is also shown that the proposed scheme based on inexact linear solves delivers superior performance, as compared to methods which rely on exact linear solves, indicating tremendous potential of the 'inexact solve' concept. Finally, the scheme which generates an extended projection basis is found to provide a cost-efficient alternative to classical deflation schemes when several eigenvalues are computed.
Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit
2017-05-01
Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.
Huang, Fengchun; Zhang, Huilin; Wang, Lei; Lai, Weihua; Lin, Jianhan
2018-02-15
Combining double-layer capillary based high gradient immunomagnetic separation, invertase-nanocluster based signal amplification and glucose meter based signal detection, a novel biosensor was developed for sensitive and rapid detection of E. coli O157:H7 in this study. The streptavidin modified magnetic nanobeads (MNBs) were conjugated with the biotinylated polyclonal antibodies against E. coli O157:H7 to form the immune MNBs, which were captured by the high gradient magnetic field in the double-layer capillary to specifically separate and efficiently concentrate the target bacteria. Calcium chloride was used with the monoclonal antibodies against E. coli O157:H7 and the invertase to form the immune invertase-nanoclusters (INCs), which were used to react with the target bacteria to form the MNB-bacteria-INC complexes in the capillary. The sucrose was then injected into the capillary and catalyzed by the invertase on the complexes into the glucose, which was detected using the glucose meter to obtain the concentration of the glucose for final determination of the E. coli O157:H7 cells in the sample. A linear relationship between the readout of the glucose meter and the concentration of the E. coli O157:H7 cells (from 10 2 to 10 7 CFU/mL) was found and the lower detection limit of this biosensor was 79 CFU/mL. This biosensor might be extended for the detection of other foodborne pathogens by changing the antibodies and has shown the potential for the detection of foodborne pathogens in a large volume of sample to further increase the sensitivity. Copyright © 2017 Elsevier B.V. All rights reserved.
Conjugate heat and mass transfer in the lattice Boltzmann equation method.
Li, Like; Chen, Chen; Mei, Renwei; Klausner, James F
2014-04-01
An interface treatment for conjugate heat and mass transfer in the lattice Boltzmann equation method is proposed based on our previously proposed second-order accurate Dirichlet and Neumann boundary schemes. The continuity of temperature (concentration) and its flux at the interface for heat (mass) transfer is intrinsically satisfied without iterative computations, and the interfacial temperature (concentration) and their fluxes are conveniently obtained from the microscopic distribution functions without finite-difference calculations. The present treatment takes into account the local geometry of the interface so that it can be directly applied to curved interface problems such as conjugate heat and mass transfer in porous media. For straight interfaces or curved interfaces with no tangential gradient, the coupling between the interfacial fluxes along the discrete lattice velocity directions is eliminated and thus the proposed interface schemes can be greatly simplified. Several numerical tests are conducted to verify the applicability and accuracy of the proposed conjugate interface treatment, including (i) steady convection-diffusion in a channel containing two different fluids, (ii) unsteady convection-diffusion in the channel, (iii) steady heat conduction inside a circular domain with two different solid materials, and (iv) unsteady mass transfer from a spherical droplet in an extensional creeping flow. The accuracy and order of convergence of the simulated interior temperature (concentration) field, the interfacial temperature (concentration), and heat (mass) flux are examined in detail and compared with those obtained from the "half-lattice division" treatment in the literature. The present analysis and numerical results show that the half-lattice division scheme is second-order accurate only when the interface is fixed at the center of the lattice links, while the present treatment preserves second-order accuracy for arbitrary link fractions. For curved interfaces, the present treatment yields second-order accurate interior and interfacial temperatures (concentrations) and first-order accurate interfacial heat (mass) flux. An increase of order of convergence by one degree is obtained for each of these three quantities compared with the half-lattice division scheme. The surface-averaged Sherwood numbers computed in test (iv) agree well with published results.
Conjugate heat and mass transfer in the lattice Boltzmann equation method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, LK; Chen, C; Mei, RW
2014-04-22
An interface treatment for conjugate heat and mass transfer in the lattice Boltzmann equation method is proposed based on our previously proposed second-order accurate Dirichlet and Neumann boundary schemes. The continuity of temperature (concentration) and its flux at the interface for heat (mass) transfer is intrinsically satisfied without iterative computations, and the interfacial temperature (concentration) and their fluxes are conveniently obtained from the microscopic distribution functions without finite-difference calculations. The present treatment takes into account the local geometry of the interface so that it can be directly applied to curved interface problems such as conjugate heat and mass transfer inmore » porous media. For straight interfaces or curved interfaces with no tangential gradient, the coupling between the interfacial fluxes along the discrete lattice velocity directions is eliminated and thus the proposed interface schemes can be greatly simplified. Several numerical tests are conducted to verify the applicability and accuracy of the proposed conjugate interface treatment, including (i) steady convection-diffusion in a channel containing two different fluids, (ii) unsteady convection-diffusion in the channel, (iii) steady heat conduction inside a circular domain with two different solid materials, and (iv) unsteady mass transfer from a spherical droplet in an extensional creeping flow. The accuracy and order of convergence of the simulated interior temperature (concentration) field, the interfacial temperature (concentration), and heat (mass) flux are examined in detail and compared with those obtained from the "half-lattice division" treatment in the literature. The present analysis and numerical results show that the half-lattice division scheme is second-order accurate only when the interface is fixed at the center of the lattice links, while the present treatment preserves second-order accuracy for arbitrary link fractions. For curved interfaces, the present treatment yields second-order accurate interior and interfacial temperatures (concentrations) and first-order accurate interfacial heat (mass) flux. An increase of order of convergence by one degree is obtained for each of these three quantities compared with the half-lattice division scheme. The surface-averaged Sherwood numbers computed in test (iv) agree well with published results.« less
Inhomogeneity in the excited-state torsional disorder of a conjugated macrocycle.
Yang, Jaesung; Ham, Sujin; Kim, Tae-Woo; Park, Kyu Hyung; Nakao, Kazumi; Shimizu, Hideyuki; Iyoda, Masahiko; Kim, Dongho
2015-03-12
The photophysics of conjugated polymers has generally been explained based on the interactions between the component conjugated chromophores in a tangled chain. However, conjugated chromophores are entities with static and dynamic structural disorder, which directly affects the conjugated polymer photophysics. Here we demonstrate the impact of chain structure torsional disorder on the spectral characteristics for a macrocyclic oligothiophene 1, which is obscured in conventional linear conjugated chromophores by diverse structural disorders such as those in chromophore size and shape. We used simultaneous multiple fluorescence parameter measurement for a single molecule and quantum-mechanical calculations to show that within the fixed conjugation length across the entire ring an inhomogeneity from torsional disorder in the structure of 1 plays a crucial role in causing its energetic disorder, which affords the spectral broadening of ∼220 meV. The torsional disorder in 1 fluctuated on the time scale of hundreds of milliseconds, typically accompanied by spectral drifts on the order of ∼10 meV. The fluctuations could generate torsional defects and change the electronic structure of 1 associated with the ring symmetry. These findings disclose the fundamental nature of conjugated chromophore that is the most elementary spectroscopic unit in conjugated polymers and suggest the importance of engineering structural disorder to optimize polymer-based device photophysics. Additionally, we combined defocused wide-field fluorescence microscopy and linear dichroism obtained from the simultaneous measurements to show that 1 emits polarized light with a changing polarization direction based on the torsional disorder fluctuations.
Phenoxazine Based Units- Synthesis, Photophysics and Electrochemistry
Nowakowska-Oleksy, Anna; Cabaj, Joanna
2010-01-01
A few new phenoxazine-based conjugated monomers were synthesized, characterized, and successfully used as semiconducting materials. The phenoxazine-based oligomers have low ionization potentials or high-lying HOMO levels (~4.7 eV), which were estimated from cyclic voltammetry. Conjugated oligomers offer good film—forming, mechanical and optical properties connected with their wide application. These results demonstrate that phenoxazine-based conjugated mers are a promising type of semiconducting and luminescent structures able to be used as thin films in organic electronics. PMID:20625802
NASA Astrophysics Data System (ADS)
Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.
2017-10-01
Over the recent decades, a number of fast approximate solutions of Lippmann-Schwinger equation, which are more accurate than classic Born and Rytov approximations, were proposed in the field of electromagnetic modeling. Those developments could be naturally extended to acoustic and elastic fields; however, until recently, they were almost unknown in seismology. This paper presents several solutions of this kind applied to acoustic modeling for both lossy and lossless media. We evaluated the numerical merits of those methods and provide an estimation of their numerical complexity. In our numerical realization we use the matrix-free implementation of the corresponding integral operator. We study the accuracy of those approximate solutions and demonstrate, that the quasi-analytical approximation is more accurate, than the Born approximation. Further, we apply the quasi-analytical approximation to the solution of the inverse problem. It is demonstrated that, this approach improves the estimation of the data gradient, comparing to the Born approximation. The developed inversion algorithm is based on the conjugate-gradient type optimization. Numerical model study demonstrates that the quasi-analytical solution significantly reduces computation time of the seismic full-waveform inversion. We also show how the quasi-analytical approximation can be extended to the case of elastic wavefield.
Density reconstruction in multiparameter elastic full-waveform inversion
NASA Astrophysics Data System (ADS)
Sun, Min'ao; Yang, Jizhong; Dong, Liangguo; Liu, Yuzhu; Huang, Chao
2017-12-01
Elastic full-waveform inversion (EFWI) is a quantitative data fitting procedure that recovers multiple subsurface parameters from multicomponent seismic data. As density is involved in addition to P- and S-wave velocities, the multiparameter EFWI suffers from more serious tradeoffs. In addition, compared with P- and S-wave velocities, the misfit function is less sensitive to density perturbation. Thus, a robust density reconstruction remains a difficult problem in multiparameter EFWI. In this paper, we develop an improved scattering-integral-based truncated Gauss-Newton method to simultaneously recover P- and S-wave velocities and density in EFWI. In this method, the inverse Gauss-Newton Hessian has been estimated by iteratively solving the Gauss-Newton equation with a matrix-free conjugate gradient algorithm. Therefore, it is able to properly handle the parameter tradeoffs. To give a detailed illustration of the tradeoffs between P- and S-wave velocities and density in EFWI, wavefield-separated sensitivity kernels and the Gauss-Newton Hessian are numerically computed, and their distribution characteristics are analyzed. Numerical experiments on a canonical inclusion model and a modified SEG/EAGE Overthrust model have demonstrated that the proposed method can effectively mitigate the tradeoff effects, and improve multiparameter gradients. Thus, a high convergence rate and an accurate density reconstruction can be achieved.
Hessian-based norm regularization for image restoration with biomedical applications.
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.
NASA Astrophysics Data System (ADS)
Kurtoglu, Yunus Emre
The drug release characteristics of G4-polyamidoamine (PAMAM) dendrimer-ibuprofen conjugates with ester, amide, and peptide linkers were investigated, in addition to a linear PEG-ibuprofen conjugate to understand the effect of architecture and linker on drug release. Ibuprofen was directly conjugated to NH2 -terminated dendrimer by an amide bond and OH-terminated dendrimer by an ester bond. A tetra-peptide linked dendrimer conjugate and a linear mPEG-ibuprofen conjugate were also studied for comparison to direct linked dendrimer conjugates. It is demonstrated that the 3-D nanoscale architecture of PAMAM dendrimer-drug conjugates, along with linking chemistry govern the drug release mechanisms as well as kinetics. Understanding these structural effects on their drug release characteristics is crucial for design of dendrimer conjugates with high efficacy such as poly(amidoamine) dendrimer-N-Acetylcysteine conjugates with disulfide linkages. N-Acetylcysteine (NAC) is an anti-inflammatory agent with significant potential for clinical use in the treatment of neuroinflammation, stroke and cerebral palsy. A poly(amidoamine) dendrimer-NAC conjugate that contains a disulfide linkage was synthesized and evaluated for its release kinetics in the presence of glutathione (GSH), Cysteine (Cys), and bovine serum albumin (BSA) at both physiological and lysosomal pH. FITC-labeled conjugates showed that they enter cells rapidly and localize in the cytoplasm of lipopolysaccharide (LPS)-activated microglial cells. The efficacy of the dendrimer-NAC conjugate was measured in activated microglial cells using reactive oxygen species (ROS) assays. The conjugates showed an order of magnitude increase in anti-oxidant activity compared to free drug. When combined with intrinsic and ligand-based targeting with dendrimers, these types of GSH sensitive nanodevices can lead to improved drug release profiles and in vivo efficacy.
Meng, Bin; Ren, Yi; Liu, Jun; Jäkle, Frieder; Wang, Lixiang
2018-02-19
p-π conjugation with embedded heteroatoms offers unique opportunities to tune the electronic structure of conjugated polymers. An approach is presented to form highly electron-deficient p-π conjugated polymers based on triarylboranes, demonstrate their n-type behavior, and explore device applications. By combining alternating [2,4,6-tris(trifluoromethyl)phenyl]di(thien-2-yl)borane (FBDT) and electron-deficient isoindigo (IID)/pyridine-flanked diketopyrrolopyrrole (DPPPy) units, we achieve low-lying lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) energy levels, high electron mobilities, and broad absorptions in the visible region. All-polymer solar cells with these polymers as electron acceptors exhibit encouraging photovoltaic performance with power conversion efficiencies of up to 2.83 %. These results unambiguously prove the n-type behavior and demonstrate the photovoltaic applications of p-π conjugated polymers based on triarylborane. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Effects of the Substituents of Boron Atoms on Conjugated Polymers Containing B←N Units.
Liu, Jun; Wang, Tao; Dou, Chuandong; Wang, Lixiang
2018-06-15
Organoboron chemistry is a new tool to tune the electronic structures and properties of conjugated polymers, which are important for applications in organic opto-electronic devices. To investigate the effects of substituents of boron atoms on conjugated polymers, we synthesized three conjugated polymers based on double B←N bridged bipyridine (BNBP) with various substituents on the boron atoms. By changing the substituents from four phenyl groups and two phenyl groups/two fluorine atoms to four fluorine atoms, the BNBP-based polymers show the blue-shifted absorption spectra, decreased LUMO/HOMO energy levels and enhanced electron affinities, as well as the increased electron mobilities. Moreover, these BNBP-based polymers can be used as electron acceptors for all-polymer solar cells. These results demonstrate that the substituents of boron atoms can effectively modulate the electronic properties and applications of conjugated polymers. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.
Temel, Burcin; Mills, Greg; Metiu, Horia
2008-03-27
We describe and test an implementation, using a basis set of Chebyshev polynomials, of a variational method for solving scattering problems in quantum mechanics. This minimum error method (MEM) determines the wave function Psi by minimizing the least-squares error in the function (H Psi - E Psi), where E is the desired scattering energy. We compare the MEM to an alternative, the Kohn variational principle (KVP), by solving the Secrest-Johnson model of two-dimensional inelastic scattering, which has been studied previously using the KVP and for which other numerical solutions are available. We use a conjugate gradient (CG) method to minimize the error, and by preconditioning the CG search, we are able to greatly reduce the number of iterations necessary; the method is thus faster and more stable than a matrix inversion, as is required in the KVP. Also, we avoid errors due to scattering off of the boundaries, which presents substantial problems for other methods, by matching the wave function in the interaction region to the correct asymptotic states at the specified energy; the use of Chebyshev polynomials allows this boundary condition to be implemented accurately. The use of Chebyshev polynomials allows for a rapid and accurate evaluation of the kinetic energy. This basis set is as efficient as plane waves but does not impose an artificial periodicity on the system. There are problems in surface science and molecular electronics which cannot be solved if periodicity is imposed, and the Chebyshev basis set is a good alternative in such situations.
Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection
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
A numerical solution for the diffusion equation in hydrogeologic systems
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.
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.
A composite step conjugate gradients squared algorithm for solving nonsymmetric linear systems
NASA Astrophysics Data System (ADS)
Chan, Tony; Szeto, Tedd
1994-03-01
We propose a new and more stable variant of the CGS method [27] for solving nonsymmetric linear systems. The method is based on squaring the Composite Step BCG method, introduced recently by Bank and Chan [1,2], which itself is a stabilized variant of BCG in that it skips over steps for which the BCG iterate is not defined and causes one kind of breakdown in BCG. By doing this, we obtain a method (Composite Step CGS or CSCGS) which not only handles the breakdowns described above, but does so with the advantages of CGS, namely, no multiplications by the transpose matrix and a faster convergence rate than BCG. Our strategy for deciding whether to skip a step does not involve any machine dependent parameters and is designed to skip near breakdowns as well as produce smoother iterates. Numerical experiments show that the new method does produce improved performance over CGS on practical problems.
