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

Science.gov (United States)

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.

Extension of Modified Polak-Ribière-Polyak Conjugate Gradient Method to Linear Equality Constraints Minimization Problems

Directory of Open Access Journals (Sweden)

Zhifeng Dai

2014-01-01

Full Text Available Combining the Rosen gradient projection method with the two-term Polak-Ribière-Polyak (PRP conjugate gradient method, we propose a two-term Polak-Ribière-Polyak (PRP conjugate gradient projection method for solving linear equality constraints optimization problems. The proposed method possesses some attractive properties: (1 search direction generated by the proposed method is a feasible descent direction; consequently the generated iterates are feasible points; (2 the sequences of function are decreasing. Under some mild conditions, we show that it is globally convergent with Armijio-type line search. Preliminary numerical results show that the proposed method is promising.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.

Directory of Open Access Journals (Sweden)

Gonglin Yuan

Full Text Available 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.

Stochastic Spectral and Conjugate Descent Methods

KAUST Repository

Kovalev, Dmitry

2018-02-11

The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.

Stochastic Spectral and Conjugate Descent Methods

KAUST Repository

Kovalev, Dmitry; Gorbunov, Eduard; Gasanov, Elnur; Richtarik, Peter

2018-01-01

The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.

Block-conjugate-gradient method

International Nuclear Information System (INIS)

McCarthy, J.F.

1989-01-01

It is shown that by using the block-conjugate-gradient method several, say s, columns of the inverse Kogut-Susskind fermion matrix can be found simultaneously, in less time than it would take to run the standard conjugate-gradient algorithm s times. The method improves in efficiency relative to the standard conjugate-gradient algorithm as the fermion mass is decreased and as the value of the coupling is pushed to its limit before the finite-size effects become important. Thus it is potentially useful for measuring propagators in large lattice-gauge-theory calculations of the particle spectrum

Conjugate descent formulation of backpropagation error in ...

African Journals Online (AJOL)

The feedforward neural network architecture uses backpropagation learning to determine optimal weights between dierent interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to ...

Determination of accelerated factors in gradient descent iterations based on Taylor's series

Directory of Open Access Journals (Sweden)

Petrović Milena

2017-01-01

Full Text Available In this paper the efficiency of accelerated gradient descent methods regarding the way of determination of accelerated factor is considered. Due to the previous researches we assert that the use of Taylor's series of posed gradient descent iteration in calculation of accelerated parameter gives better final results than some other choices. We give a comparative analysis of efficiency of several methods with different approaches in obtaining accelerated parameter. According to the achieved results of numerical experiments we make a conclusion about the one of the most optimal way in defining accelerated parameter in accelerated gradient descent schemes.

Approximate error conjugation gradient minimization methods

Science.gov (United States)

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.

Ionospheric forecasting model using fuzzy logic-based gradient descent method

Directory of Open Access Journals (Sweden)

D. Venkata Ratnam

2017-09-01

Full Text Available Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC. Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E. It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements.

Gradient descent learning algorithm overview: a general dynamical systems perspective.

Science.gov (United States)

Baldi, P

1995-01-01

Gives a unified treatment of gradient descent learning algorithms for neural networks using a general framework of dynamical systems. This general approach organizes and simplifies all the known algorithms and results which have been originally derived for different problems (fixed point/trajectory learning), for different models (discrete/continuous), for different architectures (forward/recurrent), and using different techniques (backpropagation, variational calculus, adjoint methods, etc.). The general approach can also be applied to derive new algorithms. The author then briefly examines some of the complexity issues and limitations intrinsic to gradient descent learning. Throughout the paper, the author focuses on the problem of trajectory learning.

Gradient descent for robust kernel-based regression

Science.gov (United States)

Guo, Zheng-Chu; Hu, Ting; Shi, Lei

2018-06-01

In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Preconditioning the modified conjugate gradient method ...

African Journals Online (AJOL)

In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. And the convergence analysis of the modified conjugate Gradient method was analysed with our extension on preconditioning the algorithm. Convergence of the algorithm is a function of the condition number of M-1A.

Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage

Directory of Open Access Journals (Sweden)

Vahab Akbarzadeh

2014-08-01

Full Text Available We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared.

Nonlinear conjugate gradient methods in micromagnetics

Directory of Open Access Journals (Sweden)

J. Fischbacher

2017-04-01

Full Text Available Conjugate gradient methods for energy minimization in micromagnetics are compared. The comparison of analytic results with numerical simulation shows that standard conjugate gradient method may fail to produce correct results. A method that restricts the step length in the line search is introduced, in order to avoid this problem. When the step length in the line search is controlled, conjugate gradient techniques are a fast and reliable way to compute the hysteresis properties of permanent magnets. The method is applied to investigate demagnetizing effects in NdFe12 based permanent magnets. The reduction of the coercive field by demagnetizing effects is μ0ΔH = 1.4 T at 450 K.

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

Science.gov (United States)

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.

Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent

Directory of Open Access Journals (Sweden)

Ibnkahla Mohamed

2003-01-01

Full Text Available We use natural gradient (NG learning neural networks (NNs for modeling and identifying nonlinear systems with memory. The nonlinear system is comprised of a discrete-time linear filter followed by a zero-memory nonlinearity . The NN model is composed of a linear adaptive filter followed by a two-layer memoryless nonlinear NN. A Kalman filter-based technique and a search-and-converge method have been employed for the NG algorithm. It is shown that the NG descent learning significantly outperforms the ordinary gradient descent and the Levenberg-Marquardt (LM procedure in terms of convergence speed and mean squared error (MSE performance.

Reference-shaping adaptive control by using gradient descent optimizers.

Directory of Open Access Journals (Sweden)

Baris Baykant Alagoz

Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

Conjugate gradient algorithms using multiple recursions

Energy Technology Data Exchange (ETDEWEB)

Barth, T.; Manteuffel, T.

1996-12-31

Much is already known about when a conjugate gradient method can be implemented with short recursions for the direction vectors. The work done in 1984 by Faber and Manteuffel gave necessary and sufficient conditions on the iteration matrix A, in order for a conjugate gradient method to be implemented with a single recursion of a certain form. However, this form does not take into account all possible recursions. This became evident when Jagels and Reichel used an algorithm of Gragg for unitary matrices to demonstrate that the class of matrices for which a practical conjugate gradient algorithm exists can be extended to include unitary and shifted unitary matrices. The implementation uses short double recursions for the direction vectors. This motivates the study of multiple recursion algorithms.

Preconditioned stochastic gradient descent optimisation for monomodal image registration

NARCIS (Netherlands)

Klein, S.; Staring, M.; Andersson, J.P.; Pluim, J.P.W.; Fichtinger, G.; Martel, A.; Peters, T.

2011-01-01

We present a stochastic optimisation method for intensity-based monomodal image registration. The method is based on a Robbins-Monro stochastic gradient descent method with adaptive step size estimation, and adds a preconditioning matrix. The derivation of the pre-conditioner is based on the

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

Science.gov (United States)

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.

Accelerating deep neural network training with inconsistent stochastic gradient descent.

Science.gov (United States)

Wang, Linnan; Yang, Yi; Min, Renqiang; Chakradhar, Srimat

2017-09-01

Stochastic Gradient Descent (SGD) updates Convolutional Neural Network (CNN) with a noisy gradient computed from a random batch, and each batch evenly updates the network once in an epoch. This model applies the same training effort to each batch, but it overlooks the fact that the gradient variance, induced by Sampling Bias and Intrinsic Image Difference, renders different training dynamics on batches. In this paper, we develop a new training strategy for SGD, referred to as Inconsistent Stochastic Gradient Descent (ISGD) to address this problem. The core concept of ISGD is the inconsistent training, which dynamically adjusts the training effort w.r.t the loss. ISGD models the training as a stochastic process that gradually reduces down the mean of batch's loss, and it utilizes a dynamic upper control limit to identify a large loss batch on the fly. ISGD stays on the identified batch to accelerate the training with additional gradient updates, and it also has a constraint to penalize drastic parameter changes. ISGD is straightforward, computationally efficient and without requiring auxiliary memories. A series of empirical evaluations on real world datasets and networks demonstrate the promising performance of inconsistent training. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gradient descent learning in and out of equilibrium

International Nuclear Information System (INIS)

Caticha, Nestor; Araujo de Oliveira, Evaldo

2001-01-01

Relations between the off thermal equilibrium dynamical process of on-line learning and the thermally equilibrated off-line learning are studied for potential gradient descent learning. The approach of Opper to study on-line Bayesian algorithms is used for potential based or maximum likelihood learning. We look at the on-line learning algorithm that best approximates the off-line algorithm in the sense of least Kullback-Leibler information loss. The closest on-line algorithm works by updating the weights along the gradient of an effective potential, which is different from the parent off-line potential. A few examples are analyzed and the origin of the potential annealing is discussed

Minimizing inner product data dependencies in conjugate gradient iteration

Science.gov (United States)

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)).

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

Science.gov (United States)

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)

Efficient spectral computation of the stationary states of rotating Bose-Einstein condensates by preconditioned nonlinear conjugate gradient methods

Science.gov (United States)

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.

Block-Based Gradient Descent for Local Backlight Dimming and Flicker Reduction

DEFF Research Database (Denmark)

Burini, Nino; Mantel, Claire; Nadernejad, Ehsan

2014-01-01

Local backlight dimming technology is a two-fold improvement for LED backlit LCD screens that allows to reduce power consumption and increase visual quality. This paper presents a fast version of an iterative backlight dimming algorithm based on gradient descent search. The speed is increased...

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

Science.gov (United States)

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.

Modified conjugate gradient method for diagonalizing large matrices.

Science.gov (United States)

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.

Parallel conjugate gradient algorithms for manipulator dynamic simulation

Science.gov (United States)

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).

Orderings for conjugate gradient preconditionings

Science.gov (United States)

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.

An Efficient Hybrid Conjugate Gradient Method with the Strong Wolfe-Powell Line Search

Directory of Open Access Journals (Sweden)

Ahmad Alhawarat

2015-01-01

Full Text Available Conjugate gradient (CG method is an interesting tool to solve optimization problems in many fields, such as design, economics, physics, and engineering. In this paper, we depict a new hybrid of CG method which relates to the famous Polak-Ribière-Polyak (PRP formula. It reveals a solution for the PRP case which is not globally convergent with the strong Wolfe-Powell (SWP line search. The new formula possesses the sufficient descent condition and the global convergent properties. In addition, we further explained about the cases where PRP method failed with SWP line search. Furthermore, we provide numerical computations for the new hybrid CG method which is almost better than other related PRP formulas in both the number of iterations and the CPU time under some standard test functions.

New preconditioned conjugate gradient algorithms for nonlinear unconstrained optimization problems

International Nuclear Information System (INIS)

Al-Bayati, A.; Al-Asadi, N.

1997-01-01

This paper presents two new predilection conjugate gradient algorithms for nonlinear unconstrained optimization problems and examines their computational performance. Computational experience shows that the new proposed algorithms generally imp lone the efficiency of Nazareth's [13] preconditioned conjugate gradient algorithm. (authors). 16 refs., 1 tab

Dynamic gradient descent learning algorithms for enhanced empirical modeling of power plants

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, Amir; Chong, K.T.

1991-01-01

A newly developed dynamic gradient descent-based learning algorithm is used to train a recurrent multilayer perceptron network for use in empirical modeling of power plants. The two main advantages of the proposed learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation, instead of one forward and one backward pass of the backpropagation algorithm. The latter advantage results in computational time saving because both passes can be performed simultaneously. The dynamic learning algorithm is used to train a hybrid feedforward/feedback neural network, a recurrent multilayer perceptron, which was previously found to exhibit good interpolation and extrapolation capabilities in modeling nonlinear dynamic systems. One of the drawbacks, however, of the previously reported work has been the long training times associated with accurate empirical models. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm are demonstrated by a case study of a steam power plant. The number of iterations required for accurate empirical modeling has been reduced from tens of thousands to hundreds, thus significantly expediting the learning process

Computational Experience with Globally Convergent Descent Methods for Large Sparse Systems of Nonlinear Equations

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Vlček, Jan

1998-01-01

Roč. 8, č. 3-4 (1998), s. 201-223 ISSN 1055-6788 R&D Projects: GA ČR GA201/96/0918 Keywords : nonlinear equations * Armijo-type descent methods * Newton-like methods * truncated methods * global convergence * nonsymmetric linear systems * conjugate gradient -type methods * residual smoothing * computational experiments Subject RIV: BB - Applied Statistics, Operational Research

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

Science.gov (United States)

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

Error analysis of stochastic gradient descent ranking.

Science.gov (United States)

Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

Comparison of preconditioned generalized conjugate gradient methods to two-dimensional neutron and photon transport equation

International Nuclear Information System (INIS)

Chen, G.S.

1997-01-01

We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used. TFQMR (transpose free quasi-minimal residual algorithm), CGS (conjuage gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These sub-routines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. (author)

New Conjugacy Conditions and Related Nonlinear Conjugate Gradient Methods

International Nuclear Information System (INIS)

Dai, Y.-H.; Liao, L.-Z.

2001-01-01

Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. This paper proposes a new conjugacy condition, which considers an inexact line search scheme but reduces to the old one if the line search is exact. Based on the new conjugacy condition, two nonlinear conjugate gradient methods are constructed. Convergence analysis for the two methods is provided. Our numerical results show that one of the methods is very efficient for the given test problems

Experiments with conjugate gradient algorithms for homotopy curve tracking

Science.gov (United States)

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.

Pixel-based OPC optimization based on conjugate gradients.

Science.gov (United States)

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.

A penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography.

Science.gov (United States)

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.

Comparison of genetic algorithms with conjugate gradient methods

Science.gov (United States)

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.

Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals

KAUST Repository

Cho, Myung

2016-06-24

We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.

Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals

KAUST Repository

Cho, Myung; Cai, Jian-Feng; Liu, Suhui; Eldar, Yonina C.; Xu, Weiyu

2016-01-01

We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.

Conjugate Gradient Algorithms For Manipulator Simulation

Science.gov (United States)

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.

The multigrid preconditioned conjugate gradient method

Science.gov (United States)

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.

Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.

Science.gov (United States)

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.

Application of preconditioned conjugate gradient-like methods to reactor kinetics

International Nuclear Information System (INIS)

Yang, D.Y.; Chen, G.S.; Chou, H.P.

1993-01-01

Several conjugate gradient-like (CG-like) methods are applied to solve the nonsymmetric linear systems of equations derived from the time-dependent two-dimensional two-energy-group neutron diffusion equations by a finite difference approximation. The methods are: the generalized conjugate residual method; the generalized conjugate gradient least-square method; the generalized minimal residual method (GMRES); the conjugate gradient square method; and a variant of bi-conjugate gradient method (Bi-CGSTAB). In order to accelerate these methods, six preconditioning techniques are investigated. Two are based on pointwise incomplete factorization: the incomplete LU (ILU) and the modified incomplete LU (MILU) decompositions; two, based on the block tridiagonal structure of the coefficient matrix, are blockwise and modified blockwise incomplete factorizations, BILU and MBILU; two are the alternating-direction implicit and symmetric successive overrelaxation (SSOR) preconditioners, derived from the basic iterative schemes. Comparisons are made by using CG-like methods combined with different preconditioners to solve a sequence of time-step reactor transient problems. Numerical tests indicate that preconditioned BI-CGSTAB with the preconditioner MBILU requires less CPU time and fewer iterations than other methods. The preconditioned CG-like methods are less sensitive to the time-step size used than the Chebyshev semi-iteration method and line SOR method. The indication is that the CGS, Bi-CGSTAB and GMRES methods are, on average, better than the other methods in reactor kinetics computation and that a good preconditioner is more important than the choice of CG-like methods. The MILU decomposition based on the conventional row-sum criterion has difficulty yielding a convergent solution and an improved version is introduced. (author)

Robust Fully Distributed Minibatch Gradient Descent with Privacy Preservation

Directory of Open Access Journals (Sweden)

Gábor Danner

2018-01-01

Full Text Available Privacy and security are among the highest priorities in data mining approaches over data collected from mobile devices. Fully distributed machine learning is a promising direction in this context. However, it is a hard problem to design protocols that are efficient yet provide sufficient levels of privacy and security. In fully distributed environments, secure multiparty computation (MPC is often applied to solve these problems. However, in our dynamic and unreliable application domain, known MPC algorithms are not scalable or not robust enough. We propose a light-weight protocol to quickly and securely compute the sum query over a subset of participants assuming a semihonest adversary. During the computation the participants learn no individual values. We apply this protocol to efficiently calculate the sum of gradients as part of a fully distributed minibatch stochastic gradient descent algorithm. The protocol achieves scalability and robustness by exploiting the fact that in this application domain a “quick and dirty” sum computation is acceptable. We utilize the Paillier homomorphic cryptosystem as part of our solution combined with extreme lossy gradient compression to make the cost of the cryptographic algorithms affordable. We demonstrate both theoretically and experimentally, based on churn statistics from a real smartphone trace, that the protocol is indeed practically viable.

A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method

Directory of Open Access Journals (Sweden)

Shengwei Yao

2014-01-01

Full Text Available The conjugate gradient (CG method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai-Liao (2001. Based on this condition, the related nonlinear conjugate gradient method is given. With some mild conditions, the given method is globally convergent under the strong Wolfe-Powell line search for general functions. The numerical experiments show that the proposed method is very robust and efficient.