Electronic structures and magnetic/optical properties of metal phthalocyanine complexes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baba, Shintaro; Suzuki, Atsushi, E-mail: suzuki@mat.usp.ac.jp; Oku, Takeo
2016-02-01
Electronic structures and magnetic / optical properties of metal phthalocyanine complexes were studied by quantum calculations using density functional theory. Effects of central metal and expansion of π orbital on aromatic ring as conjugation system on the electronic structures, magnetic, optical properties and vibration modes of infrared and Raman spectra of metal phthalocyanines were investigated. Electron and charge density distribution and energy levels near frontier orbital and excited states were influenced by the deformed structures varied with central metal and charge. The magnetic parameters of chemical shifts in {sup 13}C-nuclear magnetic resonance ({sup 13}C-NMR), principle g-tensor, A-tensor, V-tensor of electricmore » field gradient and asymmetry parameters derived from the deformed structures with magnetic interaction of nuclear quadruple interaction based on electron and charge density distribution with a bias of charge near ligand under crystal field.« less
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
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.
[Theory, method and application of method R on estimation of (co)variance components].
Liu, Wen-Zhong
2004-07-01
Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.
NASA Astrophysics Data System (ADS)
Bonavita, M.; Torrisi, L.
2005-03-01
A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.
A least-squares finite element method for 3D incompressible Navier-Stokes equations
NASA Technical Reports Server (NTRS)
Jiang, Bo-Nan; Lin, T. L.; Hou, Lin-Jun; Povinelli, Louis A.
1993-01-01
The least-squares finite element method (LSFEM) based on the velocity-pressure-vorticity formulation is applied to three-dimensional steady incompressible Navier-Stokes problems. This method can accommodate equal-order interpolations, and results in symmetric, positive definite algebraic system. An additional compatibility equation, i.e., the divergence of vorticity vector should be zero, is included to make the first-order system elliptic. The Newton's method is employed to linearize the partial differential equations, the LSFEM is used to obtain discretized equations, and the system of algebraic equations is solved using the Jacobi preconditioned conjugate gradient method which avoids formation of either element or global matrices (matrix-free) to achieve high efficiency. The flow in a half of 3D cubic cavity is calculated at Re = 100, 400, and 1,000 with 50 x 52 x 25 trilinear elements. The Taylor-Gortler-like vortices are observed at Re = 1,000.
Tran, S T; Smith, T K
2014-02-01
Deoxynivalenol (DON, vomitoxin) is a trichothecene mycotoxin which can be considered to be an indicator of Fusarium mycotoxin contamination in grain, feed and food. Recent studies have described the presence of glucose conjugated DON, which is a product of plant metabolism, but there is a lack of information available on DON conjugation by fungi. The aim of the current study was, therefore, to investigate the ability of fungi to metabolize DON into hydrolysable conjugated DON. Alternaria alternata (54028 NRRL) and Rhizopus microsporus var. rhizopodiformis (54029 NRRL) were found to be capable of metabolizing DON into hydrolysable conjugated DON. This ranged from 13-23 % conjugation of DON in potato dextrose agar media and from 11-36 % in corn-based media. There was, however, considerable variation between fungal strains in the ability to conjugate DON as only a slight increase in hydrolysable conjugated DON (1-6 %) was observed when incubating with A. oryzae (5509 NRRL). A. oryzae (5509 NRRL) was also shown to degrade DON (up to 92 %) over 21 days of incubation on corn-based media. The current study shows that conjugation of DON can be achieved through fungal metabolism in addition to being a product of plant metabolism.
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.
Personal Cooling Fabric Based on Polymeric Thermoelectrics
2016-07-28
weight organic materials. Furthermore, p- and n-doped conjugated polymers with high electrical conductivity were discovered over two decades ago...fully conjugated PPV polymer MEH-PPV with SWCNT provided films with the highest conductivity while maintaining relatively unchanged Seebeck...Geise, H. J., Synthesis of Electrically Conducting Copolymers with Short Alternating Conjugated and Non- conjugated Blocks. Polymer 1994, 35, (2), 391-397.
NASA Astrophysics Data System (ADS)
Dovgan, Igor; Kolodych, Sergii; Koniev, Oleksandr; Wagner, Alain
2016-08-01
The vast majority of antibody-drug conjugates (ADC) are prepared through amine-to-thiol conjugation. To date, N-Succinimidyl-4-(maleimidomethyl) cyclohexanecarboxylate (SMCC) has been one of the most frequently applied reagents for the preparation of ADC and other functional conjugates. However, SMCC-based conjugates suffer from limited stability in blood circulation and from a hydrophobic character of the linker, which may give rise to major pharmacokinetic implications. To address this issue, we have developed a heterobifunctional analogue of a SMCC reagent, i.e., sodium 4-(maleimidomethyl)-1,3-dioxane-5-carbonyl)oxy)-2,3,5,6- tetrafluorobenzenesulfonate (MDTF) for amine-to-thiol conjugation. By replacing the cyclohexyl ring in the SMCC structure with the 1,3-dioxane, we increased the hydrophilicity of the linker. A FRET probe based on MD linker was prepared and showed superior stability compared to the MCC linker in human plasma, as well as in a variety of aqueous buffers. A detailed investigation demonstrated an accelerated succinimide ring opening for MD linker, resulting in stabilized conjugates. Finally, the MDTF reagent was applied for the preparation of serum stable antibody-dye conjugate.
Accelerated gradient based diffuse optical tomographic image reconstruction.
Biswas, Samir Kumar; Rajan, K; Vasu, R M
2011-01-01
Fast reconstruction of interior optical parameter distribution using a new approach called Broyden-based model iterative image reconstruction (BMOBIIR) and adjoint Broyden-based MOBIIR (ABMOBIIR) of a tissue and a tissue mimicking phantom from boundary measurement data in diffuse optical tomography (DOT). DOT is a nonlinear and ill-posed inverse problem. Newton-based MOBIIR algorithm, which is generally used, requires repeated evaluation of the Jacobian which consumes bulk of the computation time for reconstruction. In this study, we propose a Broyden approach-based accelerated scheme for Jacobian computation and it is combined with conjugate gradient scheme (CGS) for fast reconstruction. The method makes explicit use of secant and adjoint information that can be obtained from forward solution of the diffusion equation. This approach reduces the computational time many fold by approximating the system Jacobian successively through low-rank updates. Simulation studies have been carried out with single as well as multiple inhomogeneities. Algorithms are validated using an experimental study carried out on a pork tissue with fat acting as an inhomogeneity. The results obtained through the proposed BMOBIIR and ABMOBIIR approaches are compared with those of Newton-based MOBIIR algorithm. The mean squared error and execution time are used as metrics for comparing the results of reconstruction. We have shown through experimental and simulation studies that Broyden-based MOBIIR and adjoint Broyden-based methods are capable of reconstructing single as well as multiple inhomogeneities in tissue and a tissue-mimicking phantom. Broyden MOBIIR and adjoint Broyden MOBIIR methods are computationally simple and they result in much faster implementations because they avoid direct evaluation of Jacobian. The image reconstructions have been carried out with different initial values using Newton, Broyden, and adjoint Broyden approaches. These algorithms work well when the initial guess is close to the true solution. However, when initial guess is far away from true solution, Newton-based MOBIIR gives better reconstructed images. The proposed methods are found to be stable with noisy measurement data.
Bruschi, Maurizio; Limacher, Peter A; Hutter, Jürg; Lüthi, Hans Peter
2009-03-10
In this study, we present a scheme for the evaluation of electron delocalization and conjugation efficiency in lineraly π-conjugated systems. The scheme, based on the natural bond orbital theory, allows monitoring the evolution of electron delocalization along an extended conjugation path as well as its response to chemical modification. The scheme presented is evaluated and illustrated by means of a computational investigation of π-conjugation in all-trans polyacetylene [PA; H(-CH═CH)n-H], polydiacetylene [PDA, H(-C≡C-CH═CH)n-H], and polytriacetylene [PTA, H(-C≡C-CH═CH-C≡C)n-H] with up to 180 carbon atoms, all related by the number of ethynyl units incorporated in the chain. We are able to show that for short oligomers the incorporation of ethynyl spacers into the PA chain increases the π-delocalization energy, but, on the other hand, reduces the efficiency with which π-electron delocalization is promoted along the backbone. This explains the generally shorter effective conjugation lengths observed for the properties of the polyeneynes (PDA and PTA) relative to the polyenes (PA). It will also be shown that the reduced conjugation efficiency, within the NBO-based model presented in this work, can be related to the orbital interaction pattern along the π-conjugated chain. We will show that the orbital interaction energy pattern is characteristic for the type and the length of the backbone and may therefore serve as a descriptor for linearly π-conjugated chains.
Amin, Muhammad; Abbas, Nazia Shahana; Hussain, Muhammad Ajaz; Sher, Muhammad; Edgar, Kevin J
2018-07-01
The present study reveals the syntheses of hydroxypropylcellulose‑(HPC) and hydroxyethylcellulose‑(HEC) based macromolecular prodrugs (MPDs) of ciprofloxacin (CIP) using homogeneous reaction methodology. Covalently loaded drug content (DC) of each prodrug was quantified using UV-Vis spectrophotometry to determine degree of substitution (DS). HPC-ciprofloxacin (HPC-CIP) conjugates showed DS of CIP in the range 0.87-1.15 whereas HEC-ciprofloxacin (HEC-CIP) conjugates showed DS range 0.51-0.75. Transmission electron microscopy revealed that HPC-CIP conjugate 2 and HEC-CIP conjugate 6 self-assembled into nanoparticles of 150-300 and 180-250nm, respectively. Size exclusion chromatography revealed HPC-CIP conjugate 2 and HEC-CIP conjugate 6 as monodisperse systems. In vitro drug release studies indicated 15 and 43% CIP release from HPC-CIP conjugate 2 after 6h in simulated gastric and simulated intestinal fluids (SGF and SIF), respectively. HEC-CIP conjugate 6 showed 16% and 46% release after 6h in SGF and SIF, respectively. HPC-CIP conjugate 2 and HEC-CIP conjugate 6 exhibited half-lives of 10.87 and 11.71h, respectively with area under the curve values of 164 and 175hμgmL -1 , respectively, indicating enhanced bioavailability and improved pharmacokinetic profiles in animal model. Equal antibacterial activities to that of unmodified CIP confirmed their competitive efficacies. Cytotoxicity studies supported their non-toxic nature and biocompatibility. Copyright © 2018 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.
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.
Stepwise Assembly and Characterization of DNA Linked Two-Color Quantum Dot Clusters.
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.
An infrared image based methodology for breast lesions screening
NASA Astrophysics Data System (ADS)
Morais, K. C. C.; Vargas, J. V. C.; Reisemberger, G. G.; Freitas, F. N. P.; Oliari, S. H.; Brioschi, M. L.; Louveira, M. H.; Spautz, C.; Dias, F. G.; Gasperin, P.; Budel, V. M.; Cordeiro, R. A. G.; Schittini, A. P. P.; Neto, C. D.
2016-05-01
The objective of this paper is to evaluate the potential of utilizing a structured methodology for breast lesions screening, based on infrared imaging temperature measurements of a healthy control group to establish expected normality ranges, and of breast cancer patients, previously diagnosed through biopsies of the affected regions. An analysis of the systematic error of the infrared camera skin temperature measurements was conducted in several different regions of the body, by direct comparison to high precision thermistor temperature measurements, showing that infrared camera temperatures are consistently around 2 °C above the thermistor temperatures. Therefore, a method of conjugated gradients is proposed to eliminate the infrared camera direct temperature measurement imprecision, by calculating the temperature difference between two points to cancel out the error. The method takes into account the human body approximate bilateral symmetry, and compares measured dimensionless temperature difference values (Δ θ bar) between two symmetric regions of the patient's breast, that takes into account the breast region, the surrounding ambient and the individual core temperatures, and doing so, the results interpretation for different individuals become simple and non subjective. The range of normal whole breast average dimensionless temperature differences for 101 healthy individuals was determined, and admitting that the breasts temperatures exhibit a unimodal normal distribution, the healthy normal range for each region was considered to be the dimensionless temperature difference plus/minus twice the standard deviation of the measurements, Δ θ bar ‾ + 2σ Δ θ bar ‾ , in order to represent 95% of the population. Forty-seven patients with previously diagnosed breast cancer through biopsies were examined with the method, which was capable of detecting breast abnormalities in 45 cases (96%). Therefore, the conjugated gradients method was considered effective in breast lesions screening through infrared imaging in order to recommend a biopsy, even with the use of a low optical resolution camera (160 × 120 pixels) and a thermal resolution of 0.1 °C, whose results were compared to the results of a higher resolution camera (320 × 240 pixels). The main conclusion is that the results demonstrate that the method has potential for utilization as a noninvasive screening exam for individuals with breast complaints, indicating whether the patient should be submitted to a biopsy or not.
Synthesis and Characterization of Bioactive Tamoxifen-conjugated Polymers
Rickert, Emily L.; Trebley, Joseph P.; Peterson, Anton C.; Morrell, Melinda M.; Weatherman, Ross V.
2008-01-01
Macromolecular conjugates of tamoxifen could perhaps be used to circumvent some of the limitations of the extensively used breast cancer drug. To test the feasibility of these conjugates, a 4-hydroxytamoxifen analog was conjugated to a diaminoalkyl linker and then conjugated to activated esters of a poly(methacrylic acid) polymer synthesized by atom transfer radical polymerization. A polymer conjugated to the 4-hydroxytamoxifen analog with a six carbon linker showed high affinity for both estrogen receptor alpha and estrogen receptor beta and potent antagonism of the estrogen receptor in cell-based transcriptional reporter assays. These results suggest that the conjugation of 4-hydroxytamoxifen to a polymer results in a macromolecular conjugate that can display ligand in a manner that can be recognized by estrogen receptor and still act as a potent antiestrogen in cells. PMID:17929966
COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM.
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.
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.
A pH-responsive carboxymethyl dextran-based conjugate as a carrier of docetaxel for cancer therapy.
Han, Hwa Seung; Lee, Minchang; An, Jae Yoon; Son, Soyoung; Ko, Hyewon; Lee, Hansang; Chae, Yee Soo; Kang, Young Mo; Park, Jae Hyung
2016-05-01
Although docetaxel is available for the treatment of various cancers, its clinical applications are limited by its poor water solubility and toxicity to normal cells, resulting in severe adverse effects. In this study, we synthesized a polymeric conjugate with an acid-labile ester linkage, consisting of carboxymethyl dextran (CMD) and docetaxel (DTX), as a potential anticancer drug delivery system. The conjugate exhibited sustained release of DTX in physiological buffer (pH 7.4), whereas its release rate increased remarkably under mildly acidic conditions (pH < 6.5), mimicking the intracellular environment. Cytotoxicity tests conducted in vitro demonstrated that the conjugate exhibited much higher toxicity to cancer cells under mildly acidic conditions than at physiological buffer (pH 7.4). These results implied that the ester linkage in the conjugate allowed for selective release of biologically active DTX under mildly acidic conditions. The in vivo biodistribution of a Cy5.5-labeled conjugate was observed using the noninvasive optical imaging technique after its systemic administration into tumor-bearing mice. The conjugate was effectively accumulated into the tumor site, which may have been because of an enhanced permeability and retention effect. In addition, in vivo antitumor efficacy of the conjugate was significantly higher than that of free DTX. Overall, the CMD-based conjugate might have promising potential as a carrier of DTX for cancer therapy. © 2015 Wiley Periodicals, Inc.
Lu, Dan; Joshi, Amita; Wang, Bei; Olsen, Steve; Yi, Joo-Hee; Krop, Ian E; Burris, Howard A; Girish, Sandhya
2013-08-01
Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate recently approved by the US Food and Drug Administration for the treatment of human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer previously treated with trastuzumab and taxane chemotherapy. It comprises the microtubule inhibitory cytotoxic agent DM1 conjugated to the HER2-targeted humanized monoclonal antibody trastuzumab via a stable linker. To characterize the pharmacokinetics of T-DM1 in patients with metastatic breast cancer, concentrations of multiple analytes were quantified, including serum concentrations of T-DM1 conjugate and total trastuzumab (the sum of conjugated and unconjugated trastuzumab), as well as plasma concentrations of DM1. The clearance of T-DM1 conjugate is approximately 2 to 3 times faster than its parent antibody, trastuzumab. However, the clearance pathways accounting for this faster clearance rate are unclear. An integrated population pharmacokinetic model that simultaneously fits the pharmacokinetics of T-DM1 conjugate and total trastuzumab can help to elucidate the clearance pathways of T-DM1. The model can also be used to predict total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data, thereby reducing the frequency of pharmacokinetic sampling. T-DM1 conjugate and total trastuzumab serum concentration data, including baseline trastuzumab concentrations prior to T-DM1 treatment, from phase I and II studies were used to develop this integrated population pharmacokinetic model. Based on a hypothetical T-DM1 catabolism scheme, two-compartment models for T-DM1 conjugate and trastuzumab were integrated by assuming a one-step deconjugation clearance from T-DM1 conjugate to trastuzumab. The ability of the model to predict the total trastuzumab pharmacokinetic profile based on T-DM1 conjugate pharmacokinetics and various sampling schemes of total trastuzumab pharmacokinetics was assessed to evaluate total trastuzumab sampling schemes. The final model reflects a simplified catabolism scheme of T-DM1, suggesting that T-DM1 clearance pathways include both deconjugation and proteolytic degradation. The model fits T-DM1 conjugate and total trastuzumab pharmacokinetic data simultaneously. The deconjugation clearance of T-DM1 was estimated to be ~0.4 L/day. Proteolytic degradation clearances for T-DM1 and trastuzumab were similar (~0.3 L/day). This model accurately predicts total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data sampled at preinfusion and end of infusion in cycle 1, and in one additional steady state cycle. This semi-mechanistic integrated model links T-DM1 conjugate and total trastuzumab pharmacokinetic data, and supports the inclusion of both proteolytic degradation and deconjugation as clearance pathways in the hypothetical T-DM1 catabolism scheme. The model attributes a faster T-DM1 conjugate clearance versus that of trastuzumab to the presence of a deconjugation process and suggests a similar proteolytic clearance of T-DM1 and trastuzumab. Based on the model and T-DM1 conjugate pharmacokinetic data, a sparse pharmacokinetic sampling scheme for total trastuzumab provides an entire pharmacokinetic profile with similar predictive accuracy to that of a dense pharmacokinetic sampling scheme.
GPU-based acceleration of computations in nonlinear finite element deformation analysis.
Mafi, Ramin; Sirouspour, Shahin
2014-03-01
The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Beratan, David N. (Inventor)
1991-01-01
Highly conjugated organic polymers typically have large non-resonant electronic susceptibilities, which give the molecules unusual optical properties. To enhance these properties, defects are introduced into the polymer chain. Examples include light doping of the conjugated polymer and synthesis, conjugated polymers which incorporate either electron donating or accepting groups, and conjugated polymers which contain a photoexcitable species capable of reversibly transferring its electron to an acceptor. Such defects in the chain permit enhancement of the second hyperpolarizability by at least an order of magnitude.
Integrated circuits based on conjugated polymer monolayer
Li, Mengmeng; Mangalore, Deepthi Kamath; Zhao, Jingbo; ...
2018-01-31
It is still a great challenge to fabricate conjugated polymer monolayer field-effect transistors (PoM-FETs) due to intricate crystallization and film formation of conjugated polymers. Here we demonstrate PoM-FETs based on a single monolayer of a conjugated polymer. The resulting PoM-FETs are highly reproducible and exhibit charge carrier mobilities reaching 3 cm 2 V -1 s -1. The high performance is attributed to the strong interactions of the polymer chains present already in solution leading to pronounced edge-on packing and well-defined microstructure in the monolayer. The high reproducibility enables the integration of discrete unipolar PoM-FETs into inverters and ring oscillators. Realmore » logic functionality has been demonstrated by constructing a 15-bit code generator in which hundreds of self-assembled PoM-FETs are addressed simultaneously. Lastly, our results provide the state-of-the-art example of integrated circuits based on a conjugated polymer monolayer, opening prospective pathways for bottom-up organic electronics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Franklin L.; Farimani, Amir Barati; Gu, Kevin L.
Conjugated polymers are the key material in thin-film organic optoelectronic devices due to the versatility of these molecules combined with their semiconducting properties. A molecular-scale understanding of conjugated polymers is important to the optimization of the thin-film morphology. We examine the solution-phase behavior of conjugated isoindigo-based donor–acceptor polymer single chains of various chain lengths using atomistic molecular dynamics simulations. Our simulations elucidate the transition from a rod-like to a coil-like conformation from an analysis of normal modes and persistence length. In addition, we find another transition based on the solvent environment, contrasting the coil-like conformation in a good solvent withmore » a globule-like conformation in a poor solvent. Altogether, our results provide valuable insights into the transition between conformational regimes for conjugated polymers as a function of both the chain length and the solvent environment, which will help to accurately parametrize higher level models.« less
Lee, Franklin L.; Farimani, Amir Barati; Gu, Kevin L.; ...
2017-10-25
Conjugated polymers are the key material in thin-film organic optoelectronic devices due to the versatility of these molecules combined with their semiconducting properties. A molecular-scale understanding of conjugated polymers is important to the optimization of the thin-film morphology. We examine the solution-phase behavior of conjugated isoindigo-based donor–acceptor polymer single chains of various chain lengths using atomistic molecular dynamics simulations. Our simulations elucidate the transition from a rod-like to a coil-like conformation from an analysis of normal modes and persistence length. In addition, we find another transition based on the solvent environment, contrasting the coil-like conformation in a good solvent withmore » a globule-like conformation in a poor solvent. Altogether, our results provide valuable insights into the transition between conformational regimes for conjugated polymers as a function of both the chain length and the solvent environment, which will help to accurately parametrize higher level models.« less
Integrated circuits based on conjugated polymer monolayer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Mengmeng; Mangalore, Deepthi Kamath; Zhao, Jingbo
It is still a great challenge to fabricate conjugated polymer monolayer field-effect transistors (PoM-FETs) due to intricate crystallization and film formation of conjugated polymers. Here we demonstrate PoM-FETs based on a single monolayer of a conjugated polymer. The resulting PoM-FETs are highly reproducible and exhibit charge carrier mobilities reaching 3 cm 2 V -1 s -1. The high performance is attributed to the strong interactions of the polymer chains present already in solution leading to pronounced edge-on packing and well-defined microstructure in the monolayer. The high reproducibility enables the integration of discrete unipolar PoM-FETs into inverters and ring oscillators. Realmore » logic functionality has been demonstrated by constructing a 15-bit code generator in which hundreds of self-assembled PoM-FETs are addressed simultaneously. Lastly, our results provide the state-of-the-art example of integrated circuits based on a conjugated polymer monolayer, opening prospective pathways for bottom-up organic electronics.« less
Integrated circuits based on conjugated polymer monolayer.
Li, Mengmeng; Mangalore, Deepthi Kamath; Zhao, Jingbo; Carpenter, Joshua H; Yan, Hongping; Ade, Harald; Yan, He; Müllen, Klaus; Blom, Paul W M; Pisula, Wojciech; de Leeuw, Dago M; Asadi, Kamal
2018-01-31
It is still a great challenge to fabricate conjugated polymer monolayer field-effect transistors (PoM-FETs) due to intricate crystallization and film formation of conjugated polymers. Here we demonstrate PoM-FETs based on a single monolayer of a conjugated polymer. The resulting PoM-FETs are highly reproducible and exhibit charge carrier mobilities reaching 3 cm 2 V -1 s -1 . The high performance is attributed to the strong interactions of the polymer chains present already in solution leading to pronounced edge-on packing and well-defined microstructure in the monolayer. The high reproducibility enables the integration of discrete unipolar PoM-FETs into inverters and ring oscillators. Real logic functionality has been demonstrated by constructing a 15-bit code generator in which hundreds of self-assembled PoM-FETs are addressed simultaneously. Our results provide the state-of-the-art example of integrated circuits based on a conjugated polymer monolayer, opening prospective pathways for bottom-up organic electronics.
Zhang, Weidong; Li, Guoping; Xu, Letian; Zhuo, Yue; Wan, Wenming; Yan, Ni; He, Gang
2018-05-21
The introduction of main group elements into conjugated scaffolds is emerging as a key route to novel optoelectronic materials. Herein, an efficient and versatile way to synthesize polymerizable 9,10-azaboraphenanthrene ( BNP )-containing monomers by aromaticity-driven ring expansion reactions between highly antiaromatic borafluorene and azides is reported, and the corresponding conjugated small molecules and polymers are developed as well. The BNP -containing small molecules and conjugated polymers showed good air/moisture stability and notable fluorescence properties. Addition of fluoride ions to the BNP -based small molecules and polymers induced a rapid change in the emission color from blue to green/yellow, respectively, accompanied by strong intensity changes. The conjugated polymers showed better ratiometric sensing performance than small molecules due to the exciton migration along the conjugated chains. Further experiments showed that the sensing process is fully reversible. The films prepared by solution-deposition of BNP -based compounds in the presence of polycaprolactone also showed good ratiometric sensing for fluoride ions.
Nonlinear propagation of phase-conjugate focused sound beams in water
NASA Astrophysics Data System (ADS)
Brysev, A. P.; Krutyansky, L. M.; Preobrazhensky, V. L.; Pyl'nov, Yu. V.; Cunningham, K. B.; Hamilton, M. F.
2000-07-01
Nonlinear propagation of phase-conjugate, focused, ultrasound beams is studied. Measurements are presented of harmonic amplitudes along the axis and in the focal plane of the conjugate beam, and of the waveform and spectrum at the focus. A maximum peak pressure of 3.9 MPa was recorded in the conjugate beam. The measurements are compared with simulations based on the KZK equation, and satisfactory agreement is obtained.
Subpicosecond Optical Digital Computation Using Conjugate Parametric Generators
1989-03-31
Using Phase Conjugate Farametric Generators ..... 12. PERSONAL AUTHOR(S) Alfano, Robert- Eichmann . George; Dorsinville. Roger! Li. Yao 13a. TYPE OF...conjugation-based optical residue arithmetic processor," Y. Li, G. Eichmann , R. Dorsinville, and R. R. Alfano, Opt. Lett. 13, (1988). [2] "Parallel ultrafast...optical digital and symbolic computation via optical phase conjugation," Y. Li, G. Eichmann , R. Dorsinville, Appl. Opt. 27, 2025 (1988). [3
USDA-ARS?s Scientific Manuscript database
ß-Lactoglobulin (BLG)-chlorogenic acid (CA) conjugates were generated with a free radical induced grafting method. BLG-CA conjugates showed better antioxidant activities than that of BLG. The antioxidant activity increased with the increase of CA substitution. The particle sizes of (-)-epigallocatec...
Tan, Mingqian; Ye, Zhen; Jeong, Eun-Kee; Wu, Xueming; Parker, Dennis L; Lu, Zheng-Rong
2011-05-18
Because of the recent observation of the toxic side effects of Gd(III) based MRI contrast agents in patients with impaired renal function, there is strong interest on developing alternative contrast agents for MRI. In this study, macrocyclic Mn(II) chelates were conjugated to nanoglobular carriers, lysine dendrimers with a silsesquioxane core, to synthesize non-Gd(III) based MRI contrast agents. A generation 3 nanoglobular conjugate of Mn(II)-1,4,7-triaazacyclononane-1,4,7-triacetate-GA amide (G3-NOTA-Mn) was also synthesized and evaluated. The per ion T(1) and T(2) relaxivities of G2, G3, G4 nanoglobular Mn(II)-DOTA monoamide conjugates decreased with increasing generation of the carriers. The T(1) relaxivities of G2, G3, and G4 nanoglobular Mn(II)-DOTA conjugates were 3.3, 2.8, and 2.4 mM(-1) s(-1) per Mn(II) chelate at 3 T, respectively. The T(1) relaxivity of G3-NOTA-Mn was 3.80 mM(-1) s(-1) per Mn(II) chelate at 3 T. The nanoglobular macrocyclic Mn(II) chelate conjugates showed good in vivo stability and were readily excreted via renal filtration. The conjugates resulted in much less nonspecific liver enhancement than MnCl(2) and were effective for contrast-enhanced tumor imaging in nude mice bearing MDA-MB-231 breast tumor xenografts at a dose of 0.03 mmol Mn/kg. The nanoglobular macrocyclic Mn(II) chelate conjugates are promising nongadolinium based MRI contrast agents.
NASA Astrophysics Data System (ADS)
Era, Masanao; Shironita, Yu; Soda, Koichi
2018-03-01
Using the squeezed out technique, we successfully prepared PbBr-based layered perovskite Langmuir-Blodgett (LB) films, which have π-conjugated materials as an organic layer (i.e., a phenylenevinylene oligomer, a dithienylethene derivative, and a π-conjugated polyfluorene derivative). The mixed monolayers of π-conjugated materials and octadecylammonium bromide were spread on an aqueous subphase containing saturated PbBr2. During pressing, octadecylammonium molecules were squeezed from the mixed monolayer, and the squeezed ammonium molecules formed the PbBr-based layered perovskite structure at the air-aqueous subphase interface. The monolayers with the PbBr-based layered perovskite structure could be deposited on fused quartz substrates by the LB technique. In addition to the preparation procedure, the structural and optical properties of the layered perovskite LB films and their formation mechanism are reported in this paper.
The Tcp conjugation system of Clostridium perfringens.
Wisniewski, Jessica A; Rood, Julian I
2017-05-01
The Gram-positive pathogen Clostridium perfringens possesses a family of large conjugative plasmids that is typified by the tetracycline resistance plasmid pCW3. Since these plasmids may carry antibiotic resistance genes or genes encoding extracellular or sporulation-associated toxins, the conjugative transfer of these plasmids appears to be important for the epidemiology of C. perfringens-mediated diseases. Sequence analysis of members of this plasmid family identified a highly conserved 35kb region that encodes proteins with various functions, including plasmid replication and partitioning. The tcp conjugation locus also was identified in this region, initially based on low-level amino acid sequence identity to conjugation proteins from the integrative conjugative element Tn916. Genetic studies confirmed that the tcp locus is required for conjugative transfer and combined with biochemical and structural analyses have led to the development of a functional model of the Tcp conjugation apparatus. This review summarises our current understanding of the Tcp conjugation system, which is now one of the best-characterized conjugation systems in Gram-positive bacteria. Copyright © 2017 Elsevier Inc. All rights reserved.
Ferrocene conjugated oligonucleotide for electrochemical detection of DNA base mismatch.
Hasegawa, Yusuke; Takada, Tadao; Nakamura, Mitsunobu; Yamana, Kazushige
2017-08-01
We describe the synthesis, binding, and electrochemical properties of ferrocene-conjugated oligonucleotides (Fc-oligos). The key step for the preparation of Fc-oligos contains the coupling of vinylferrocene to 5-iododeoxyuridine via Heck reaction. The Fc-conjugated deoxyuridine phosphoramidite was used in the Fc-oligonucleotide synthesis. We show that thiol-modified Fc-oligos deposited onto gold electrodes possess potential ability in electrochemical detection of DNA base mismatch. Copyright © 2017 Elsevier Ltd. All rights reserved.
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
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
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.
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.
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.
Numerical solution of the Hele-Shaw equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whitaker, N.
1987-04-01
An algorithm is presented for approximating the motion of the interface between two immiscible fluids in a Hele-Shaw cell. The interface is represented by a set of volume fractions. We use the Simple Line Interface Calculation method along with the method of fractional steps to transport the interface. The equation of continuity leads to a Poisson equation for the pressure. The Poisson equation is discretized. Near the interface where the velocity field is discontinuous, the discretization is based on a weak formulation of the continuity equation. Interpolation is used on each side of the interface to increase the accuracy ofmore » the algorithm. The weak formulation as well as the interpolation are based on the computed volume fractions. This treatment of the interface is new. The discretized equations are solved by a modified conjugate gradient method. Surface tension is included and the curvature is computed through the use of osculating circles. For perturbations of small amplitude, a surprisingly good agreement is found between the numerical results and linearized perturbation theory. Numerical results are presented for the finite amplitude growth of unstable fingers. 62 refs., 13 figs.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buckner, Mark A; Bobrek, Miljko; Farquhar, Ethan
Wireless Access Points (WAP) remain one of the top 10 network security threats. This research is part of an effort to develop a physical (PHY) layer aware Radio Frequency (RF) air monitoring system with multi-factor authentication to provide a first-line of defense for network security--stopping attackers before they can gain access to critical infrastructure networks through vulnerable WAPs. This paper presents early results on the identification of OFDM-based 802.11a WiFi devices using RF Distinct Native Attribute (RF-DNA) fingerprints produced by the Fractional Fourier Transform (FRFT). These fingerprints are input to a "Learning from Signals" (LFS) classifier which uses hybrid Differentialmore » Evolution/Conjugate Gradient (DECG) optimization to determine the optimal features for a low-rank model to be used for future predictions. Results are presented for devices under the most challenging conditions of intra-manufacturer classification, i.e., same-manufacturer, same-model, differing only in serial number. The results of Fractional Fourier Domain (FRFD) RF-DNA fingerprints demonstrate significant improvement over results based on Time Domain (TD), Spectral Domain (SD) and even Wavelet Domain (WD) fingerprints.« less
Smart linkers in polymer-drug conjugates for tumor-targeted delivery.