Conjugate Gradient like methods and their application to fixed source neutron diffusion problems

International Nuclear Information System (INIS)

Suetomi, Eiichi; Sekimoto, Hiroshi

1989-01-01

This paper presents a number of fast iterative methods for solving systems of linear equations appearing in fixed source problems for neutron diffusion. We employed the conjugate gradient and conjugate residual methods. In order to accelerate the conjugate residual method, we proposed the conjugate residual squared method by transforming the residual polynomial of the conjugate residual method. Since the convergence of these methods depends on the spectrum of coefficient matrix, we employed the incomplete Choleski (IC) factorization and the modified IC (MIC) factorization as preconditioners. These methods were applied to some neutron diffusion problems and compared with the successive overrelaxation (SOR) method. The results of these numerical experiments showed superior convergence characteristics of the conjugate gradient like method with MIC factorization to the SOR method, especially for a problem involving void region. The CPU time of the MICCG, MICCR and MICCRS methods showed no great difference. In order to vectorize the conjugate gradient like methods based on (M)IC factorization, the hyperplane method was used and implemented on the vector computers, the HITAC S-820/80 and ETA10-E (one processor mode). Significant decrease of the CPU times was observed on the S-820/80. Since the scaled conjugate gradient (SCG) method can be vectorized with no manipulation, it was also compared with the above methods. It turned out the SCG method was the fastest with respect to the CPU times on the ETA10-E. These results suggest that one should implement suitable algorithm for different vector computers. (author)

Comparison of preconditioned generalized conjugate gradient methods to two-dimensional neutron and photon transport equation

International Nuclear Information System (INIS)

Chen, G.S.; Yang, D.Y.

1998-01-01

We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used: TFQMR (transpose free quasi-minimal residual algorithm) CGS (conjugate gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These subroutines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. The reasons to choose the generalized conjugate gradient methods are that the methods have better residual (equivalent to error) control procedures in the computation and have better convergent rate. The pointwise incomplete LU factorization ILU, modified pointwise incomplete LU factorization MILU, block incomplete factorization BILU and modified blockwise incomplete LU factorization MBILU are the preconditioning techniques used in the several testing problems. In Bi-CGSTAB, CGS, TFQMR and QMRCGSTAB method, we find that either CGS or Bi-CGSTAB method combined with preconditioner MBILU is the most efficient algorithm in these methods in the several testing problems. The numerical solution of flux by preconditioned CGS and Bi-CGSTAB methods has the same result as those from Cray computer, obtained by either the point successive relaxation method or the line successive relaxation method combined with Gaussian elimination

Error Estimation in Preconditioned Conjugate Gradients

Czech Academy of Sciences Publication Activity Database

Strakoš, Zdeněk; Tichý, Petr

2005-01-01

Roč. 45, - (2005), s. 789-817 ISSN 0006-3835 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB1030306 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned conjugate gradient method * error bounds * stopping criteria * evaluation of convergence * numerical stability * finite precision arithmetic * rounding errors Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2005

M-step preconditioned conjugate gradient methods

Science.gov (United States)

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.

Application of Conjugate Gradient methods to tidal simulation

Science.gov (United States)

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.

Fractional-order gradient descent learning of BP neural networks with Caputo derivative.

Science.gov (United States)

Wang, Jian; Wen, Yanqing; Gou, Yida; Ye, Zhenyun; Chen, Hua

2017-05-01

Fractional calculus has been found to be a promising area of research for information processing and modeling of some physical systems. In this paper, we propose a fractional gradient descent method for the backpropagation (BP) training of neural networks. In particular, the Caputo derivative is employed to evaluate the fractional-order gradient of the error defined as the traditional quadratic energy function. The monotonicity and weak (strong) convergence of the proposed approach are proved in detail. Two simulations have been implemented to illustrate the performance of presented fractional-order BP algorithm on three small datasets and one large dataset. The numerical simulations effectively verify the theoretical observations of this paper as well. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Spectral Conjugate Gradient Method for Unconstrained Optimization

International Nuclear Information System (INIS)

Birgin, E. G.; Martinez, J. M.

2001-01-01

A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Perry, the Polak-Ribiere and the Fletcher-Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient optimization method. The best combination of formula, scaling and initial choice of step-length is compared against well known algorithms using a classical set of problems. An additional comparison involving an ill-conditioned estimation problem in Optics is presented

Problem of unstable pivots in the incomplete LU-conjugate gradient method

International Nuclear Information System (INIS)

Kershaw, D.S.

1978-01-01

Incomplete LU and incomplete-Cholesky conjugate gradient methods are becoming widely used in both laser and magnetic fusion research. In my original presentation of these methods, the problem of what to do if a pivot [L/sub ii/U/sub ii/) becomes very small or zero was raised and only partially answered by the suggestion that it be arbitrarily set to some non-zero value. In what follows it will be shown precisely how small the pivot can become before it must be fixed and precisely what value it should be set to in order to minimize the error in LU. Numerical examples will be given to show that not only does this prescription improve incomplete LU-conjugate gradient methods , but exact LU decomposition carried out with this prescription for handling small pivots and followed by a few linear or conjugate gradient iterations can be much faster than the permutations of rows and columns usually employed to circumvent small pivot problems

Ultrasonic wave propagation through aberrating layers: experimental verification of the conjugate gradient Rayleigh method

NARCIS (Netherlands)

Ledoux, L.A.F.; Berkhoff, Arthur P.; Thijssen, J.M.

The Conjugate Gradient Rayleigh method for the calculation of acoustic reflection and transmission at a rough interface between two media was experimentally verified. The method is based on a continuous version of the conjugate gradient technique and plane-wave expansions. We measured the beam

Conjugate-Gradient Algorithms For Dynamics Of Manipulators

Science.gov (United States)

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.

Conjugate gradient heat bath for ill-conditioned actions.

Science.gov (United States)

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.

PRECONDITIONED BI-CONJUGATE GRADIENT METHOD FOR RADIATIVE TRANSFER IN SPHERICAL MEDIA

International Nuclear Information System (INIS)

Anusha, L. S.; Nagendra, K. N.; Paletou, F.; Leger, L.

2009-01-01

A robust numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is proposed for the solution of the radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These are iterative methods based on the construction of a set of bi-orthogonal vectors. The application of the Pre-BiCG method in some benchmark tests shows that the method is quite versatile, and can handle difficult problems that may arise in astrophysical radiative transfer theory.

Necessary and sufficient conditions for the existence of a conjugate gradient method

International Nuclear Information System (INIS)

Faber, V.; Manteuffel, T.

1984-01-01

The authors characterize the class CG(s) of matrices A for which the linear system Ax = b can be solved by an s-term conjugate gradient method. The authors show that, except for a few anomalies, the class CG(s) consists of matrices A for which conjugate gradient methods are already known. These matrices are the Hermitian matrices, A* = A, and the matrices of the form A = e/sup i theta/(dI + B), with B* = -B. 7 references

Programmed gradient descent biosorption of strontium ions by Saccaromyces cerevisiae and ashing analysis: A decrement solution for nuclide and heavy metal disposal

Energy Technology Data Exchange (ETDEWEB)

Liu, Mingxue [Life Science and Engineering College, Southwest University of Science and Technology, Mianyang, 621010 (China); Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Dong, Faqin, E-mail: fqdong@swust.edu.cn [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Zhang, Wei [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Nie, Xiaoqin [Fundamental Science on Nuclear Wastes and Environmental Safety Laboratory, Mianyang, 621010 (China); Sun, Shiyong [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Wei, Hongfu; Luo, Lang; Xiang, Sha; Zhang, Gege [Life Science and Engineering College, Southwest University of Science and Technology, Mianyang, 621010 (China)

2016-08-15

Highlights: • A programmed gradient descent biosorption process was designed. • The adsorption and bioaccumulation quantity of strontium ions by yeast cell were measured. • The decrement of biosorbents after biosorption by ashing was analyzed. • A technological flow process of decrement solution for waste disposal was proposed. - Abstract: One of the waste disposal principles is decrement. The programmed gradient descent biosorption of strontium ions by Saccaromyces cerevisiae regarding bioremoval and ashing process for decrement were studied in present research. The results indicated that S. cerevisiae cells showed valid biosorption for strontium ions with greater than 90% bioremoval efficiency for high concentration strontium ions under batch culture conditions. The S. cerevisiae cells bioaccumulated approximately 10% of strontium ions in the cytoplasm besides adsorbing 90% strontium ions on cell wall. The programmed gradient descent biosorption presented good performance with a nearly 100% bioremoval ratio for low concentration strontium ions after 3 cycles. The ashing process resulted in a huge volume and weight reduction ratio as well as enrichment for strontium in the ash. XRD results showed that SrSO{sub 4} existed in ash. Simulated experiments proved that sulfate could adjust the precipitation of strontium ions. Finally, we proposed a technological flow process that combined the programmed gradient descent biosorption and ashing, which could yield great decrement and allow the supernatant to meet discharge standard. This technological flow process may be beneficial for nuclides and heavy metal disposal treatment in many fields.

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

Science.gov (United States)

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.