Chang, Minglu; Zhang, Fang; Wei, Ting; Zuo, Tiantian; Guan, Yuanyuan; Lin, Guimei; Shao, Wei
2016-01-01
To achieve effective chemotherapy, many types of drug delivery systems have been developed for the specific environments in tumor tissues. Polymer-drug conjugates are increasingly used in tumor therapy due to several significant advantages over traditional delivery systems. In the fabrication of polymer-drug conjugates, a smart linker is an important component that joins two fragments or molecules together and can be cleared by a specific stimulus, which results in targeted drug delivery and controlled release. By regulating the conjugation between the drug and the nanocarriers, stimulus-sensitive systems based on smart linkers can offer high payloads, certified stability, controlled release and targeted delivery. In this review, we summarize the current state of smart linkers (e.g. disulfide, hydrazone, peptide, azo) used recently in various polymer-drug conjugate-based delivery systems with a primary focus on their sophisticated design principles and drug delivery mechanisms as well as in vivo processes.
Ponedel'kina, Irina Yu; Gaskarova, Aigul R; Khaybrakhmanova, Elvira A; Lukina, Elena S; Odinokov, Victor N
2016-06-25
In this study, water soluble hyaluronic acid (HA) based hydroxamate and conjugates with biologically active amines and hydrazides such as p- and o-aminophenols, anthranilic, 4- and 5-aminosalicylic acids, nicotinic, N-benzylnicotinic and isonicotinic hydrazides, p-aminobenzenesulfonamide (Streptocide), p-aminobenzoic acid diethylaminoethyl ester (Procaine), and 4-amino-2,3-dimethyl-1-phenyl-3-pyrazolin-5-one (4-aminoantipyrene) were examined as matrix metalloproteinase-2 inhibitors (MMPIs). In a dose of 0.27-270μM, the most efficient MMPIs were HA conjugates with o-aminophenol=4-aminoantipyrine>4-aminosalicylic acid>5-aminosalicylic acid. Conjugates with Streptocide, Procaine and HA hydroxamate showed 40-50% inhibitory effect at all used concentrations. Conjugates with anthranilic acid and isonicotinic hydrazide (Isoniazid) in a dose of 0.27μM inhibited enzyme activity by ∼70%, but with the concentration increase their inhibitory effect was decreased. Copyright © 2016 Elsevier Ltd. All rights reserved.
Toward High Performance Photovoltaic Cells based on Conjugated Polymers
2016-12-26
AFRL-AFOSR-JP-TR-2016-0103 Toward High Performance Photovoltaic Cells based on Conjugated Polymers Kung-Hwa Wei National Chiao Tung University Final...Conjugated Polymers 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA2386-15-1-4113 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Kung-Hwa Wei 5d. PROJECT...gap polymer with good packing order as the active layer for a single-junction photovoltaic device. The light absorptions for the small molecule and the
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.
Multilevel Investigation of Charge Transport in Conjugated Polymers.
Dong, Huanli; Hu, Wenping
2016-11-15
Conjugated polymers have attracted the world's attentions since their discovery due to their great promise for optoelectronic devices. However, the fundamental understanding of charge transport in conjugated polymers remains far from clear. The origin of this challenge is the natural disorder of polymers with complex molecular structures in the solid state. Moreover, an effective way to examine the intrinsic properties of conjugated polymers is absent. Optoelectronic devices are always based on spin-coated films. In films, polymers tend to form highly disordered structures at nanometer to micrometer length scales due to the high degree of conformational freedom of macromolecular chains and the irregular interchain entanglement, thus typically resulting in much lower charge transport properties than their intrinsic performance. Furthermore, a subtle change of processing conditions may dramatically affect the film formation-inducing large variations in the morphology, crystallinity, microstructure, molecular packing, and alignment, and finally varying the effective charge transport significantly and leading to great inconsistency over an order of magnitude even for devices based on the same polymer semiconductor. Meanwhile, the charge transport mechanism in conjugated polymers is still unclear and its investigation is challenging based on such complex microstructures of polymers in films. Therefore, how to objectively evaluate the charge transport and probe the charge transport mechanism of conjugated polymers has confronted the world for decades. In this Account, we present our recent progress on multilevel charge transport in conjugated polymers, from disordered films, uniaxially aligned thin films, and single crystalline micro- or nanowires to molecular scale, where a derivative of poly(para-phenylene ethynylene) with thioacetyl end groups (TA-PPE) is selected as the candidate for investigation, which could also be extended to other conjugated polymer systems. Our systematic investigations demonstrated that 3-4 orders higher charge transport properties could be achieved with the improvement of polymer chain order and confirmed efficient charge transport along the conjugated polymer backbones. Moreover, with downscaling to molecular scale, many novel phenomena were observed such as the largely quantized electronic structure for an 18 nm-long TA-PPE and the modulation of the redox center of tetrathiafulvalene (TTF) units on tunneling charge transport, which opens the door for conjugated polymers used in nanometer quantum devices. We hope the understanding of charge transport in PPE and its related conjugated polymer at multilevel scale in this Account will provide a new method to sketch the charge transport properties of conjugated polymers, and new insights into the combination of more conjugated polymer materials in the multilevel optoelectronic and other related functional devices, which will offer great promise for the next generation of electronic devices.
NASA Astrophysics Data System (ADS)
Kumar, V.; Singh, A.; Sharma, S. P.
2016-12-01
Regular grid discretization is often utilized to define complex geological models. However, this subdivision strategy performs at lower precision to represent the topographical observation surface. We have developed a new 2D unstructured grid based inversion for magnetic data for models including topography. It will consolidate prior parametric information into a deterministic inversion system to enhance the boundary between the different lithology based on recovered magnetic susceptibility distribution from the inversion. The presented susceptibility model will satisfy both the observed magnetic data and parametric information and therefore can represent the earth better than geophysical inversion models that only honor the observed magnetic data. Geophysical inversion and lithology classification are generally treated as two autonomous methodologies and connected in a serial way. The presented inversion strategy integrates these two parts into a unified scheme. To reduce the storage space and computation time, the conjugate gradient method is used. It results in feasible and practical imaging inversion of magnetic data to deal with large number of triangular grids. The efficacy of the presented inversion is demonstrated using two synthetic examples and one field data example.
Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI.
Hu, Changwei; Qu, Xiaobo; Guo, Di; Bao, Lijun; Chen, Zhong
2011-09-01
Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ℓ(2) data fidelity term and ℓ(1) sparsity regularization term. Rather than manually setting the regularization parameter for the ℓ(1) term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression. Copyright © 2011 Elsevier Inc. All rights reserved.
Azami, Hamed; Escudero, Javier
2015-08-01
Breast cancer is one of the most common types of cancer in women all over the world. Early diagnosis of this kind of cancer can significantly increase the chances of long-term survival. Since diagnosis of breast cancer is a complex problem, neural network (NN) approaches have been used as a promising solution. Considering the low speed of the back-propagation (BP) algorithm to train a feed-forward NN, we consider a number of improved NN trainings for the Wisconsin breast cancer dataset: BP with momentum, BP with adaptive learning rate, BP with adaptive learning rate and momentum, Polak-Ribikre conjugate gradient algorithm (CGA), Fletcher-Reeves CGA, Powell-Beale CGA, scaled CGA, resilient BP (RBP), one-step secant and quasi-Newton methods. An NN ensemble, which is a learning paradigm to combine a number of NN outputs, is used to improve the accuracy of the classification task. Results demonstrate that NN ensemble-based classification methods have better performance than NN-based algorithms. The highest overall average accuracy is 97.68% obtained by NN ensemble trained by RBP for 50%-50% training-test evaluation method.
CONJUGATED POLYMERS AND POLYELECTROLYTES IN SOLAR PHOTOCONVERSION, Final Technical Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schanze, Kirk S
2014-08-05
This DOE-supported program investigated the fundamental properties of conjugated polyelectrolytes, with emphasis placed on studies of excited state energy transport, self-assembly into conjugated polyelectroyte (CPE) based films and colloids, and exciton transport and charge injection in CPE films constructed atop wide bandgap semiconductors. In the most recent grant period we have also extended efforts to examine the properties of low-bandgap donor-acceptor conjugated polyelectrolytes that feature strong visible light absorption and the ability to adsorb to metal-oxide interfaces.
Wang, Wei-Yuan; Zhao, Xiu-Fen; Ju, Xiao-Han; Liu, Ping; Li, Jing; Tang, Ya-Wen; Li, Shu-Ping; Li, Xiao-Dong; Song, Fu-Gui
2018-03-01
Au-methotrexate (Au-MTX) conjugates induced by sugar molecules were produced by a simple, one-pot, hydrothermal growth method. Herein, the Au(III)-MTX complexes were used as the precursors to form Au-MTX conjugates. Addition of different types of sugar molecules with abundant hydroxyl groups resulted in the formation of Au-MTX conjugates featuring distinct characteristics that could be explained by the diverse capping mechanisms of sugar molecules. That is, the instant-capping mechanism of glucose favored the generation of peanut-like Au-MTX conjugates with high colloidal stability while the post-capping mechanism of dextran and sucrose resulted in the production of Au-MTX conjugates featuring excellent near-infrared (NIR) optical properties with a long-wavelength plasmon resonance near 630-760 nm. Moreover, in vitro bioassays showed that cancer cell viabilities upon incubation with free MTX, Au-MTX conjugates doped with glucose, dextran and sucrose for 48 h were 74.6%, 55.0%, 62.0%, and 63.1%, respectively. Glucose-doped Au-MTX conjugates exhibited a higher anticancer activity than those doped with dextran and sucrose, therefore potentially presenting a promising treatment platform for anticancer therapy. Based on the present study, this work may provide the first example of using biocompatible sugars as regulating agents to effectively guide the shape and assembly behavior of Au-MTX conjugates. Potentially, the synergistic strategy of drug molecules and sugar molecules may offer the possibility to create more gold-based nanocarriers with new shapes and beneficial features for advanced anticancer therapy. Copyright © 2018 Elsevier B.V. All rights reserved.
He, B; Xia, S; Yu, F; Fu, Y; Li, W; Wang, Q; Lu, L; Jiang, S
2016-02-01
The emergence of influenza A H7N9 in infection has posed a great threat to public health globally. Poor immunogenicity of H7N9 haemagglutinin (HA) is a major obstacle to the development of an effective H7N9 vaccine. Here, we found that the vaccine containing the H7HA head conjugated with IgG Fc (Hd-Fc) induced strong neutralizing antibody responses and protection against H7N9 infection, whilst the Fc-conjugated H7HA stalk (St-Fc)-based vaccine could not induce neutralizing antibodies, although the St-Fc-immunized mice were partially protected. The vaccines containing the full-length extracellular domain of HA conjugated with Fc and the mixture of Hd-Fc plus St-Fc induced significantly lower neutralizing antibody and haemagglutination inhibition titres than the Hd-Fc-based vaccine. These results suggest that the St-Fc may have inhibitory effects on the neutralizing immunogenicity of Hd-Fc. Therefore, the neutralizing domain(s), such as the receptor-binding domain, in the HA head should be kept and the non-neutralizing domain(s) in the HA stalk with the ability to potentially suppress the neutralizing immunogenicity of HA head should be removed from Fc-conjugated HA-based influenza vaccines to increase the neutralizing antibody response.
An improved conjugate gradient scheme to the solution of least squares SVM.
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.
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.
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.
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.
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.
Dobbins, RL; O'Connor‐Semmes, RL; Young, MA
2016-01-01
A systems model was developed to describe the metabolism and disposition of ursodeoxycholic acid (UDCA) and its conjugates in healthy subjects based on pharmacokinetic (PK) data from published studies in order to study the distribution of oral UDCA and potential interactions influencing therapeutic effects upon interruption of its enterohepatic recirculation. The base model was empirically adapted to patients with primary biliary cirrhosis (PBC) based on current understanding of disease pathophysiology and clinical measurements. Simulations were performed for patients with PBC under two competing hypotheses: one for inhibition of ileal absorption of both UDCA and conjugates and the other only of conjugates. The simulations predicted distinctly different bile acid distribution patterns in plasma and bile. The UDCA model adapted to patients with PBC provides a platform to investigate a complex therapeutic drug interaction among UDCA, UDCA conjugates, and inhibition of ileal bile acid transport in this rare disease population. PMID:27537780
Gomes, Nadirlene Pereira; Erdmann, Alacoque Lorenzini
2014-01-01
Objective to construct a theoretical matrix based on the meanings of the interactions and actions experienced by the professionals regarding the nursing care practices and the health of women in situations of conjugal violence in the ambit of the Family Health Strategy. Methods research based in Grounded Theory. Following approval by the Research Ethics Committee, 52 professionals were interviewed in Santa Catarina, Brazil. The analysis was based on open, axial and selective codifications. Results the theoretical model was delimited based on the phenomenon "Recognizing conjugal violence as a public health problem, and the need for management of the care for the woman", which reflects the experience of the professionals in relation to care for the woman, as well as the meanings attributed to this care. Conclusions the phenomenon allows one to understand the movement of action and interaction regarding the care for the woman in a situation of conjugal violence. PMID:24553706
Chen, Juan-Juan; Huang, Yi-Zhen; Song, Mei-Ru; Zhang, Zhi-Hong; Xue, Jin-Ping
2017-09-21
Small-molecular-target-based photodynamic therapy-a promising targeted anticancer strategy-was developed by conjugating zinc(II) phthalocyanine with a small-molecular-target-based anticancer drug. To prevent self-aggregation and avoid problems of phthalocyanine isomerization, two silicon phthalocyanines di-substituted axially with erlotinib have been synthesized and fully characterized. These conjugates are present in monomeric form in various solvents as well as culture media. Cell-based experiments showed that these conjugates localize in lysosomes and mitochondria, while maintaining high photodynamic activities (IC 50 values as low as 8 nm under a light dose of 1.5 J cm -2 ). With erlotinib as the targeting moiety, two conjugates were found to exhibit high specificity for EGFR-overexpressing cancer cells. Various poly(ethylene glycol) (PEG) linker lengths were shown to have an effect on the photophysical/photochemical properties and on in vitro phototoxicity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Gomes, Nadirlene Pereira; Erdmann, Alacoque Lorenzini
2014-01-01
to construct a theoretical matrix based on the meanings of the interactions and actions experienced by the professionals regarding the nursing care practices and the health of women in situations of conjugal violence in the ambit of the Family Health Strategy. research based in Grounded Theory. Following approval by the Research Ethics Committee, 52 professionals were interviewed in Santa Catarina, Brazil. The analysis was based on open, axial and selective codifications. the theoretical model was delimited based on the phenomenon "Recognizing conjugal violence as a public health problem, and the need for management of the care for the woman", which reflects the experience of the professionals in relation to care for the woman, as well as the meanings attributed to this care. the phenomenon allows one to understand the movement of action and interaction regarding the care for the woman in a situation of conjugal violence.
The Use of Conjugate Charts in Transfer Reactions: A Unified Approach
ERIC Educational Resources Information Center
Allnutt, Michael I.
2007-01-01
Redox reactions can be conveniently discussed in terms of the relative strengths of the oxidant, the reductant, and their conjugates; a conjugate chart is a most convenient and useful way of doing this. A similar chart for acids and bases is proposed, which can be applied in the same manner. (Contains 7 figures and 2 tables.)
Quantitative studies of sulphate conjugation by isolated rat liver cells using [35S]sulphate.
Dawson, J; Knowles, R G; Pogson, C I
1991-06-21
We have developed a simple, rapid and sensitive method for the study of sulphate conjugation in isolated liver cells based on the incorporation of 35S from [35S]sulphate. Excess [35S]sulphate is removed by a barium precipitation procedure, leaving [35S]sulphate conjugates in solution. We have used this method to examine the kinetics of sulphation of N-acetyl-p-aminophenol (acetaminophen), 4-nitrophenol and 1-naphthol in isolated rat liver cells. The efficiency of recovery of the sulphate conjugates was greater than 86%. The method is applicable to the quantitative study of sulphate conjugation of any substrate which forms a sulphate conjugate that is soluble in the presence of barium, without the need for standards or radiolabelled sulphate acceptors.
NASA Astrophysics Data System (ADS)
Huang, Richard Y.-C.; O'Neil, Steven R.; Lipovšek, Daša; Chen, Guodong
2018-05-01
Higher-order structure (HOS) characterization of therapeutic protein-drug conjugates for comprehensive assessment of conjugation-induced protein conformational changes is an important consideration in the biopharmaceutical industry to ensure proper behavior of protein therapeutics. In this study, conformational dynamics of a small therapeutic protein, adnectin 1, together with its drug conjugate were characterized by hydrogen/deuterium exchange mass spectrometry (HDX-MS) with different spatial resolutions. Top-down HDX allows detailed assessment of the residue-level deuterium content in the payload conjugation region. HDX-MS dataset revealed the ability of peptide-based payload/linker to retain deuterium in HDX experiments. Combined results from intact, top-down, and bottom-up HDX indicated no significant conformational changes of adnectin 1 upon payload conjugation. [Figure not available: see fulltext.