Moving force identification based on modified preconditioned conjugate gradient method

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Implementasi Jaringan Syaraf Tiruan Recurrent Menggunakan Gradient Descent Adaptive Learning Rate and Momentum Untuk Pendugaan Curah Hujan

Directory of Open Access Journals (Sweden)

Afan Galih Salman

2011-06-01

Full Text Available The artificial neural network (ANN technology in rainfall prediction can be done using the learning approach. The ANN prediction accuracy is measured by the determination coefficient (R2 and root mean square error (RMSE. This research implements Elman’s Recurrent ANN which is heuristically optimized based on el-nino southern oscilation (ENSO variables: wind, southern oscillation index (SOI, sea surface temperatur (SST dan outgoing long wave radiation (OLR to forecast regional monthly rainfall in Bongan Bali. The heuristic learning optimization done is basically a performance development of standard gradient descent learning algorithm into training algorithms: gradient descent momentum and adaptive learning rate. The patterns of input data affect the performance of Recurrent Elman neural network in estimation process. The first data group that is 75% training data and 25% testing data produce the maximum R2 leap 74,6% while the second data group that is 50% training data and 50% testing data produce the maximum R2 leap 49,8%.

A complete implementation of the conjugate gradient algorithm on a reconfigurable supercomputer

International Nuclear Information System (INIS)

Dubois, David H.; Dubois, Andrew J.; Connor, Carolyn M.; Boorman, Thomas M.; Poole, Stephen W.

2008-01-01

The conjugate gradient is a prominent iterative method for solving systems of sparse linear equations. Large-scale scientific applications often utilize a conjugate gradient solver at their computational core. In this paper we present a field programmable gate array (FPGA) based implementation of a double precision, non-preconditioned, conjugate gradient solver for fmite-element or finite-difference methods. OUf work utilizes the SRC Computers, Inc. MAPStation hardware platform along with the 'Carte' software programming environment to ease the programming workload when working with the hybrid (CPUIFPGA) environment. The implementation is designed to handle large sparse matrices of up to order N x N where N <= 116,394, with up to 7 non-zero, 64-bit elements per sparse row. This implementation utilizes an optimized sparse matrix-vector multiply operation which is critical for obtaining high performance. Direct parallel implementations of loop unrolling and loop fusion are utilized to extract performance from the various vector/matrix operations. Rather than utilize the FPGA devices as function off-load accelerators, our implementation uses the FPGAs to implement the core conjugate gradient algorithm. Measured run-time performance data is presented comparing the FPGA implementation to a software-only version showing that the FPGA can outperform processors running up to 30x the clock rate. In conclusion we take a look at the new SRC-7 system and estimate the performance of this algorithm on that architecture.

HIRFL-SSC trim coil currents calculation by conjugate gradients method

International Nuclear Information System (INIS)

Liu, W.

2005-01-01

For accelerating different kinds of ions to various energies, the HIRFL-SSC should form the corresponding isochronous magnetic field by its main coil and trim coils. Previously, there were errors in fitting the theoretical isochronous magnetic field in the small radius region, which led to some operation difficulties for ion acceleration in the inject region. After further investigation of the restrictive condition of the maximum current limitation, the trim coil currents for fitting the theoretical isochronous magnetic field were recalculated by the conjugate gradients method. Better results were obtained in the operation of HIRFL-SSC. This article introduces the procedure to calculate the trim coil currents. The calculation method of conjugate gradients is introduced and the fitting error is analysed. (author)

Application of conjugate gradient method to Commix-1B three-dimensional momentum equation

International Nuclear Information System (INIS)

King, J.B.; Domanus, H.

1987-01-01

Conjugate gradient method which is a special case of the variational method was implemented in the momentum section of the COMMIX-1B thermal hydraulics code. The comparisons between this method and the conventional iterative method of Successive Over Relation (S.O.R.) were made. Using COMMIX-1B, three steady state problems were analyzed. These problems were flow distribution in a scaled model of the Clinch River Fast Breeder Reactor outlet plenum, flow of coolant in the cold leg and downcomer of a PWR and isothermal air flow through a partially blocked pipe. It was found that if the conjugate gradient method is used, the execution time required to solve the resulting COMMIX-1B system of equations can be reduced by a factor of about 2 for the first two problems. For the isothermal air flow problem, the conjugate gradient method did not improve the execution time

Accurate conjugate gradient methods for families of shifted systems

NARCIS (Netherlands)

Eshof, J. van den; Sleijpen, G.L.G.

We present an efficient and accurate variant of the conjugate gradient method for solving families of shifted systems. In particular we are interested in shifted systems that occur in Tikhonov regularization for inverse problems since these problems can be sensitive to roundoff errors. The

Implementing the conjugate gradient algorithm on multi-core systems

NARCIS (Netherlands)

Wiggers, W.A.; Bakker, Vincent; Kokkeler, Andre B.J.; Smit, Gerardus Johannes Maria; Nurmi, J.; Takala, J.; Vainio, O.

2007-01-01

In linear solvers, like the conjugate gradient algorithm, sparse-matrix vector multiplication is an important kernel. Due to the sparseness of the matrices, the solver runs relatively slow. For digital optical tomography (DOT), a large set of linear equations have to be solved which currently takes

Use of a preconditioned Bi-conjugate gradient method for hybrid plasma stability analysis

International Nuclear Information System (INIS)

Mikic, Z.; Morse, E.C.

1985-01-01

The numerical stability analysis of compact toroidal plasmas using implicit time differencing requires the solution of a set of coupled, 2-dimensional, elliptic partial differential equations for the field quantities at every timestep. When the equations are spatially finite-differenced and written in matrix form, the resulting matrix is large, sparse, complex, non-Hermitian, and indefinite. The use of the preconditioned bi-conjugate gradient method for solving these equations is discussed. The effect of block-diagonal preconditioning and incomplete block-LU preconditionig on the convergence of the method is investigated. For typical matrices arising in our studies, the eigenvalue spectra of the original and preconditioned matrices are calculated as an illustration of the effectiveness of the preconditioning. We show that the preconditioned bi-conjugate gradient method coverages more rapidly than the conjugate gradient method applied to the normal equations, and that it is an effective iterative method for the class of non-Hermitian, indefinite problems of interest

Applying Gradient Descent in Convolutional Neural Networks

Science.gov (United States)

Cui, Nan

2018-04-01

With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

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

Science.gov (United States)

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.

Conjugate gradient optimization programs for shuttle reentry

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Fastest Rates for Stochastic Mirror Descent Methods

KAUST Repository

Hanzely, Filip; Richtarik, Peter

2018-01-01

Relative smoothness - a notion introduced by Birnbaum et al. (2011) and rediscovered by Bauschke et al. (2016) and Lu et al. (2016) - generalizes the standard notion of smoothness typically used in the analysis of gradient type methods. In this work we are taking ideas from well studied field of stochastic convex optimization and using them in order to obtain faster algorithms for minimizing relatively smooth functions. We propose and analyze two new algorithms: Relative Randomized Coordinate Descent (relRCD) and Relative Stochastic Gradient Descent (relSGD), both generalizing famous algorithms in the standard smooth setting. The methods we propose can be in fact seen as a particular instances of stochastic mirror descent algorithms. One of them, relRCD corresponds to the first stochastic variant of mirror descent algorithm with linear convergence rate.

Fastest Rates for Stochastic Mirror Descent Methods

KAUST Repository

Hanzely, Filip

2018-03-20

Relative smoothness - a notion introduced by Birnbaum et al. (2011) and rediscovered by Bauschke et al. (2016) and Lu et al. (2016) - generalizes the standard notion of smoothness typically used in the analysis of gradient type methods. In this work we are taking ideas from well studied field of stochastic convex optimization and using them in order to obtain faster algorithms for minimizing relatively smooth functions. We propose and analyze two new algorithms: Relative Randomized Coordinate Descent (relRCD) and Relative Stochastic Gradient Descent (relSGD), both generalizing famous algorithms in the standard smooth setting. The methods we propose can be in fact seen as a particular instances of stochastic mirror descent algorithms. One of them, relRCD corresponds to the first stochastic variant of mirror descent algorithm with linear convergence rate.

Efficient two-level preconditionined conjugate gradient method on the GPU

NARCIS (Netherlands)

Gupta, R.; Van Gijzen, M.B.; Vuik, K.

2011-01-01

We present an implementation of Two-Level Preconditioned Conjugate Gradient Method for the GPU. We investigate a Truncated Neumann Series based preconditioner in combination with deflation and compare it with Block Incomplete Cholesky schemes. This combination exhibits fine-grain parallelism and

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

Science.gov (United States)

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

PET regularization by envelope guided conjugate gradients

International Nuclear Information System (INIS)

Kaufman, L.; Neumaier, A.

1996-01-01

The authors propose a new way to iteratively solve large scale ill-posed problems and in particular the image reconstruction problem in positron emission tomography by exploiting the relation between Tikhonov regularization and multiobjective optimization to obtain iteratively approximations to the Tikhonov L-curve and its corner. Monitoring the change of the approximate L-curves allows us to adjust the regularization parameter adaptively during a preconditioned conjugate gradient iteration, so that the desired solution can be reconstructed with a small number of iterations

Solving large mixed linear models using preconditioned conjugate gradient iteration.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Conjugate gradient type methods for linear systems with complex symmetric coefficient matrices

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Deflation in preconditioned conjugate gradient methods for Finite Element Problems

NARCIS (Netherlands)

Vermolen, F.J.; Vuik, C.; Segal, A.

2002-01-01

We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods applied to a Finite Element discretization for an elliptic equation. Our set-up is a Poisson problem in two dimensions with continuous or discontinuous

The Lanczos and Conjugate Gradient Algorithms in Finite Precision Arithmetic

Czech Academy of Sciences Publication Activity Database

Meurant, G.; Strakoš, Zdeněk

2006-01-01

Roč. 15, - (2006), s. 471-542 ISSN 0962-4929 R&D Projects: GA AV ČR 1ET400300415 Institutional research plan: CEZ:AV0Z10300504 Keywords : Lanczos method * conjugate gradient method * finite precision arithmetic * numerical stability * iterative methods Subject RIV: BA - General Mathematics

A partitioned conjugate gradient algorithm for lattice Green functions

International Nuclear Information System (INIS)

Bowler, K.C.; Kenway, R.D.; Pawley, G.S.; Wallace, D.J.

1984-01-01

Partitioning reduces by one the dimensionality of the lattice on which a propagator need be calculated using, for example, the conjugate gradient algorithm. Thus the quark propagator in lattice QCD may be determined by a computation on a single spatial hyperplane. For free fermions on a 16 3 x N lattice 2N-bit accuracy in the propagator is required to avoid rounding errors. (orig.)

Accurate reanalysis of structures by a preconditioned conjugate gradient method

Czech Academy of Sciences Publication Activity Database

Kirsch, U.; Kočvara, Michal; Zowe, J.

2002-01-01

Roč. 55, č. 2 (2002), s. 233-251 ISSN 0029-5981 R&D Projects: GA AV ČR IAA1075005 Grant - others:BMBF(DE) 03ZOM3ER Institutional research plan: CEZ:AV0Z1075907 Keywords : preconditioned conjugate gradient s * structural reanalysis Subject RIV: BA - General Mathematics Impact factor: 1.468, year: 2002

New generalized conjugate gradient methods for the non-quadratic model in unconstrained optimization

International Nuclear Information System (INIS)

Al-Bayati, A.

2001-01-01

This paper present two new conjugate gradient algorithms which use the non-quadratic model in unconstrained optimization. The first is a new generalized self-scaling variable metric algorithm based on the sloboda generalized conjugate gradient method which is invariant to a nonlinear scaling of a stricity convex quadratic function; the second is an interleaving between the generalized sloboda method and the first algorithm; all these algorithm use exact line searches. Numerical comparisons over twenty test functions show that the interleaving algorithm is best overall and requires only about half the function evaluations of the Sloboda method: interleaving algorithms are likely to be preferred when the dimensionality of the problem is increased. (author). 29 refs., 1 tab

MILC staggered conjugate gradient performance on Intel KNL

OpenAIRE

DeTar, Carleton; Doerfler, Douglas; Gottlieb, Steven; Jha, Ashish; Kalamkar, Dhiraj; Li, Ruizi; Toussaint, Doug

2016-01-01

We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. ...

Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent

Science.gov (United States)

De Sa, Christopher; Feldman, Matthew; Ré, Christopher; Olukotun, Kunle

2018-01-01

Stochastic gradient descent (SGD) is one of the most popular numerical algorithms used in machine learning and other domains. Since this is likely to continue for the foreseeable future, it is important to study techniques that can make it run fast on parallel hardware. In this paper, we provide the first analysis of a technique called Buckwild! that uses both asynchronous execution and low-precision computation. We introduce the DMGC model, the first conceptualization of the parameter space that exists when implementing low-precision SGD, and show that it provides a way to both classify these algorithms and model their performance. We leverage this insight to propose and analyze techniques to improve the speed of low-precision SGD. First, we propose software optimizations that can increase throughput on existing CPUs by up to 11×. Second, we propose architectural changes, including a new cache technique we call an obstinate cache, that increase throughput beyond the limits of current-generation hardware. We also implement and analyze low-precision SGD on the FPGA, which is a promising alternative to the CPU for future SGD systems. PMID:29391770

Practical gradient-descent for memristive crossbars

OpenAIRE

Nair, Manu V; Dudek, Piotr

2015-01-01

This paper discusses implementations of gradientdescent based learning algorithms on memristive crossbar arrays. The Unregulated Step Descent (USD) is described as a practical algorithm for feed-forward on-line training of large crossbar arrays. It allows fast feed-forward fully parallel on-line hardware based learning, without requiring accurate models of the memristor behaviour and precise control of the programming pulses. The effect of device parameters, training parameters, and device va...

Computing several eigenpairs of Hermitian problems by conjugate gradient iterations

International Nuclear Information System (INIS)

Ovtchinnikov, E.E.

2008-01-01

The paper is concerned with algorithms for computing several extreme eigenpairs of Hermitian problems based on the conjugate gradient method. We analyse computational strategies employed by various algorithms of this kind reported in the literature and identify their limitations. Our criticism is illustrated by numerical tests on a set of problems from electronic structure calculations and acoustics

An M-step preconditioned conjugate gradient method for parallel computation

Science.gov (United States)

Adams, L.

1983-01-01

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

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

Science.gov (United States)

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.

Machine learning for inverse lithography: using stochastic gradient descent for robust photomask synthesis

International Nuclear Information System (INIS)

Jia, Ningning; Lam, Edmund Y

2010-01-01

Inverse lithography technology (ILT) synthesizes photomasks by solving an inverse imaging problem through optimization of an appropriate functional. Much effort on ILT is dedicated to deriving superior masks at a nominal process condition. However, the lower k 1 factor causes the mask to be more sensitive to process variations. Robustness to major process variations, such as focus and dose variations, is desired. In this paper, we consider the focus variation as a stochastic variable, and treat the mask design as a machine learning problem. The stochastic gradient descent approach, which is a useful tool in machine learning, is adopted to train the mask design. Compared with previous work, simulation shows that the proposed algorithm is effective in producing robust masks

Two-level preconditioned conjugate gradient methods with applications to bubbly flow problems

NARCIS (Netherlands)

Tang, J.M.

2008-01-01

The Preconditioned Conjugate Gradient (PCG) method is one of the most popular iterative methods for solving large linear systems with a symmetric and positive semi-definite coefficient matrix. However, if the preconditioned coefficient matrix is ill-conditioned, the convergence of the PCG method

Realization of preconditioned Lanczos and conjugate gradient algorithms on optical linear algebra processors.

Science.gov (United States)

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.

Gadolinium burnable absorber optimization by the method of conjugate gradients

International Nuclear Information System (INIS)

Drumm, C.R.; Lee, J.C.

1987-01-01

The optimal axial distribution of gadolinium burnable poison in a pressurized water reactor is determined to yield an improved power distribution. The optimization scheme is based on Pontryagin's maximum principle, with the objective function accounting for a target power distribution. The conjugate gradients optimization method is used to solve the resulting Euler-Lagrange equations iteratively, efficiently handling the high degree of nonlinearity of the problem

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

Science.gov (United States)

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

Numerical Simulation of Solid Combustion with a Robust Conjugate-Gradient Solution for Pressure

National Research Council Canada - National Science Library

Wang, Yi-Zun

2002-01-01

A Bi-Conjugate Gradient method (Bi-CGSTAB) is studied and tested for solid combustion in which the gas and solid phases are coupled by a set of conditions describing mass, momentum and heat transport across the interface...

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

Science.gov (United States)

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.

Analysis and performance estimation of the Conjugate Gradient method on multiple GPUs

NARCIS (Netherlands)

Verschoor, M.; Jalba, A.C.

2012-01-01

The Conjugate Gradient (CG) method is a widely-used iterative method for solving linear systems described by a (sparse) matrix. The method requires a large amount of Sparse-Matrix Vector (SpMV) multiplications, vector reductions and other vector operations to be performed. We present a number of

T2CG1, a package of preconditioned conjugate gradient solvers for TOUGH2

International Nuclear Information System (INIS)

Moridis, G.; Pruess, K.; Antunez, E.