NASA Astrophysics Data System (ADS)
Toušek, J.; Toušková, J.; Remeš, Z.; Chomutová, R.; Čermák, J.; Helgesen, M.; Carlé, J. E.; Krebs, F. C.
2015-12-01
Measurements of electrical conductivity, electron work function, carrier mobility of holes and the diffusion length of excitons were performed on samples of conjugated polymers relevant to polymer solar cells. A state of the art fluorinated benzothiadiazole based conjugated copolymer (PBDTTHD - DTBTff) was studied and benchmarked against the reference polymer poly-3-hexylthiophene (P3HT). We employed, respectively, four electrode conductivity measurements, Kelvin probe work function measurements, carrier mobility using charge extraction by linearly increasing voltage (CELIV) measurements and diffusion length determinaton using surface photovoltage measurements.
A coupled electro-thermal Discontinuous Galerkin method
NASA Astrophysics Data System (ADS)
Homsi, L.; Geuzaine, C.; Noels, L.
2017-11-01
This paper presents a Discontinuous Galerkin scheme in order to solve the nonlinear elliptic partial differential equations of coupled electro-thermal problems. In this paper we discuss the fundamental equations for the transport of electricity and heat, in terms of macroscopic variables such as temperature and electric potential. A fully coupled nonlinear weak formulation for electro-thermal problems is developed based on continuum mechanics equations expressed in terms of energetically conjugated pair of fluxes and fields gradients. The weak form can thus be formulated as a Discontinuous Galerkin method. The existence and uniqueness of the weak form solution are proved. The numerical properties of the nonlinear elliptic problems i.e., consistency and stability, are demonstrated under specific conditions, i.e. use of high enough stabilization parameter and at least quadratic polynomial approximations. Moreover the prior error estimates in the H1-norm and in the L2-norm are shown to be optimal in the mesh size with the polynomial approximation degree.
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.
NASA Astrophysics Data System (ADS)
Fischer, Robert E.; Smith, Warren J.; Harvey, James
1986-01-01
Papers dealing with current materials for gradient-index optics, an intelligent data-base system for optical designers; tilted mirror systems; a null-lens design approach for centrally obscured components; the use of the vector aberration theory to optimize an unobscured optical system; multizone bifocal contact lens design; and the concentric meniscus element are presented. Topics discussed include optical manufacturing in the Far East; the optical performance of molded-glass lenses for optical memory applications; through-wafer optical interconnects for multiwafer wafer-scale integrated architecture; optical thin-flim monitoring using optical fibers; aerooptical testing; optical inspection; and a system analysis program for a 32K microcomputer. Consideration is given to various theories, algorithms, and applications of diffraction, a vector formulation of a ray-equivalent method for Gaussian beam propagation; Fourier optical analysis of aberrations in focused laser beams; holography and moire interferometry; and phase-conjugate optical correctors for diffraction-limited applications.
On the inversion of geodetic integrals defined over the sphere using 1-D FFT
NASA Astrophysics Data System (ADS)
García, R. V.; Alejo, C. A.
2005-08-01
An iterative method is presented which performs inversion of integrals defined over the sphere. The method is based on one-dimensional fast Fourier transform (1-D FFT) inversion and is implemented with the projected Landweber technique, which is used to solve constrained least-squares problems reducing the associated 1-D cyclic-convolution error. The results obtained are as precise as the direct matrix inversion approach, but with better computational efficiency. A case study uses the inversion of Hotine’s integral to obtain gravity disturbances from geoid undulations. Numerical convergence is also analyzed and comparisons with respect to the direct matrix inversion method using conjugate gradient (CG) iteration are presented. Like the CG method, the number of iterations needed to get the optimum (i.e., small) error decreases as the measurement noise increases. Nevertheless, for discrete data given over a whole parallel band, the method can be applied directly without implementing the projected Landweber method, since no cyclic convolution error exists.
Parallel consensual neural networks.
Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H
1997-01-01
A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.
Imaging Internal Structure of Long Bones Using Wave Scattering Theory.
Zheng, Rui; Le, Lawrence H; Sacchi, Mauricio D; Lou, Edmond
2015-11-01
An ultrasonic wavefield imaging method is developed to reconstruct the internal geometric properties of long bones using zero-offset data acquired axially on the bone surface. The imaging algorithm based on Born scattering theory is implemented with the conjugate gradient iterative method to reconstruct an optimal image. In the case of a multilayered velocity model, ray tracing through a smooth medium is used to calculate the traveled distance and traveling time. The method has been applied to simulated and real data. The results indicate that the interfaces of the top cortex are accurately imaged and correspond favorably to the original model. The reconstructed bottom cortex below the marrow is less accurate mainly because of the low signal-to-noise ratio. The current imaging method has successfully recovered the top cortical layer, providing a potential tool to investigate the internal structures of long bone cortex for osteoporosis assessment. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wannamaker, Philip E.
We have developed an algorithm for the inversion of magnetotelluric (MT) data to a 3D earth resistivity model based upon the finite element method. Hexahedral edge finite elements are implemented to accommodate discontinuities in the electric field across resistivity boundaries, and to accurately simulate topographic variations. All matrices are reduced and solved using direct solution modules which avoids ill-conditioning endemic to iterative solvers such as conjugate gradients, principally PARDISO for the finite element system and PLASMA for the parameter step estimate. Large model parameterizations can be handled by transforming the Gauss-Newton estimator to data-space form. Accuracy of the forward problemmore » and jacobians has been checked by comparison to integral equations results and by limiting asymptotes. Inverse accuracy and performance has been verified against the public Dublin Secret Test Model 2 and the well-known Mount St Helens 3D MT data set. This algorithm we believe is the most capable yet for forming 3D images of earth resistivity structure and their implications for geothermal fluids and pathways.« less
Parallel Reconstruction Using Null Operations (PRUNO)
Zhang, Jian; Liu, Chunlei; Moseley, Michael E.
2011-01-01
A novel iterative k-space data-driven technique, namely Parallel Reconstruction Using Null Operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data calibration and image reconstruction are formulated into linear algebra problems based on a generalized system model. An optimal data calibration strategy is demonstrated by using Singular Value Decomposition (SVD). And an iterative conjugate- gradient approach is proposed to efficiently solve missing k-space samples during reconstruction. With its generalized formulation and precise mathematical model, PRUNO reconstruction yields good accuracy, flexibility, stability. Both computer simulation and in vivo studies have shown that PRUNO produces much better reconstruction quality than autocalibrating partially parallel acquisition (GRAPPA), especially under high accelerating rates. With the aid of PRUO reconstruction, ultra high accelerating parallel imaging can be performed with decent image quality. For example, we have done successful PRUNO reconstruction at a reduction factor of 6 (effective factor of 4.44) with 8 coils and only a few autocalibration signal (ACS) lines. PMID:21604290
Zhao, Lei; Cui, Tie Jun
2005-12-01
An enhancement of the specific absorption rate (SAR) inside a lossy dielectric object has been investigated theoretically based on a slab of left-handed medium (LHM). In order to make an accurate analysis of SAR distribution, a proper Green's function involved in the LHM slab is proposed, from which an integral equation for the electric field inside the dielectric object is derived. Such an integral equation has been solved accurately and efficiently using the conjugate gradient method and the fast Fourier transform. We have made a lot of numerical experiments on the SAR distributions inside the dielectric object excited by a line source with and without the LHM slab. Numerical experiments show that SAR can be enhanced tremendously when the LHM slab is involved due to the proper usage of strong surface waves, which will be helpful in the potential biomedical applications for hyperthermia. The physical insight for such a phenomenon has also been discussed.
Cummings, J; MacLellan, A J; Mark, M; Jodrell, D I
1999-09-24
[Arg6, D-Trp7,9 mePhe8]-substance P (6-11), code-named antagonist G, is a novel peptide currently undergoing early clinical trials as an anticancer drug. A sensitive, high efficiency high-performance liquid chromatography (HPLC) method is described for the determination in human plasma of antagonist G and its three major metabolites, deamidated-G (M1), G-minus Met11 (M2) and G[Met11(O)] (M3). Gradient elution was employed using 40 mM ammonium acetate in 0.15% trifluoroacetic acid as buffer A and acetonitrile as solvent B, with a linear gradient increasing from 30 to 100% B over 15 min, together with a microbore analytical column (microBondapak C18, 30 cm X 2 mm I.D.). Detection was by UV at 280 nm and the column was maintained at 40 degrees C. Retention times varied by <1% throughout the day and were as follows: G, 13.0 min; M1, 12.2 min; M2, 11.2 min; M3, 10.8 min, and 18.1 min for a pyrene conjugate of G (G-P). The limit of detection on column (LOD) was 2.5 ng for antagonist G, M1-3 and G-P and the limit of quantitation (LOQ) was 20 ng/ml for G and 100 ng/ml for M1-3. Sample clean-up by solid-phase extraction using C2-bonded 40 microm silica particles (Bond Elut, 1 ml reservoirs) resulted in elimination of interference from plasma constituents. Within-day and between-day precision and accuracy over a broad range of concentrations (100 ng/ml-100 microg/ml) normally varied by < 10%, although at the highest concentrations of M1 and M2 studied (50 microg/ml), increased variability and reduced recovery were observed. The new assay will aid in the clinical development of antagonist G.
Sun, Wenjuan; Hu, Xiaolong; Liu, Jia; Zhang, Yurong; Lu, Jianzhong; Zeng, Libo
2017-10-01
In this study, the multi-walled carbon nanotubes (MWCNTs) were applied in lateral flow strips (LFS) for semi-quantitative and quantitative assays. Firstly, the solubility of MWCNTs was improved using various surfactants to enhance their biocompatibility for practical application. The dispersed MWCNTs were conjugated with the methamphetamine (MET) antibody in a non-covalent manner and then manufactured into the LFS for the quantitative detection of MET. The MWCNTs-based lateral flow assay (MWCNTs-LFA) exhibited an excellent linear relationship between the values of test line and MET when its concentration ranges from 62.5 to 1500 ng/mL. The sensitivity of the LFS was evaluated by conjugating MWCNTs with HCG antibody and the MWCNTs conjugated method is 10 times more sensitive than the one conjugated with classical colloidal gold nanoparticles. Taken together, our data demonstrate that MWCNTs-LFA is a more sensitive and reliable assay for semi-quantitative and quantitative detection which can be used in forensic analysis.
Lin, Yanna; Dai, Yuxue; Sun, Yuanling; Ding, Chaofan; Sun, Weiyan; Zhu, Xiaodong; Liu, Hao; Luo, Chuannan
2018-05-15
In this work, HKUST-1 and QDs-luminol-aptamer conjugates were prepared. The QDs-luminol-aptamer conjugates can be adsorbed by graphene oxide through π-π conjugation. When the adenosine was added, the QDs-luminol-aptamer conjugates were released from magnetic graphene oxide (MGO), the chemiluminescent switch was turned on. It was reported that HKUST-1 can catalyze the chemiluminescence reaction of luminol-H 2 O 2 system in an alkaline medium, and improve the chemiluminescence resonance energy transfer (CRET) between chemiluminescence and QDs indirectly. Thus, the adenosine can be detected sensitively. Based on this phenomenon, the excellent platform for detection of adenosine was established. Under the optimized conditions, the linear detection range for adenosine was 1.0 × 10 -12 -2.2 × 10 -10 mol/L with a detection limit of 2.1 × 10 -13 mol/L. The proposed method was successfully used for adenosine detection in biological samples. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Brandt, Yekaterina I.; Armijo, Leisha M.; Rivera, Antonio C.; Plumley, John B.; Cook, Nathaniel C.; Smolyakov, Gennady A.; Smyth, Hugh D. C.; Osiński, Marek
2013-02-01
Cystic fibrosis (CF) is an inherited childhood-onset life-shortening disease. It is characterized by increased respiratory production, leading to airway obstruction, chronic lung infection and inflammatory reactions. The most common bacteria causing persisting infections in people with CF is Pseudomonas aeruginosa. Superparamagnetic Fe3O4 iron oxide nanoparticles (NPs) conjugated to the antibiotic (tobramycin), guided by a gradient of the magnetic field or subjected to an oscillating magnetic field, show promise in improving the drug delivery across the mucus and P. aeruginosa biofilm to the bacteria. The question remains whether tobramycin needs to be released from the NPs after the penetration of the mucus barrier in order to act upon the pathogenic bacteria. We used a zero-length 1-ethyl-3-[3-dimethylaminopropyl] carbodiimide hydrochloride (EDC) crosslinking agent to couple tobramycin, via its amine groups, to the carboxyl groups on Fe3O4 NPs capped with citric acid. The therapeutic efficiency of Fe3O4 NPs attached to the drug versus that of the free drug was investigated in P. aeruginosa culture.
Quantum dot-polymer conjugates for stable luminescent displays.
Ghimire, Sushant; Sivadas, Anjaly; Yuyama, Ken-Ichi; Takano, Yuta; Francis, Raju; Biju, Vasudevanpillai
2018-05-23
The broad absorption of light in the UV-Vis-NIR region and the size-based tunable photoluminescence color of semiconductor quantum dots make these tiny crystals one of the most attractive antennae in solar cells and phosphors in electrooptical devices. One of the primary requirements for such real-world applications of quantum dots is their stable and uniform distribution in optically transparent matrices. In this work, we prepare transparent thin films of polymer-quantum dot conjugates, where CdSe/ZnS quantum dots are uniformly distributed at high densities in a chitosan-polystyrene copolymer (CS-g-PS) matrix. Here, quantum dots in an aqueous solution are conjugated to the copolymer by a phase transfer reaction. With the stable conjugation of quantum dots to the copolymer, we prevent undesired phase separation between the two and aggregation of quantum dots. Furthermore, the conjugate allows us to prepare transparent thin films in which quantum dots are uniformly distributed at high densities. The CS-g-PS copolymer helps us in not only preserving the photoluminescence properties of quantum dots in the film but also rendering excellent photostability to quantum dots at the ensemble and single particle levels, making the conjugate a promising material for photoluminescence-based devices.
Jenkins, S M; Zvyaga, T; Johnson, S R; Hurley, J; Wagner, A; Burrell, R; Turley, W; Leet, J E; Philip, T; Rodrigues, A D
2011-12-01
In previous studies, gemfibrozil acyl-β-glucuronide, but not gemfibrozil, was found to be a mechanism-based inhibitor of cytochrome P450 2C8. To better understand whether this inhibition is specific for gemfibrozil acyl-β-glucuronide or whether other glucuronide conjugates are potential substrates for inhibition of this enzyme, we evaluated several pharmaceutical compounds (as their acyl glucuronides) as direct-acting and metabolism-dependent inhibitors of CYP2C8 in human liver microsomes. Of 11 compounds that were evaluated as their acyl glucuronide conjugates, only gemfibrozil acyl-β-glucuronide exhibited mechanism-based inhibition, indicating that CYP2C8 mechanism-based inhibition is very specific to certain glucuronide conjugates. Structural analogs of gemfibrozil were synthesized, and their glucuronide conjugates were prepared to further examine the mechanism of inhibition. When the aromatic methyl groups on the gemfibrozil moiety were substituted with trifluoromethyls, the resulting glucuronide conjugate was a weaker inhibitor of CYP2C8 and mechanism-based inhibition was abolished. However, the glucuronide conjugates of monomethyl gemfibrozil analogs were mechanism-based inhibitors of CYP2C8, although not as potent as gemfibrozil acyl-β-glucuronide itself. The ortho-monomethyl analog was a more potent inhibitor than the meta-monomethyl analog, indicating that CYP2C8 favors the ortho position for oxidation and potential inhibition. Molecular modeling of gemfibrozil acyl-β-glucuronide in the CYP2C8 active site is consistent with the ortho-methyl position being the favored site of covalent attachment to the heme. Moreover, hydrogen bonding to four residues (Ser100, Ser103, Gln214, and Asn217) is implicated.
Demonstration of nuclear compartmentalization of glutathione in hepatocytes.