1994-03-01

Most of the computational work in the numerical simulation of fluid and heat flows in permeable media arises in the solution of large systems of linear equations. The simplest technique for solving such equations is by direct methods. However, because of large storage requirements and accumulation of roundoff errors, the application of direct solution techniques is limited, depending on matrix bandwidth, to systems of a few hundred to at most a few thousand simultaneous equations. T2CG1, a package of preconditioned conjugate gradient solvers, has been added to TOUGH2 to complement its direct solver and significantly increase the size of problems tractable on PCs. T2CG1 includes three different solvers: a Bi-Conjugate Gradient (BCG) solver, a Bi-Conjugate Gradient Squared (BCGS) solver, and a Generalized Minimum Residual (GMRES) solver. Results from six test problems with up to 30,000 equations show that T2CG1 (1) is significantly (and invariably) faster and requires far less memory than the MA28 direct solver, (2) it makes possible the solution of very large three-dimensional problems on PCs, and (3) that the BCGS solver is the fastest of the three in the tested problems. Sample problems are presented related to heat and fluid flow at Yucca Mountain and WIPP, environmental remediation by the Thermal Enhanced Vapor Extraction System, and geothermal resources

Three-Dimensional Induced Polarization Parallel Inversion Using Nonlinear Conjugate Gradients Method

Directory of Open Access Journals (Sweden)

Huan Ma

2015-01-01

Full Text Available Four kinds of array of induced polarization (IP methods (surface, borehole-surface, surface-borehole, and borehole-borehole are widely used in resource exploration. However, due to the presence of large amounts of the sources, it will take much time to complete the inversion. In the paper, a new parallel algorithm is described which uses message passing interface (MPI and graphics processing unit (GPU to accelerate 3D inversion of these four methods. The forward finite differential equation is solved by ILU0 preconditioner and the conjugate gradient (CG solver. The inverse problem is solved by nonlinear conjugate gradients (NLCG iteration which is used to calculate one forward and two “pseudo-forward” modelings and update the direction, space, and model in turn. Because each source is independent in forward and “pseudo-forward” modelings, multiprocess modes are opened by calling MPI library. The iterative matrix solver within CULA is called in each process. Some tables and synthetic data examples illustrate that this parallel inversion algorithm is effective. Furthermore, we demonstrate that the joint inversion of surface and borehole data produces resistivity and chargeability results are superior to those obtained from inversions of individual surface data.

Conjugate gradient coupled with multigrid for an indefinite problem

Science.gov (United States)

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.

On the solution of the Hartree-Fock-Bogoliubov equations by the conjugate gradient method

International Nuclear Information System (INIS)

Egido, J.L.; Robledo, L.M.

1995-01-01

The conjugate gradient method is formulated in the Hilbert space for density and non-density dependent Hamiltonians. We apply it to the solution of the Hartree-Fock-Bogoliubov equations with constraints. As a numerical application we show calculations with the finite range density dependent Gogny force. The number of iterations required to reach convergence is reduced by a factor of three to four as compared with the standard gradient method. (orig.)

Compensation of spatial system response in SPECT with conjugate gradient reconstruction technique

International Nuclear Information System (INIS)

Formiconi, A.R.; Pupi, A.; Passeri, A.

1989-01-01

A procedure for determination of the system matrix in single photon emission tomography (SPECT) is described which use a conjugate gradient reconstruction technique to take into account the variable system resolution of a camera equipped with parallel-hole collimators. The procedure involves acquisition of system line spread functions (LSF) in the region occupied by the object studied. Those data are used to generate a set of weighting factors based on the assumption that the LSFs of the collimated camera are of Gaussian shape with full width at half maximum (FWHM) linearly dependent on source depth in the span of image space. Factors are stored on a disc file for subsequent use in reconstruction. Afterwards reconstruction is performed using the conjugate gradient method with the system matrix modified by incorporation of these precalculated factors to take into account variable geometrical system response. The set of weighting factors is regenerated whenever acquisition conditions are changed (collimator, radius of rotation) with an ultra high resolution (UHR) collimator 2000 weighting factors need to be calculated. (author)

The influence of deflation vectors at interfaces on the deflated conjugate gradient method

NARCIS (Netherlands)

Vermolen, F.J.; Vuik, C.

2001-01-01

We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods. Our set-up is a Laplace problem in two dimensions with continuous or discontinuous coeffcients that vary in several orders of magnitude. In the

A fast nonlinear conjugate gradient based method for 3D frictional contact problems

NARCIS (Netherlands)

Zhao, J.; Vollebregt, E.A.H.; Oosterlee, C.W.

2014-01-01

This paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from a 3D frictional contact problem. It incorporates an active set strategy with a nonlinear conjugate gradient method. One novelty is to consider the tractions of each slip element in a polar

Understanding the Convolutional Neural Networks with Gradient Descent and Backpropagation

Science.gov (United States)

Zhou, XueFei

2018-04-01

With the development of computer technology, the applications of machine learning are more and more extensive. And machine learning is providing endless opportunities to develop new applications. One of those applications is image recognition by using Convolutional Neural Networks (CNNs). CNN is one of the most common algorithms in image recognition. It is significant to understand its theory and structure for every scholar who is interested in this field. CNN is mainly used in computer identification, especially in voice, text recognition and other aspects of the application. It utilizes hierarchical structure with different layers to accelerate computing speed. In addition, the greatest features of CNNs are the weight sharing and dimension reduction. And all of these consolidate the high effectiveness and efficiency of CNNs with idea computing speed and error rate. With the help of other learning altruisms, CNNs could be used in several scenarios for machine learning, especially for deep learning. Based on the general introduction to the background and the core solution CNN, this paper is going to focus on summarizing how Gradient Descent and Backpropagation work, and how they contribute to the high performances of CNNs. Also, some practical applications will be discussed in the following parts. The last section exhibits the conclusion and some perspectives of future work.

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

Science.gov (United States)

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.

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Science.gov (United States)

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).

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Directory of Open Access Journals (Sweden)

Gonglin Yuan

Full Text Available 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.

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

Science.gov (United States)

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.

MILC staggered conjugate gradient performance on Intel KNL

Energy Technology Data Exchange (ETDEWEB)

Li, Ruiz [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Detar, Carleton [Univ. of Utah, Salt Lake City, UT (United States). Dept. of Physics and Astronomy; Doerfler, Douglas W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Gottlieb, Steven [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Jha, Asish [Intel Corp., Hillsboro, OR (United States). Sofware and Services Group; Kalamkar, Dhiraj [Intel Labs., Bangalore (India). Parallel Computing Lab.; Toussaint, Doug [Univ. of Arizona, Tucson, AZ (United States). Physics Dept.

2016-11-03

We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. We compare performance of an MPI+OpenMP baseline version of the MILC code with a version incorporating the QPhiX staggered CG solver, for both one-node and multi-node runs.

A fast nonlinear conjugate gradient based method for 3D concentrated frictional contact problems

NARCIS (Netherlands)

J. Zhao (Jing); E.A.H. Vollebregt (Edwin); C.W. Oosterlee (Cornelis)

2015-01-01

htmlabstractThis paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from 3D concentrated frictional shift and rolling contact problems with dry Coulomb friction. The solver combines an active set strategy with a nonlinear conjugate gradient method. One

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

Directory of Open Access Journals (Sweden)

Dexiang Feng

2017-09-01

Full Text Available Abstract 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.

Landslide Occurrence Prediction Using Trainable Cascade Forward Network and Multilayer Perceptron

Directory of Open Access Journals (Sweden)

Mohammad Subhi Al-batah

2015-01-01

Full Text Available Landslides are one of the dangerous natural phenomena that hinder the development in Penang Island, Malaysia. Therefore, finding the reliable method to predict the occurrence of landslides is still the research of interest. In this paper, two models of artificial neural network, namely, Multilayer Perceptron (MLP and Cascade Forward Neural Network (CFNN, are introduced to predict the landslide hazard map of Penang Island. These two models were tested and compared using eleven machine learning algorithms, that is, Levenberg Marquardt, Broyden Fletcher Goldfarb, Resilient Back Propagation, Scaled Conjugate Gradient, Conjugate Gradient with Beale, Conjugate Gradient with Fletcher Reeves updates, Conjugate Gradient with Polakribiere updates, One Step Secant, Gradient Descent, Gradient Descent with Momentum and Adaptive Learning Rate, and Gradient Descent with Momentum algorithm. Often, the performance of the landslide prediction depends on the input factors beside the prediction method. In this research work, 14 input factors were used. The prediction accuracies of networks were verified using the Area under the Curve method for the Receiver Operating Characteristics. The results indicated that the best prediction accuracy of 82.89% was achieved using the CFNN network with the Levenberg Marquardt learning algorithm for the training data set and 81.62% for the testing data set.

Parallel preconditioned conjugate gradient algorithm applied to neutron diffusion problem

International Nuclear Information System (INIS)

Majumdar, A.; Martin, W.R.

1992-01-01

Numerical solution of the neutron diffusion problem requires solving a linear system of equations such as Ax = b, where A is an n x n symmetric positive definite (SPD) matrix; x and b are vectors with n components. The preconditioned conjugate gradient (PCG) algorithm is an efficient iterative method for solving such a linear system of equations. In this paper, the authors describe the implementation of a parallel PCG algorithm on a shared memory machine (BBN TC2000) and on a distributed workstation (IBM RS6000) environment created by the parallel virtual machine parallelization software

A fast, preconditioned conjugate gradient Toeplitz solver

Science.gov (United States)

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.