Bellomo, G; Vairetti, M; Stivala, L; Mirabelli, F; Richelmi, P; Orrenius, S
1992-01-01
The intracellular distribution of glutathione (GSH) in cultured hepatocytes has been investigated by using the compound monochlorobimane (BmCl), which interacts specifically with GSH to form a highly fluorescent adduct. Image analysis of BmCl-labeled hepatocytes predominantly localized the fluorescence in the nucleus; the nuclear/cytoplasmic concentration gradient was approximately three. This concentration gradient was collapsed by treatment of the cells with ATP-depleting agents. The uneven distribution of BmCl fluorescence was not attributable to (i) nonspecific interaction of BmCl with protein sulfhydryl groups, (ii) any selective nuclear localization of the GSH transferase(s) catalyzing formation of the GSH-BmCl conjugate, or (iii) any apparent alterations in cell morphology from culture conditions, suggesting that this distribution did, indeed, reflect a nuclear compartmentalization of GSH. That the nuclear pool of GSH was found more resistant to depletion by several agents than the cytoplasmic pool supports the assumption that GSH is essential in protecting DNA and other nuclear structures from chemical injury. Images PMID:1584774
Navier-Stokes dynamics on a differential one-form
NASA Astrophysics Data System (ADS)
Story, Troy L.
2006-11-01
After transforming the Navier-Stokes dynamic equation into a characteristic differential one-form on an odd-dimensional differentiable manifold, exterior calculus is used to construct a pair of differential equations and tangent vector(vortex vector) characteristic of Hamiltonian geometry. A solution to the Navier-Stokes dynamic equation is then obtained by solving this pair of equations for the position x^k and the conjugate to the position bk as functions of time. The solution bk is shown to be divergence-free by contracting the differential 3-form corresponding to the divergence of the gradient of the velocity with a triple of tangent vectors, implying constraints on two of the tangent vectors for the system. Analysis of the solution bk shows it is bounded since it remains finite as | x^k | ->,, and is physically reasonable since the square of the gradient of the principal function is bounded. By contracting the characteristic differential one-form with the vortex vector, the Lagrangian is obtained.
The unidirectional motion of two heat-conducting liquids in a flat channel
NASA Astrophysics Data System (ADS)
Andreev, V. K.; Cheremnykh, E. N.
2017-10-01
The unidirectional motion of two viscous incompressible liquids in a flat channel is studied. Liquids contact on a flat interface. External boundaries are fixed solid walls, on which the non-stationary temperature gradients are given. The motion is induced by a joint action of thermogravitational and thermocapillary forces and given total non - stationary fluid flow rate in layers. The corresponding initial boundary value problem is conjugate and inverse because the pressure gradients along axes channel have to be determined together with the velocity and temperature field. For this problem the exact stationary solution is found and a priori estimates of non - stationary solutions are obtained. In Laplace images the solution of the non - stationary problem is found in quadratures. It is proved, that the solution converges to a steady regime with time, if the temperature on the walls and the fluid flow rate are stabilized. The numerical calculations for specific liquid media good agree with the theoretical results.
Ion-exchange chromatography for the characterization of biopharmaceuticals.
Fekete, Szabolcs; Beck, Alain; Veuthey, Jean-Luc; Guillarme, Davy
2015-09-10
Ion-exchange chromatography (IEX) is a historical technique widely used for the detailed characterization of therapeutic proteins and can be considered as a reference and powerful technique for the qualitative and quantitative evaluation of charge heterogeneity. The goal of this review is to provide an overview of theoretical and practical aspects of modern IEX applied for the characterization of therapeutic proteins including monoclonal antibodies (Mabs) and antibody drug conjugates (ADCs). The section on method development describes how to select a suitable stationary phase chemistry and dimensions, the mobile phase conditions (pH, nature and concentration of salt), as well as the temperature and flow rate, considering proteins isoelectric point (pI). In addition, both salt-gradient and pH-gradient approaches were critically reviewed and benefits as well as limitations of these two strategies were provided. Finally, several applications, mostly from pharmaceutical industries, illustrate the potential of IEX for the characterization of charge variants of various types of biopharmaceutical products. Copyright © 2015 Elsevier B.V. All rights reserved.
Hennebicq, Emmanuelle; Deleener, Caroline; Brédas, Jean-Luc; Scholes, Gregory D; Beljonne, David
2006-08-07
The influence of chemical defects and conformational kinks on the nature of the lowest electronic excitations in phenylenevinylene-based polymers is assessed at the semiempirical quantum-chemical level. The amount of excited-state localization and the amplitude of through-space (Coulomb-like) versus through-bond (charge-transfer-like) interactions have been quantified by comparing the results provided by excitonic and supermolecular models. While excitation delocalization among conjugated segments delineated by the defects occurs in the acceptor configuration, self-confinement on individual chromophores follows from geometric relaxation in the excited-state donor configuration. The extent of excited-state localization is found to be sensitive to both the nature of the defect and the length of the conjugated chains. Implications for resonant energy transfer along conjugated polymer chains are discussed.
Acchione, Mauro; Kwon, Hyewon; Jochheim, Claudia M.; Atkins, William M.
2012-01-01
Antibody-drug conjugates (ADCs) with biotin as a model cargo tethered to IgG1 mAbs via different linkers and conjugation methods were prepared and tested for thermostability and ability to bind target antigen and Fc receptor. Most conjugates demonstrated decreased thermostability relative to unconjugated antibody, based on DSC, with carbohydrate and amine coupled ADCs showing the least effect compared with thiol coupled conjugates. A strong correlation between biotin-load and loss of stability is observed with thiol conjugation to one IgG scaffold, but the stability of a second IgG scaffold is relatively insensitive to biotin load. The same correlation for amine coupling was less significant. Binding of antibody to antigen and Fc receptor was investigated using surface plasmon resonance. None of the conjugates exhibited altered antigen affinity. Fc receptor FcγIIb (CD32b) interactions were investigated using captured antibody conjugate. Protein G and Protein A, known inhibitors of Fc receptor (FcR) binding to IgG, were also used to extend the analysis of the impact of conjugation on Fc receptor binding. H10NPEG4 was the only conjugate to show significant negative impact to FcR binding, which is likely due to higher biotin-load compared with the other ADCs. The ADC aHISNLC and aHISTPEG8 demonstrated some loss in affinity for FcR, but to much lower extent. The general insensitivity of target binding and effector function of the IgG1 platform to conjugation highlight their utility. The observed changes in thermostability require consideration for the choice of conjugation chemistry, depending on the system being pursued and particular application of the conjugate. PMID:22531451
Chen, Xingxing; Zhang, Zijian; Ding, Zicheng; Liu, Jun; Wang, Lixiang
2016-08-22
Conjugated polymers are essential for solution-processable organic opto-electronic devices. In contrast to the great efforts on developing new conjugated polymer backbones, research on developing side chains is rare. Herein, we report branched oligo(ethylene glycol) (OEG) as side chains of conjugated polymers. Compared with typical alkyl side chains, branched OEG side chains endowed the resulting conjugated polymers with a smaller π-π stacking distance, higher hole mobility, smaller optical band gap, higher dielectric constant, and larger surface energy. Moreover, the conjugated polymers with branched OEG side chains exhibited outstanding photovoltaic performance in polymer solar cells. A power conversion efficiency of 5.37 % with near-infrared photoresponse was demonstrated and the device performance could be insensitive to the active layer thickness. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Maslennikova, I L; Kuznetsova, M V; Toplak, N; Nekrasova, I V; Žgur Bertok, D; Starčič Erjavec, M
2018-05-07
The efficiency of the bacteriocin, colicin ColE7, bacterial conjugation-based "kill" - "anti-kill" antimicrobial system, was assessed using real-time PCR, flow cytometry and bioluminescence. The ColE7 antimicrobial system consists of the genetically modified Escherichia coli strain Nissle 1917 harbouring a conjugative plasmid (derivative of the F-plasmid) encoding the "kill" gene (ColE7 activity gene) and a chromosomally encoded "anti-kill" gene (ColE7 immunity gene). On the basis of traJ gene expression in the killer donor cells, our results showed that the efficiency of the here studied antimicrobial system against target E. coli was higher at 4 than at 24 h. Flow cytometry was used to indirectly estimate DNase activity of the antimicrobial system, as lysis of target E. coli cells in the conjugative mixture with the killer donor strain led to reduction in cell cytosol fluorescence. According to a lux assay, E. coli TG1 (pXen lux + Ap r ) with constitutive luminescence were killed already after 2 h of treatment. Target sensor E. coli C600 with DNA damage SOS-inducible luminescence showed significantly lower SOS induction 6 and 24 h following treatment with the killer donor strain. Our results thus showed that bioluminescent techniques are quick and suitable for estimation of the ColE7 bacterial conjugation-based antimicrobial system antibacterial activity. Bacterial antimicrobial resistance is worldwide rising and causing deaths of thousands of patients infected with multi-drug resistant bacterial strains. In addition, there is a lack of efficient alternative antimicrobial agents. The significance of our research is the use of a number of methods (real-time PCR, flow cytometry and bioluminescence-based technique) to assess the antibacterial activity of the bacteriocin, colicin ColE7, bacterial conjugation-based "kill" - "anti-kill" antimicrobial system. Bioluminescent techniques proved to be rapid and suitable for estimation of antibacterial activity of ColE7 bacterial conjugation-based antimicrobial system and possibly other related systems. © 2018 The Society for Applied Microbiology.
In vitro evaluation of dendrimer prodrugs for oral drug delivery.
Najlah, Mohammad; Freeman, Sally; Attwood, David; D'Emanuele, Antony
2007-05-04
Dendrimer-based prodrugs were used to enhance the transepithelial permeability of naproxen, a low solubility model drug. The stability of the dendrimer-naproxen link was assessed. Naproxen was conjugated to G0 polyamidoamine (PAMAM) dendrimers either by an amide bond or an ester bond. The stability of G0 prodrugs was evaluated in 80% human plasma and 50% rat liver homogenate. The cytotoxicity of conjugates towards Caco-2 cells was determined and the transport of the conjugates across Caco-2 monolayers (37 degrees C) was reported. In addition, one lauroyl chain (L) was attached to the surface group of G0 PAMAM dendrimer of the diethylene glycol ester conjugate (G0-deg-NAP) to enhance permeability. The lactic ester conjugate, G0-lact-NAP, hydrolyzed slowly in 80% human plasma and in 50% rat liver homogenate (t(1/2)=180 min). G0-deg-NAP was hydrolyzed more rapidly in 80% human plasma (t(1/2)=51 min) and was rapidly cleaved in 50% liver homogenate (t(1/2)=4.7 min). The conjugates were non-toxic when exposed to Caco-2 cells for 3h. Permeability studies showed a significant enhancement in the transport of naproxen when conjugated to dendrimers; L-G0-deg-NAP yielding the highest permeability. Dendrimer-based prodrugs with appropriate linkers have potential as carriers for the oral delivery of low solubility drugs such as naproxen.
Scott, Susana; Altanseseg, Dorjpurev; Sodbayer, Demberelsuren; Nymadawa, Pagvajav; Bulgan, Davaadash; Mendsaikhan, Jamsran; Watt, James P; Slack, Mary P E; Carvalho, Maria G; Hajjeh, Rana; Edmond, Karen M
2013-07-01
Bacterial meningitis is associated with high mortality and long-term complications. This study assessed the impact of Haemophilus influenzae type b (Hib) conjugate vaccine on childhood bacterial meningitis in Ulaanbaatar, Mongolia. Prospective, active, population-based surveillance for suspected meningitis in children aged 2-59 months was conducted (February 2002-January 2011) in 6 hospitals. Clinical data, blood, and cerebrospinal fluid were collected. The impact of Hib conjugate vaccine was assessed by comparing Hib and all cause meningitis data in the 3 years preceding pentavalent conjugate vaccine implementation (2002-2004) with 3 years postimplementation (2008-2010). Five hundred eleven cases of suspected meningitis were identified from 2002-2011. Pentavalent conjugate vaccine coverage in December 2005 in Ulaanbaatar city was 97%. The proportion of suspected cases confirmed as Hib meningitis decreased from 25% (50/201) in the prevaccination era to 2% (4/193) in the postvaccination era (P < .0001). The annual incidence of Hib decreased from 28 cases per 100,000 children in 2002-2005 to 2 per 100,000 in 2008-2010 (P < .0001). This article demonstrates the marked impact of Hib conjugate vaccine introduction on meningitis in Mongolia. It is important to sustain this surveillance system to monitor the long-term impact of Hib conjugate vaccine, as well as other interventions such as pneumococcal and meningococcal vaccines. Copyright © 2013. Published by Mosby, Inc.
Gemcitabine-based polymer-drug conjugate for enhanced anticancer effect in colon cancer.
Liang, Tie-Jun; Zhou, Zhong-Mei; Cao, Ying-Qing; Ma, Ming-Ze; Wang, Xiao-Jun; Jing, Kai
2016-11-20
In this study, we have demonstrated gemcitabine (GEM)-conjugated amphiphilic biodegradable polymeric drug carriers. Our aim was to increase the chemotherapeutic potential of GEM in colon cancer by forming a unique polymer-drug conjugates. The polymer-drug conjugate micelles were nanosized with a typical spherical shape. The GEM-conjugated methoxy poly(ethylene glycol)-poly(lactic acid) (GEM-PL) exhibited a controlled release of drug in both the pH conditions. The developed GEM-PL efficiently killed the HT29 cancers cells in a typical time dependent manner. The clonogenic assay further confirmed the superior anticancer effect of GEM-PL which showed least number of colonies. GEM-PL formulation exhibited a significantly higher apoptosis of cancer cells (∼25%) when stained using Annexin-V/PI kit. Conjugation of GEM to the mPEG-PLA significantly enhanced the blood circulation potential in animal model compared to that of free GEM. GEM-PL could prevent quick elimination of the drug and can provide sufficient time for the greater accumulation of GEM at the tumor sites. GEM-PL showed a remarkable tumor regression effect as evident from the lowest tumor volume in HT-29 containing tumor model. Overall, mPEG-PLA/GEM conjugates showed the potential of polymer-based drug targeting and might hold significant clinical potential in the treatment of colon cancers. Copyright © 2016 Elsevier B.V. All rights reserved.
Ma, Heng; Yang, Jun; Liu, Jing; Ge, Lan; An, Jing; Tang, Qing; Li, Han; Zhang, Yu; Chen, David; Wang, Yong; Liu, Jiabin; Liang, Zhigang; Lin, Kai; Jin, Lixin; Bi, Xiaoming; Li, Kuncheng; Li, Debiao
2012-04-15
Myocardial perfusion magnetic resonance imaging (MRI) with sliding-window conjugate-gradient highly constrained back-projection reconstruction (SW-CG-HYPR) allows whole left ventricular coverage, improved temporal and spatial resolution and signal/noise ratio, and reduced cardiac motion-related image artifacts. The accuracy of this technique for detecting coronary artery disease (CAD) has not been determined in a large number of patients. We prospectively evaluated the diagnostic performance of myocardial perfusion MRI with SW-CG-HYPR in patients with suspected CAD. A total of 50 consecutive patients who were scheduled for coronary angiography with suspected CAD underwent myocardial perfusion MRI with SW-CG-HYPR at 3.0 T. The perfusion defects were interpreted qualitatively by 2 blinded observers and were correlated with x-ray angiographic stenoses ≥50%. The prevalence of CAD was 56%. In the per-patient analysis, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of SW-CG-HYPR was 96% (95% confidence interval 82% to 100%), 82% (95% confidence interval 60% to 95%), 87% (95% confidence interval 70% to 96%), 95% (95% confidence interval 74% to100%), and 90% (95% confidence interval 82% to 98%), respectively. In the per-vessel analysis, the corresponding values were 98% (95% confidence interval 91% to 100%), 89% (95% confidence interval 80% to 94%), 86% (95% confidence interval 76% to 93%), 99% (95% confidence interval 93% to 100%), and 93% (95% confidence interval 89% to 97%), respectively. In conclusion, myocardial perfusion MRI using SW-CG-HYPR allows whole left ventricular coverage and high resolution and has high diagnostic accuracy in patients with suspected CAD. Copyright © 2012 Elsevier Inc. All rights reserved.
Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.
Gilles, Luc; Ellerbroek, Brent L; Vogel, Curtis R
2003-09-10
Multiconjugate adaptive optics (MCAO) systems with 10(4)-10(5) degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 10(4) actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10(-2) Hz, i.e., 4-5 orders of magnitude lower than the typical 10(3) Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.
A nonrecursive order N preconditioned conjugate gradient: Range space formulation of MDOF dynamics
NASA Technical Reports Server (NTRS)
Kurdila, Andrew J.
1990-01-01
While excellent progress has been made in deriving algorithms that are efficient for certain combinations of system topologies and concurrent multiprocessing hardware, several issues must be resolved to incorporate transient simulation in the control design process for large space structures. Specifically, strategies must be developed that are applicable to systems with numerous degrees of freedom. In addition, the algorithms must have a growth potential in that they must also be amenable to implementation on forthcoming parallel system architectures. For mechanical system simulation, this fact implies that algorithms are required that induce parallelism on a fine scale, suitable for the emerging class of highly parallel processors; and transient simulation methods must be automatically load balancing for a wider collection of system topologies and hardware configurations. These problems are addressed by employing a combination range space/preconditioned conjugate gradient formulation of multi-degree-of-freedom dynamics. The method described has several advantages. In a sequential computing environment, the method has the features that: by employing regular ordering of the system connectivity graph, an extremely efficient preconditioner can be derived from the 'range space metric', as opposed to the system coefficient matrix; because of the effectiveness of the preconditioner, preliminary studies indicate that the method can achieve performance rates that depend linearly upon the number of substructures, hence the title 'Order N'; and the method is non-assembling. Furthermore, the approach is promising as a potential parallel processing algorithm in that the method exhibits a fine parallel granularity suitable for a wide collection of combinations of physical system topologies/computer architectures; and the method is easily load balanced among processors, and does not rely upon system topology to induce parallelism.
Multigrid Methods for the Computation of Propagators in Gauge Fields
NASA Astrophysics Data System (ADS)
Kalkreuter, Thomas
Multigrid methods were invented for the solution of discretized partial differential equations in order to overcome the slowness of traditional algorithms by updates on various length scales. In the present work generalizations of multigrid methods for propagators in gauge fields are investigated. Gauge fields are incorporated in algorithms in a covariant way. The kernel C of the restriction operator which averages from one grid to the next coarser grid is defined by projection on the ground-state of a local Hamiltonian. The idea behind this definition is that the appropriate notion of smoothness depends on the dynamics. The ground-state projection choice of C can be used in arbitrary dimension and for arbitrary gauge group. We discuss proper averaging operations for bosons and for staggered fermions. The kernels C can also be used in multigrid Monte Carlo simulations, and for the definition of block spins and blocked gauge fields in Monte Carlo renormalization group studies. Actual numerical computations are performed in four-dimensional SU(2) gauge fields. We prove that our proposals for block spins are “good”, using renormalization group arguments. A central result is that the multigrid method works in arbitrarily disordered gauge fields, in principle. It is proved that computations of propagators in gauge fields without critical slowing down are possible when one uses an ideal interpolation kernel. Unfortunately, the idealized algorithm is not practical, but it was important to answer questions of principle. Practical methods are able to outperform the conjugate gradient algorithm in case of bosons. The case of staggered fermions is harder. Multigrid methods give considerable speed-ups compared to conventional relaxation algorithms, but on lattices up to 184 conjugate gradient is superior.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dul, F.A.; Arczewski, K.
1994-03-01
Although it has been stated that [open quotes]an attempt to solve (very large problems) by subspace iterations seems futile[close quotes], we will show that the statement is not true, especially for extremely large eigenproblems. In this paper a new two-phase subspace iteration/Rayleigh quotient/conjugate gradient method for generalized, large, symmetric eigenproblems Ax = [lambda]Bx is presented. It has the ability of solving extremely large eigenproblems, N = 216,000, for example, and finding a large number of leftmost or rightmost eigenpairs, up to 1000 or more. Multiple eigenpairs, even those with multiplicity 100, can be easily found. The use of the proposedmore » method for solving the big full eigenproblems (N [approximately] 10[sup 3]), as well as for large weakly non-symmetric eigenproblems, have been considered also. The proposed method is fully iterative; thus the factorization of matrices ins avoided. The key idea consists in joining two methods: subspace and Rayleigh quotient iterations. The systems of indefinite and almost singular linear equations (a - [sigma]B)x = By are solved by various iterative conjugate gradient method can be used without danger of breaking down due to its property that may be called [open quotes]self-correction towards the eigenvector,[close quotes] discovered recently by us. The use of various preconditioners (SSOR and IC) has also been considered. The main features of the proposed method have been analyzed in detail. Comparisons with other methods, such as, accelerated subspace iteration, Lanczos, Davidson, TLIME, TRACMN, and SRQMCG, are presented. The results of numerical tests for various physical problems (acoustic, vibrations of structures, quantum chemistry) are presented as well. 40 refs., 12 figs., 2 tabs.« less
Functionalization of quantum rods with oligonucleotides for programmable assembly with DNA origami
NASA Astrophysics Data System (ADS)
Doane, Tennyson L.; Alam, Rabeka; Maye, Mathew M.
2015-02-01
The DNA-mediated self-assembly of CdSe/CdS quantum rods (QRs) onto DNA origami is described. Two QR types with unique optical emission and high polarization were synthesized, and then functionalized with oligonucleotides (ssDNA) using a novel protection-deprotection approach, which harnessed ssDNA's tailorable rigidity and denaturation temperature to increase DNA coverage by reducing non-specific coordination and wrapping. The QR assembly was programmable, and occurred at two different assembly zones that had capture strands in parallel alignment. QRs with different optical properties were assembled, opening up future studies on orientation dependent QR FRET. The QR-origami conjugates could be purified via gel electrophoresis and sucrose gradient ultracentrifugation. Assembly yields, QR stoichiometry and orientation, as well as energy transfer implications were studied in light of QR distances, origami flexibility, and conditions.The DNA-mediated self-assembly of CdSe/CdS quantum rods (QRs) onto DNA origami is described. Two QR types with unique optical emission and high polarization were synthesized, and then functionalized with oligonucleotides (ssDNA) using a novel protection-deprotection approach, which harnessed ssDNA's tailorable rigidity and denaturation temperature to increase DNA coverage by reducing non-specific coordination and wrapping. The QR assembly was programmable, and occurred at two different assembly zones that had capture strands in parallel alignment. QRs with different optical properties were assembled, opening up future studies on orientation dependent QR FRET. The QR-origami conjugates could be purified via gel electrophoresis and sucrose gradient ultracentrifugation. Assembly yields, QR stoichiometry and orientation, as well as energy transfer implications were studied in light of QR distances, origami flexibility, and conditions. Electronic supplementary information (ESI) available: Experimental conditions, DNA origami blueprint and sequences, FRET calculations. Additional Fig. S1-S13. See DOI: 10.1039/c4nr07662a
Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I
2017-01-01
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.
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.
Xu, Yaolin; Baiu, Dana C.; Sherwood, Jennifer A.; McElreath, Meghan R.; Qin, Ying; Lackey, Kimberly H.; Otto, Mario; Bao, Yuping
2015-01-01
Specific targeting is a key step to realize the full potential of iron oxide nanoparticles in biomedical applications, especially tumor-associated diagnosis and therapy. Here, we developed anti-GD2 antibody conjugated iron oxide nanoparticles for highly efficient neuroblastoma cell targeting. The antibody conjugation was achieved through an easy, linker-free method based on catechol reactions. The targeting efficiency and specificity of the antibody-conjugated nanoparticles to GD2-positive neuroblastoma cells were confirmed by flow cytometry, fluorescence microscopy, Prussian blue staining and transmission electron microscopy. These detailed studies indicated that the receptor-recognition capability of the antibody was fully retained after conjugation and the conjugated nanoparticles quickly attached to GD2-positive cells within four hours. Interestingly, longer treatment (12 h) led the cell membrane-bound nanoparticles to be internalized into cytosol, either by directly penetrating the cell membrane or escaping from the endosomes. Last but importantly, the uniquely designed functional surfaces of the nanoparticles allow easy conjugation of other bioactive molecules. PMID:26660881
Counter-extrapolation method for conjugate interfaces in computational heat and mass transfer.
Le, Guigao; Oulaid, Othmane; Zhang, Junfeng
2015-03-01
In this paper a conjugate interface method is developed by performing extrapolations along the normal direction. Compared to other existing conjugate models, our method has several technical advantages, including the simple and straightforward algorithm, accurate representation of the interface geometry, applicability to any interface-lattice relative orientation, and availability of the normal gradient. The model is validated by simulating the steady and unsteady convection-diffusion system with a flat interface and the steady diffusion system with a circular interface, and good agreement is observed when comparing the lattice Boltzmann results with respective analytical solutions. A more general system with unsteady convection-diffusion process and a curved interface, i.e., the cooling process of a hot cylinder in a cold flow, is also simulated as an example to illustrate the practical usefulness of our model, and the effects of the cylinder heat capacity and thermal diffusivity on the cooling process are examined. Results show that the cylinder with a larger heat capacity can release more heat energy into the fluid and the cylinder temperature cools down slower, while the enhanced heat conduction inside the cylinder can facilitate the cooling process of the system. Although these findings appear obvious from physical principles, the confirming results demonstrates the application potential of our method in more complex systems. In addition, the basic idea and algorithm of the counter-extrapolation procedure presented here can be readily extended to other lattice Boltzmann models and even other computational technologies for heat and mass transfer systems.
Zhu, Xiali; Huang, Heqing; Zhang, Yingjie; Xie, Yingxia; Hou, Lin; Zhang, Huijuan; Zhang, Zhenzhong
2015-01-01
Single-walled carbon nanotubes (SWNT) have been widely explored as carriers for drug delivery because of their large surface area, high near-infrared absorption coefficient and facile transport through cellular membranes. In this study, Lysine (Lys) modified SWNT-liposomes conjugate loaded with doxorubicin (DOX) was designed to enhance the targeted drug delivery and antitumor effect. The conjugate (DOX-Lys/SWNT-Lip) was prepared with pH gradient methods, and the mean particle size and drug entrapment efficiency were 223±5.9 nm and 85.9 %, respectively. In vitro drug release study showed that DOX released much slowly from DOX-Lys/SWNT-Lip than from DOX solution, but faster than that of DOX-Lys/SWNT. DOX-Lys/SWNT-Lip could efficiently cross the cell membrane and afford higher anti-tumor efficacy on MCF-7 cells in vitro. For in vivo experiment, normal saline (N.S.), and DOX or DOX-Lys/SWNTLip were given to the S180 tumor bearing mice by i.v. administration, and followed by exposing the tumor site to nearinfrared laser (NIR) irradiation at 808 nm for 2 min. The relative tumor volumes in DOX-Lys/SWNT-Lip group and DOX group were obviously smaller than those of N.S. group. When combined with NIR laser irradiation, the suppression on tumor growth was much stronger. In conclusion, this study may provide potentially viable clinical strategies for tumor treatment with chemotherapy and photothermal therapy dual-mechanism.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Haifeng; Zhou, Guangjun, E-mail: gjzhou@sdu.edu.cn; Zhou, Juan
2015-05-15
Highlights: • QDs with variety morphology were obtained via an injection controlled process. • 3-D PL spectra of core–shell QDs show different excitation wavelength dependence. • The PL intensity of QDs with ZnSe transition layer increases dramatically. • Core–shell QDs were processed into aqueous phase and conjugated with E. coli O-157. - Abstract: Wide emission-tunable and different morphological alloyed CdTeSe quantum dots (QDs), CdTeSe/ZnS and CdTeSe/ZnSe/ZnS core–shell QDs were successfully synthesized via an injection controlled process. The effect of injection procedure and reaction temperature were systematically discussed and the growth mechanism was proposed. Most efficient PL wavelength was correlated withmore » reaction time and temperature. The 3-D PL spectra of spherical bare CdTeSe and core–shell QDs with different passivation showed different excitation wavelength dependency. The PL intensity of CdTeSe/ZnSe/ZnS core–shell QDs increased greatly in comparison with that of CdTeSe and CdTeSe/ZnSe QDs. ZnSe transition layer played an important role in improving the PL intensity by providing a smoothened interface and gradient band offsets. The core–shell QDs were transferred into aqueous phase and successfully conjugated with Escherichia coli O-157. The proposed phase-transfer and bio-labeling strategy may be applicable to various QDs with different compositions.« less
Mukaisho, Ken-ichi; Hagiwara, Tadashi; Nakayama, Takahisa; Hattori, Takanori; Sugihara, Hiroyuki
2014-09-14
The long-term use of proton pump inhibitors (PPIs) exacerbates corpus atrophic gastritis in patients with Helicobacter pylori (H. pylori) infection. To identify a potential mechanism for this change, we discuss interactions between pH, bile acids, and H. pylori. Duodenogastric reflux, which includes bile, occurs in healthy individuals, and bile reflux is increased in patients with gastroesophageal reflux disease (GERD). Diluted human plasma and bile acids have been found to be significant chemoattractants and chemorepellents, respectively, for the bacillus H. pylori. Although only taurine conjugates, with a pKa of 1.8-1.9, are soluble in an acidic environment, glycine conjugates, with a pKa of 4.3-5.2, as well as taurine-conjugated bile acids are soluble in the presence of PPI therapy. Thus, the soluble bile acid concentrations in the gastric contents of patients with GERD after continuous PPI therapy are considerably higher than that in those with intact acid production. In the distal stomach, the high concentration of soluble bile acids is likely to act as a bactericide or chemorepellent for H. pylori. In contrast, the mucous layer in the proximal stomach has an optimal bile concentration that forms chemotactic gradients with plasma components required to direct H. pylori to the epithelial surface. H. pylori may then colonize in the stomach body rather than in the pyloric antrum, which may explain the occurrence of corpus-predominant gastritis after PPI therapy in H. pylori-positive patients with GERD.
NASA Astrophysics Data System (ADS)
Kandel, Prakash K.; Fernando, Lawrence P.; Ackroyd, P. Christine; Christensen, Kenneth A.
2011-03-01
We report a simple and rapid method to prepare extremely bright, functionalized, stable, and biocompatible conjugated polymer nanoparticles incorporating functionalized polyethylene glycol (PEG) lipids by reprecipitation. These nanoparticles retain the fundamental spectroscopic properties of conjugated polymer nanoparticles prepared without PEG lipid, but demonstrate greater hydrophilicity and quantum yield compared to unmodified conjugated polymer nanoparticles. The sizes of these nanoparticles, as determined by TEM, were 21-26 nm. Notably, these nanoparticles were prepared with several PEG lipid functional end groups, including biotin and carboxy moieties that can be easily conjugated to biomolecules. We have demonstrated the availability of these end groups for functionalization using the interaction of biotin PEG lipid conjugated polymer nanoparticles with streptavidin. Biotinylated PEG lipid conjugated polymer nanoparticles bound streptavidin-linked magnetic beads, while carboxy and methoxy PEG lipid modified nanoparticles did not. Similarly, biotinylated PEG lipid conjugated polymer nanoparticles bound streptavidin-coated glass slides and could be visualized as diffraction-limited spots, while nanoparticles without PEG lipid or with non-biotin PEG lipid end groups were not bound. To demonstrate that nanoparticle functionalization could be used for targeted labelling of specific cellular proteins, biotinylated PEG lipid conjugated polymer nanoparticles were bound to biotinylated anti-CD16/32 antibodies on J774A.1 cell surface receptors, using streptavidin as a linker. This work represents the first demonstration of targeted delivery of conjugated polymer nanoparticles and demonstrates the utility of these new nanoparticles for fluorescence based imaging and sensing.We report a simple and rapid method to prepare extremely bright, functionalized, stable, and biocompatible conjugated polymer nanoparticles incorporating functionalized polyethylene glycol (PEG) lipids by reprecipitation. These nanoparticles retain the fundamental spectroscopic properties of conjugated polymer nanoparticles prepared without PEG lipid, but demonstrate greater hydrophilicity and quantum yield compared to unmodified conjugated polymer nanoparticles. The sizes of these nanoparticles, as determined by TEM, were 21-26 nm. Notably, these nanoparticles were prepared with several PEG lipid functional end groups, including biotin and carboxy moieties that can be easily conjugated to biomolecules. We have demonstrated the availability of these end groups for functionalization using the interaction of biotin PEG lipid conjugated polymer nanoparticles with streptavidin. Biotinylated PEG lipid conjugated polymer nanoparticles bound streptavidin-linked magnetic beads, while carboxy and methoxy PEG lipid modified nanoparticles did not. Similarly, biotinylated PEG lipid conjugated polymer nanoparticles bound streptavidin-coated glass slides and could be visualized as diffraction-limited spots, while nanoparticles without PEG lipid or with non-biotin PEG lipid end groups were not bound. To demonstrate that nanoparticle functionalization could be used for targeted labelling of specific cellular proteins, biotinylated PEG lipid conjugated polymer nanoparticles were bound to biotinylated anti-CD16/32 antibodies on J774A.1 cell surface receptors, using streptavidin as a linker. This work represents the first demonstration of targeted delivery of conjugated polymer nanoparticles and demonstrates the utility of these new nanoparticles for fluorescence based imaging and sensing. Electronic supplementary information (ESI) available: Additional TEM data, supplemental light scattering measurements, absorbance and fluorescence emission spectra, and photostability measurements. See DOI: 10.1039/c0nr00746c
Functional Hybrid Biomaterials based on Peptide-Polymer Conjugates for Nanomedicine
NASA Astrophysics Data System (ADS)
Shu, Jessica Yo
The focus of this dissertation is the design, synthesis and characterization of hybrid functional biomaterials based on peptide-polymer conjugates for nanomedicine. Generating synthetic materials with properties comparable to or superior than those found in nature has been a "holy grail" for the materials community. Man-made materials are still rather simplistic when compared to the chemical and structural complexity of a cell. Peptide-polymer conjugates have the potential to combine the advantages of the biological and synthetic worlds---that is they can combine the precise chemical structure and diverse functionality of biomolecules with the stability and processibility of synthetic polymers. As a new family of soft matter, they may lead to materials with novel properties that have yet to be realized with either of the components alone. In order for peptide-polymer conjugates to reach their full potential as useful materials, the structure and function of the peptide should be maintained upon polymer conjugation. The success in achieving desirable, functional assemblies relies on fundamentally understanding the interactions between each building block and delicately balancing and manipulating these interactions to achieve targeted assemblies without interfering with designed structures and functionalities. Such fundamental studies of peptide-polymer interactions were investigated as the nature of the polymer (hydrophilic vs. hydrophobic) and the site of its conjugation (end-conjugation vs. side-conjugation) were varied. The fundamental knowledge gained was then applied to the design of amphiphiles that self-assemble to form stable functional micelles. The micelles exhibited exceptional monodispersity and long-term stability, which is atypical of self-assembled systems. Thus such micelles based on amphiphilic peptide-polymer conjugates may meet many current demands in nanomedicine, in particular for drug delivery of hydrophobic anti-cancer therapeutics. Lastly, biological evaluations were performed to investigate the potential of micelles as drug delivery vehicles. In vitro cell studies demonstrated that the micelles can be used as a delivery vehicle to tailor the cellular uptake, time release, and intracellular trafficking of drugs. In vivo biodistribution and pharmacokinetic experiments showed long blood circulation. This work demonstrates that peptide-polymer conjugates can be used as building blocks to generate hierarchical functional nanostructures with a wide range of applications, only one of which is drug delivery.