A nonsmooth nonlinear conjugate gradient method for interactive contact force problems

DEFF Research Database (Denmark)

Silcowitz, Morten; Abel, Sarah Maria Niebe; Erleben, Kenny

2010-01-01

of a nonlinear complementarity problem (NCP), which can be solved using an iterative splitting method, such as the projected Gauss–Seidel (PGS) method. We present a novel method for solving the NCP problem by applying a Fletcher–Reeves type nonlinear nonsmooth conjugate gradient (NNCG) type method. We analyze...... and present experimental convergence behavior and properties of the new method. Our results show that the NNCG method has at least the same convergence rate as PGS, and in many cases better....

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

preconditioning the modified conjugate gradient method

African Journals Online (AJOL)

Admin

steepest descent method, the number of matrix-vector products per iteration .... modified CGM algorithm is used for large class of problems that is not ..... New Trends in the Mathematical and Computer Sciences with Applications to Real World.

A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics

DEFF Research Database (Denmark)

Engell-Nørregård, Morten; Erleben, Kenny

2009-01-01

Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...

An online supervised learning method based on gradient descent for spiking neurons.

Science.gov (United States)

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Accelerating learning of neural networks with conjugate gradients for nuclear power plant applications

International Nuclear Information System (INIS)

Reifman, J.; Vitela, J.E.

1994-01-01

The method of conjugate gradients is used to expedite the learning process of feedforward multilayer artificial neural networks and to systematically update both the learning parameter and the momentum parameter at each training cycle. The mechanism for the occurrence of premature saturation of the network nodes observed with the back propagation algorithm is described, suggestions are made to eliminate this undesirable phenomenon, and the reason by which this phenomenon is precluded in the method of conjugate gradients is presented. The proposed method is compared with the standard back propagation algorithm in the training of neural networks to classify transient events in neural power plants simulated by the Midland Nuclear Power Plant Unit 2 simulator. The comparison results indicate that the rate of convergence of the proposed method is much greater than the standard back propagation, that it reduces both the number of training cycles and the CPU time, and that it is less sensitive to the choice of initial weights. The advantages of the method are more noticeable and important for problems where the network architecture consists of a large number of nodes, the training database is large, and a tight convergence criterion is desired

The q-G method : A q-version of the Steepest Descent method for global optimization.

Science.gov (United States)

Soterroni, Aline C; Galski, Roberto L; Scarabello, Marluce C; Ramos, Fernando M

2015-01-01

In this work, the q-Gradient (q-G) method, a q-version of the Steepest Descent method, is presented. The main idea behind the q-G method is the use of the negative of the q-gradient vector of the objective function as the search direction. The q-gradient vector, or simply the q-gradient, is a generalization of the classical gradient vector based on the concept of Jackson's derivative from the q-calculus. Its use provides the algorithm an effective mechanism for escaping from local minima. The q-G method reduces to the Steepest Descent method when the parameter q tends to 1. The algorithm has three free parameters and it is implemented so that the search process gradually shifts from global exploration in the beginning to local exploitation in the end. We evaluated the q-G method on 34 test functions, and compared its performance with 34 optimization algorithms, including derivative-free algorithms and the Steepest Descent method. Our results show that the q-G method is competitive and has a great potential for solving multimodal optimization problems.

On conjugate gradient type methods and polynomial preconditioners for a class of complex non-Hermitian matrices

Science.gov (United States)

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.

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

International Nuclear Information System (INIS)

Dong Bing; Ren Deqing; Zhang Xi

2011-01-01

An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image contrast shows improvement from 10 -3 to 10 -4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.

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

Science.gov (United States)

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.

Program generator for the Incomplete Cholesky Conjugate Gradient (ICCG) method

International Nuclear Information System (INIS)

Kuo-Petravic, G.; Petravic, M.

1978-04-01

The Incomplete Cholesky Conjugate Gradient (ICCG) method has been found very effective for the solution of sparse systems of linear equations. Its implementation on a computer, however, requires a considerable amount of careful coding to achieve good machine efficiency. Furthermore, the resulting code is necessarily inflexible and cannot be easily adapted to different problems. We present in this paper a code generator GENIC which, given a small amount of information concerning the sparsity pattern and size of the system of equations, generates a solver package. This package, called SOLIC, is tailor made for a particular problem and can be easily incorporated into any user program

On computing quadrature-based bounds for the A-norm of the error in conjugate gradients

Czech Academy of Sciences Publication Activity Database

Meurant, G.; Tichý, Petr

2013-01-01

Roč. 62, č. 2 (2013), s. 163-191 ISSN 1017-1398 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : conjugate gradients * norm of the error * bounds for the error norm Subject RIV: BA - General Mathematics Impact factor: 1.005, year: 2013

On computing quadrature-based bounds for the A-norm of the error in conjugate gradients

Czech Academy of Sciences Publication Activity Database

Meurant, G.; Tichý, Petr

2013-01-01

Roč. 62, č. 2 (2013), s. 163-191 ISSN 1017-1398 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : conjugate gradient s * norm of the error * bounds for the error norm Subject RIV: BA - General Mathematics Impact factor: 1.005, year: 2013

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

Science.gov (United States)

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.

Method of T2 spectrum inversion with conjugate gradient algorithm from NMR data

International Nuclear Information System (INIS)

Li Pengju; Shi Shangming; Song Yanjie

2010-01-01

Based on the optimization techniques, the T 2 spectrum inversion method of conjugate gradient that is easy to realize non-negativity constraint of T2 spectrum is proposed. The method transforms the linear mixed-determined problem of T2 spectrum inversion into the typical optimization problem of searching the minimum of objective function by building up the objective function according to the basic idea of geophysics modeling. The optimization problem above is solved with the conjugate gradient algorithm that has quick convergence rate and quadratic termination. The method has been applied to the inversion of noise free echo train generated from artificial spectrum, artificial echo train with signal-to-noise ratio (SNR)=25 and NMR experimental data of drilling core. The comparison between the inversion results of this paper and artificial spectrum or the result of software imported in NMR laboratory shows that the method can correctly invert T 2 spectrum from artificial NMR relaxation data even though SNR=25 and that inversion T 2 spectrum with good continuity and smoothness from core NMR experimental data accords perfectly with that of laboratory software imported, and moreover,the absolute error between the NMR porosity computed from T 2 spectrum and helium (He) porosity in laboratory is 0.65%. (authors)

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

Science.gov (United States)

Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo

2011-07-01

Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.

Aerodynamic shape optimization using preconditioned conjugate gradient methods

Science.gov (United States)

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.

Total variation superiorized conjugate gradient method for image reconstruction

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Sobolev gradients and differential equations

CERN Document Server

Neuberger, J W

2010-01-01

A Sobolev gradient of a real-valued functional on a Hilbert space is a gradient of that functional taken relative to an underlying Sobolev norm. This book shows how descent methods using such gradients allow a unified treatment of a wide variety of problems in differential equations. For discrete versions of partial differential equations, corresponding Sobolev gradients are seen to be vastly more efficient than ordinary gradients. In fact, descent methods with these gradients generally scale linearly with the number of grid points, in sharp contrast with the use of ordinary gradients. Aside from the first edition of this work, this is the only known account of Sobolev gradients in book form. Most of the applications in this book have emerged since the first edition was published some twelve years ago. What remains of the first edition has been extensively revised. There are a number of plots of results from calculations and a sample MatLab code is included for a simple problem. Those working through a fair p...

Modified Convolutional Neural Network Based on Dropout and the Stochastic Gradient Descent Optimizer

Directory of Open Access Journals (Sweden)

Jing Yang

2018-03-01

Full Text Available This study proposes a modified convolutional neural network (CNN algorithm that is based on dropout and the stochastic gradient descent (SGD optimizer (MCNN-DS, after analyzing the problems of CNNs in extracting the convolution features, to improve the feature recognition rate and reduce the time-cost of CNNs. The MCNN-DS has a quadratic CNN structure and adopts the rectified linear unit as the activation function to avoid the gradient problem and accelerate convergence. To address the overfitting problem, the algorithm uses an SGD optimizer, which is implemented by inserting a dropout layer into the all-connected and output layers, to minimize cross entropy. This study used the datasets MNIST, HCL2000, and EnglishHand as the benchmark data, analyzed the performance of the SGD optimizer under different learning parameters, and found that the proposed algorithm exhibited good recognition performance when the learning rate was set to [0.05, 0.07]. The performances of WCNN, MLP-CNN, SVM-ELM, and MCNN-DS were compared. Statistical results showed the following: (1 For the benchmark MNIST, the MCNN-DS exhibited a high recognition rate of 99.97%, and the time-cost of the proposed algorithm was merely 21.95% of MLP-CNN, and 10.02% of SVM-ELM; (2 Compared with SVM-ELM, the average improvement in the recognition rate of MCNN-DS was 2.35% for the benchmark HCL2000, and the time-cost of MCNN-DS was only 15.41%; (3 For the EnglishHand test set, the lowest recognition rate of the algorithm was 84.93%, the highest recognition rate was 95.29%, and the average recognition rate was 89.77%.