Bechler, Shane L; Lynn, David M
2012-05-14
We report on conjugate addition-based approaches to the covalent layer-by-layer assembly of thin films and the post-fabrication functionalization of biointerfaces. Our approach is based on a recently reported approach to the "reactive" assembly of covalently cross-linked polymer multilayers driven by the 1,4-conjugate addition of amine functionality in poly(ethyleneimine) (PEI) to the acrylate groups in a small-molecule pentacrylate species (5-Ac). This process results in films containing degradable β-amino ester cross-links and residual acrylate and amine functionality that can be used as reactive handles for the subsequent immobilization of new functionality. Layer-by-layer growth of films fabricated on silicon substrates occurred in a supra-linear manner to yield films ≈ 750 nm thick after the deposition of 80 PEI/5-Ac layers. Characterization by atomic force microscopy (AFM) suggested a mechanism of growth that involves the reactive deposition of nanometer-scale aggregates of PEI and 5-Ac during assembly. Infrared (IR) spectroscopy studies revealed covalent assembly to occur by 1,4-conjugate addition without formation of amide functionality. Additional experiments demonstrated that acrylate-containing films could be postfunctionalized via conjugate addition reactions with small-molecule amines that influence important biointerfacial properties, including water contact angles and the ability of film-coated surfaces to prevent or promote the attachment of cells in vitro. For example, whereas conjugation of the hydrophobic molecule decylamine resulted in films that supported cell adhesion and growth, films treated with the carbohydrate-based motif D-glucamine resisted cell attachment and growth almost completely for up to 7 days in serum-containing media. We demonstrate that this conjugate addition-based approach also provides a means of immobilizing functionality through labile ester linkages that can be used to promote the long-term, surface-mediated release of conjugated species and promote gradual changes in interfacial properties upon incubation in physiological media (e.g., over a period of at least 1 month). These covalently cross-linked films are relatively stable in biological media for prolonged periods, but they begin to physically disintegrate after ≈ 30 days, suggesting opportunities to use this covalent layer-by-layer approach to design functional biointerfaces that ultimately erode or degrade to facilitate elimination.
NASA Astrophysics Data System (ADS)
Yuan, Zhigang; Qiao, Zheng; Li, Haimeng; Huang, Shiyong; Wang, Dedong; Yu, Xiongdong; Yu, Tao
2017-04-01
Subauroral polarization stream (SAPS) electric field can play an important role in the coupling between the inner magnetosphere and ionosphere; however, the production mechanism of SAPS has not been yet solved. During an energetic ion injection event on 26 March 2004, at latitudes lower than the equatorward boundaries of precipitating plasma sheet electrons and ions, the Defense Meteorological Satellite Program (DMSP) F13 satellite simultaneously observed a strong SAPS with the peak velocity of 1294 m/s and downward flowing field-aligned currents (FACs). Conjugate observations of DMSP F13 and NOAA 15 satellites have shown that FACs flowing into the ionosphere just lie in the outer boundary of the ring current (RC). The downward flowing FACs were observed in a region of positive latitudinal gradients of the ion energy density, implying that the downward flowing FACs are more likely linked to the azimuthal gradient than the radial gradient of the RC ion pressure. Our result demonstrates that RC ion pressure gradients on the outer boundary of the RC in the evening sector during energetic ion injection events can lead to downward flowing FACs so as to cause strong SAPS in condition of low ionospheric conductivities.
Development of solid - based paper strips for rapid diagnosis of Pseudorabies infection.
Joon Tam, Yew; Mohd Lila, Mohd Azmi; Bahaman, Abdul Rani
2004-12-01
Pseudorabies (Aujeszky's disease) is an economically significant disease of swine known to cause central nervous disorders, respiratory disease, reproductive failure and mortality in infected pigs. In attempts to eradicate the disease from becoming endemic, early detection is important to prevent further economic losses and to allow for detection and removal of infected pigs in domestic herds. Thus, a rapid and sensitive technique is necessary for the detection of the virus. For rapid and simple examination, an immuno - chromatographic lateral - flow assay system based on immunologic recognition of specific pseudorabies virus antigen was developed by utilising, as signal generator, colloidal gold conjugated to secondary antibody to detect primary or sample antibody in the sera of pseudorabies infected animals. The pseudorabies virus used as a capture antigen in the test strip was first cultivated in VERO cell culture and then purified by sucrose gradient separation to produce the viral protein concentration of 3.8 mg/ml. The standard pseudorabies antigens reacted well with the hyperimmune serum (HIS). The antibody detection system is basically composed of colloidal gold - labelled antibodies fixed on a conjugate pad, and the complementary pseudorabies antigen immobilised onto a nitrocellulose membrane forming capture zone. If the target antibody is present in a specimen, the colloidal gold-labelled antibody will form a complex with the antibody sample. Subsequently, the formed complex will migrate to the capture zone and is then bound to the solid phase via antigen - antibody interaction. As a result, a signal marker is generated by the accumulation of colloidal gold for detection confirmation. The results obtained demonstrated that the optimum combination of pseudorabies antigen needed as the capture reagent and gold conjugate as secondary antibody recognition marker was at a concentration of 0.38mg/ml and at 1:10 dilution factor respectively. The sensitivity of the solid - based test strip towards pseudorabies antibodies was high with a detection limit of 1 to 10,000 - dilution factor. The specificity of the assay was 100% with no cross - reaction being observed with other sera or antibodies. Accurate reading time needed for confirmation of the assay can be completed in 5 min with a whole blood sample of 25 microl. The colloidal gold - labelled antibody is stable at room temperature for 6 months or more (data not shown). Findings from this study indicated that the solid - based test strip assay system provided high sensitivity and specificity for the detection of pseudorabies at low levels of antibody concentration. The assay was rapid, simple, cheap, and does not require any sophisticated equipment. Thus, the solid based test strip will be a useful serological screening technique or for rapid diagnosis of an infectious disease in target populations of animals characterised by heterogeneous antibody responses.
Dehydration Polymerization for Poly(hetero)arene Conjugated Polymers.
Mirabal, Rafael A; Vanderzwet, Luke; Abuadas, Sara; Emmett, Michael R; Schipper, Derek
2018-02-18
The lack of scalable and sustainable methods to prepare conjugated polymers belies their importance in many enabling technologies. Accessing high-performance poly(hetero)arene conjugated polymers by dehydration has remained an unsolved problem in synthetic chemistry and has historically required transitional-metal coupling reactions. Herein, we report a dehydration method that allows access to conjugated heterocyclic materials. By using the technique, we have prepared a series of small molecules and polymers. The reaction avoids using transition metals, proceeds at room temperature, the only required reactant is a simple base and water is the sole by-product. The dehydration reaction is technically simple and provides a sustainable and straightforward method to prepare conjugated heteroarene motifs. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Silica nanoparticle-based dual imaging colloidal hybrids: cancer cell imaging and biodistribution
Lee, Haisung; Sung, Dongkyung; Kim, Jinhoon; Kim, Byung-Tae; Wang, Tuntun; An, Seong Soo A; Seo, Soo-Won; Yi, Dong Kee
2015-01-01
In this study, fluorescent dye-conjugated magnetic resonance (MR) imaging agents were investigated in T mode. Gadolinium-conjugated silica nanoparticles were successfully synthesized for both MR imaging and fluorescence diagnostics. Polyamine and polycarboxyl functional groups were modified chemically on the surface of the silica nanoparticles for efficient conjugation of gadolinium ions. The derived gadolinium-conjugated silica nanoparticles were investigated by zeta potential analysis, transmission electron microscopy, inductively coupled plasma mass spectrometry, and energy dispersive x-ray spectroscopy. MR equipment was used to investigate their use as contrast-enhancing agents in T1 mode under a 9.4 T magnetic field. In addition, we tracked the distribution of the gadolinium-conjugated nanoparticles in both lung cancer cells and organs in mice. PMID:26357472
NASA Astrophysics Data System (ADS)
Guo, Jia; Xu, Yanhong; Jin, Shangbin; Chen, Long; Kaji, Toshihiko; Honsho, Yoshihito; Addicoat, Matthew A.; Kim, Jangbae; Saeki, Akinori; Ihee, Hyotcherl; Seki, Shu; Irle, Stephan; Hiramoto, Masahiro; Gao, Jia; Jiang, Donglin
2013-11-01
Covalent organic frameworks are a class of crystalline organic porous materials that can utilize π-π-stacking interactions as a driving force for the crystallization of polygonal sheets to form layered frameworks and ordered pores. However, typical examples are chemically unstable and lack intrasheet π-conjugation, thereby significantly limiting their applications. Here we report a chemically stable, electronically conjugated organic framework with topologically designed wire frameworks and open nanochannels, in which the π conjugation-spans the two-dimensional sheets. Our framework permits inborn periodic ordering of conjugated chains in all three dimensions and exhibits a striking combination of properties: chemical stability, extended π-delocalization, ability to host guest molecules and hole mobility. We show that the π-conjugated organic framework is useful for high on-off ratio photoswitches and photovoltaic cells. Therefore, this strategy may constitute a step towards realizing ordered semiconducting porous materials for innovations based on two-dimensionally extended π systems.
Biomarker-specific conjugated nanopolyplexes for the active coloring of stem-like cancer cells
NASA Astrophysics Data System (ADS)
Hong, Yoochan; Lee, Eugene; Choi, Jihye; Haam, Seungjoo; Suh, Jin-Suck; Yang, Jaemoon
2016-06-01
Stem-like cancer cells possess intrinsic features and their CD44 regulate redox balance in cancer cells to survive under stress conditions. Thus, we have fabricated biomarker-specific conjugated polyplexes using CD44-targetable hyaluronic acid and redox-sensible polyaniline based on a nanoemulsion method. For the most sensitive recognition of the cellular redox at a single nanoparticle scale, a nano-scattering spectrum imaging analyzer system was introduced. The conjugated polyplexes showed a specific targeting ability toward CD44-expressing cancer cells as well as a dramatic change in its color, which depended on the redox potential in the light-scattered images. Therefore, these polyaniline-based conjugated polyplexes as well as analytical processes that include light-scattering imaging and measurements of scattering spectra, clearly establish a systematic method for the detection and monitoring of cancer microenvironments.
Sedlacek, Ondrej; Monnery, Bryn D; Mattova, Jana; Kucka, Jan; Panek, Jiri; Janouskova, Olga; Hocherl, Anita; Verbraeken, Bart; Vergaelen, Maarten; Zadinova, Marie; Hoogenboom, Richard; Hruby, Martin
2017-11-01
We designed and synthesized a new delivery system for the anticancer drug doxorubicin based on a biocompatible hydrophilic poly(2-ethyl-2-oxazoline) (PEtOx) carrier with linear architecture and narrow molar mass distribution. The drug is connected to the polymer backbone via an acid-sensitive hydrazone linker, which allows its triggered release in the tumor. The in vitro studies demonstrate successful cellular uptake of conjugates followed by release of the cytostatic cargo. In vivo experiments in EL4 lymphoma bearing mice revealed prolonged blood circulation, increased tumor accumulation and enhanced antitumor efficacy of the PEtOx conjugate having higher molecular weight (40 kDa) compared to the lower molecular weight (20 kDa) polymer. Finally, the in vitro and in vivo anti-cancer properties of the prepared PEtOx conjugates were critically compared with those of the analogous system based on the well-established PHPMA carrier. Despite the relatively slower intracellular uptake of PEtOx conjugates, resulting also in their lower cytotoxicity, there are no substantial differences in in vivo biodistribution and anti-cancer efficacy of both classes of polymer-Dox conjugates. Considering the synthetic advantages of poly(2-alkyl-2-oxazoline)s, the presented study demonstrates their potential as a versatile alternative to well-known PEO- or PHPMA-based materials for construction of drug delivery systems. Copyright © 2017 Elsevier Ltd. All rights reserved.
Borzooeian, Zahra; Taslim, Mohammad E; Ghasemi, Omid; Rezvani, Saina; Borzooeian, Giti; Nourbakhsh, Amirhasan
2018-01-01
Parametric separation of carbon nanotubes, especially based on their length is a challenge for a number of nano-tech researchers. We demonstrate a method to combine bio-conjugation, SDS-PAGE, and silver staining in order to separate carbon nanotubes on the basis of length. Egg-white lysozyme, conjugated covalently onto the single-walled carbon nanotubes surfaces using carbodiimide method. The proposed conjugation of a biomolecule onto the carbon nanotubes surfaces is a novel idea and a significant step forward for creating an indicator for length-based carbon nanotubes separation. The conjugation step was followed by SDS-PAGE and the nanotube fragments were precisely visualized using silver staining. This high precision, inexpensive, rapid and simple separation method obviates the need for centrifugation, additional chemical analyses, and expensive spectroscopic techniques such as Raman spectroscopy to visualize carbon nanotube bands. In this method, we measured the length of nanotubes using different image analysis techniques which is based on a simplified hydrodynamic model. The method has high precision and resolution and is effective in separating the nanotubes by length which would be a valuable quality control tool for the manufacture of carbon nanotubes of specific lengths in bulk quantities. To this end, we were also able to measure the carbon nanotubes of different length, produced from different sonication time intervals.
Gaowa, Arong; Horibe, Tomohisa; Kohno, Masayuki; Tabata, Yasuhiko; Harada, Hiroshi; Hiraoka, Masahiro; Kawakami, Koji
2015-05-01
To improve the anti-tumor activity of EGFR2R-lytic hybrid peptide, we prepared peptide-modified dextran conjugates with the disulfide bonds between thiolated carboxymethyl dextran (CMD-Cys) and cysteine-conjugated peptide (EGFR2R-lytic-Cys). In vitro release studies showed that the peptide was released from the CMD-s-s-peptide conjugate in a concentration-dependent manner in the presence of glutathione (GSH, 2μM-2mM). The CMD-s-s-peptide conjugate exhibited a similar cytotoxic activity with free peptide alone against human pancreatic cancer BxPC-3 cells in vitro. Furthermore, it was shown that the CMD-s-s-peptide conjugates were highly accumulated in tumor tissue in a mouse xenograft model using BxPC-3 cells, and the anti-tumor activity of the conjugate was more effective than that of the free peptide. In addition, the plasma concentrations of peptide were moderately increased and the elimination half-life of the peptide was prolonged after intravenous injection of CMD-s-s-peptide conjugates. These results demonstrated that the conjugate based on thiolated CMD polymer would be potentially useful carriers for the sustained release of the hybrid peptide in vivo. Copyright © 2015 Elsevier B.V. All rights reserved.
Researchers at the National Cancer Institute (NCI) developed novel groups of cyanine (Cy) based antibody-drug conjugate (ADC) chemical linkers that undergo photolytic cleavage upon irradiation with near-IR light. By using the fluorescent properties of the Cy linker to monitor localization of the ADC, and subsequent near-IR irradiation of cancerous tissue, drug release could be confined to the tumor microenvironment.