Penalty Algorithm Based on Conjugate Gradient Method for Solving Portfolio Management Problem

Directory of Open Access Journals (Sweden)

Wang YaLin

2009-01-01

Full Text Available A new approach was proposed to reformulate the biobjectives optimization model of portfolio management into an unconstrained minimization problem, where the objective function is a piecewise quadratic polynomial. We presented some properties of such an objective function. Then, a class of penalty algorithms based on the well-known conjugate gradient methods was developed to find the solution of portfolio management problem. By implementing the proposed algorithm to solve the real problems from the stock market in China, it was shown that this algorithm is promising.

Frequency domain optical tomography using a conjugate gradient method without line search

International Nuclear Information System (INIS)

Kim, Hyun Keol; Charette, Andre

2007-01-01

A conjugate gradient method without line search (CGMWLS) is presented. This method is used to retrieve the local maps of absorption and scattering coefficients inside the tissue-like test medium, with the synthetic data. The forward problem is solved with a discrete-ordinates finite-difference method based on the frequency domain formulation of radiative transfer equation. The inversion results demonstrate that the CGMWLS can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by reducing cross-talk between absorption and scattering coefficients

Steepest descent method implementation on unconstrained optimization problem using C++ program

Science.gov (United States)

Napitupulu, H.; Sukono; Mohd, I. Bin; Hidayat, Y.; Supian, S.

2018-03-01

Steepest Descent is known as the simplest gradient method. Recently, many researches are done to obtain the appropriate step size in order to reduce the objective function value progressively. In this paper, the properties of steepest descent method from literatures are reviewed together with advantages and disadvantages of each step size procedure. The development of steepest descent method due to its step size procedure is discussed. In order to test the performance of each step size, we run a steepest descent procedure in C++ program. We implemented it to unconstrained optimization test problem with two variables, then we compare the numerical results of each step size procedure. Based on the numerical experiment, we conclude the general computational features and weaknesses of each procedure in each case of problem.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A constrained conjugate gradient algorithm for computed tomography

Energy Technology Data Exchange (ETDEWEB)

Azevedo, S.G.; Goodman, D.M. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

Image reconstruction from projections of x-ray, gamma-ray, protons and other penetrating radiation is a well-known problem in a variety of fields, and is commonly referred to as computed tomography (CT). Various analytical and series expansion methods of reconstruction and been used in the past to provide three-dimensional (3D) views of some interior quantity. The difficulties of these approaches lie in the cases where (a) the number of views attainable is limited, (b) the Poisson (or other) uncertainties are significant, (c) quantifiable knowledge of the object is available, but not implementable, or (d) other limitations of the data exist. We have adapted a novel nonlinear optimization procedure developed at LLNL to address limited-data image reconstruction problems. The technique, known as nonlinear least squares with general constraints or constrained conjugate gradients (CCG), has been successfully applied to a number of signal and image processing problems, and is now of great interest to the image reconstruction community. Previous applications of this algorithm to deconvolution problems and x-ray diffraction images for crystallography have shown the great promise.

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

Science.gov (United States)

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.

Stochastic Spectral Descent for Discrete Graphical Models

International Nuclear Information System (INIS)

Carlson, David; Hsieh, Ya-Ping; Collins, Edo; Carin, Lawrence; Cevher, Volkan

2015-01-01

Interest in deep probabilistic graphical models has in-creased in recent years, due to their state-of-the-art performance on many machine learning applications. Such models are typically trained with the stochastic gradient method, which can take a significant number of iterations to converge. Since the computational cost of gradient estimation is prohibitive even for modestly sized models, training becomes slow and practically usable models are kept small. In this paper we propose a new, largely tuning-free algorithm to address this problem. Our approach derives novel majorization bounds based on the Schatten- norm. Intriguingly, the minimizers of these bounds can be interpreted as gradient methods in a non-Euclidean space. We thus propose using a stochastic gradient method in non-Euclidean space. We both provide simple conditions under which our algorithm is guaranteed to converge, and demonstrate empirically that our algorithm leads to dramatically faster training and improved predictive ability compared to stochastic gradient descent for both directed and undirected graphical models.

Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm

International Nuclear Information System (INIS)

Grayaa, K.; Bouzidi, A.; Aguili, T.

2011-01-01

In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.

Generalized conjugate-gradient methods for the Navier-Stokes equations

Science.gov (United States)

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

1991-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images

Science.gov (United States)

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.

Identification techniques for phenomenological models of hysteresis based on the conjugate gradient method

International Nuclear Information System (INIS)

Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu

2007-01-01

An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented

Quality of Gaussian basis sets: direct optimization of orbital exponents by the method of conjugate gradients

International Nuclear Information System (INIS)

Kari, R.E.; Mezey, P.G.; Csizmadia, I.G.

1975-01-01

Expressions are given for calculating the energy gradient vector in the exponent space of Gaussian basis sets and a technique to optimize orbital exponents using the method of conjugate gradients is described. The method is tested on the (9/sups/5/supp/) Gaussian basis space and optimum exponents are determined for the carbon atom. The analysis of the results shows that the calculated one-electron properties converge more slowly to their optimum values than the total energy converges to its optimum value. In addition, basis sets approximating the optimum total energy very well can still be markedly improved for the prediction of one-electron properties. For smaller basis sets, this improvement does not warrant the necessary expense

A Framework for Generalized Conjugate Gradient Methods - with Special Emphasis on Contributions by Rüdiger Weiss

Czech Academy of Sciences Publication Activity Database

Gutknecht, M. H.; Rozložník, Miroslav

2002-01-01

Roč. 41, - (2002), s. 7-22 ISSN 0168-9274 R&D Projects: GA AV ČR IAA1030103; GA ČR GA101/00/1035 Institutional research plan: AV0Z1030915 Keywords : sparse linear systems * Krylov space method * orthogonal residual method * minimal residual method * conjugate gradient method * residual smoothing * CG * CGNE * CGNR * CR * FOM * GMRES * PRES Subject RIV: BA - General Mathematics Impact factor: 0.504, year: 2002

IMPROVED CONJUGATE GRADIENT BUNDLE ADJUSTMENT OF DUNHUANG WALL PAINTING IMAGES

Directory of Open Access Journals (Sweden)

K. Hu

2017-09-01

Full Text Available 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.

On Scalable Deep Learning and Parallelizing Gradient Descent

CERN Document Server

AUTHOR|(CDS)2129036; Möckel, Rico; Baranowski, Zbigniew; Canali, Luca

Speeding up gradient based methods has been a subject of interest over the past years with many practical applications, especially with respect to Deep Learning. Despite the fact that many optimizations have been done on a hardware level, the convergence rate of very large models remains problematic. Therefore, data parallel methods next to mini-batch parallelism have been suggested to further decrease the training time of parameterized models using gradient based methods. Nevertheless, asynchronous optimization was considered too unstable for practical purposes due to a lacking understanding of the underlying mechanisms. Recently, a theoretical contribution has been made which defines asynchronous optimization in terms of (implicit) momentum due to the presence of a queuing model of gradients based on past parameterizations. This thesis mainly builds upon this work to construct a better understanding why asynchronous optimization shows proportionally more divergent behavior when the number of parallel worker...

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

Science.gov (United States)

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

On Error Estimation in the Conjugate Gradient Method and why it Works in Finite Precision Computations

Czech Academy of Sciences Publication Activity Database

Strakoš, Zdeněk; Tichý, Petr

2002-01-01

Roč. 13, - (2002), s. 56-80 ISSN 1068-9613 R&D Projects: GA ČR GA201/02/0595 Institutional research plan: AV0Z1030915 Keywords : conjugate gradient method * Gauss kvadrature * evaluation of convergence * error bounds * finite precision arithmetic * rounding errors * loss of orthogonality Subject RIV: BA - General Mathematics Impact factor: 0.565, year: 2002 http://etna.mcs.kent.edu/volumes/2001-2010/vol13/abstract.php?vol=13&pages=56-80

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

Directory of Open Access Journals (Sweden)

Xiangrong Li

Full Text Available 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.

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

Science.gov (United States)

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.

Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures

Science.gov (United States)

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

Science.gov (United States)

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.

Identity of the conjugate gradient and Lanczos algorithms for matrix inversion in lattice fermion calculations

International Nuclear Information System (INIS)

Burkitt, A.N.; Irving, A.C.

1988-01-01

Two of the methods that are widely used in lattice gauge theory calculations requiring inversion of the fermion matrix are the Lanczos and the conjugate gradient algorithms. Those algorithms are already known to be closely related. In fact for matrix inversion, in exact arithmetic, they give identical results at each iteration and are just alternative formulations of a single algorithm. This equivalence survives rounding errors. We give the identities between the coefficients of the two formulations, enabling many of the best features of them to be combined. (orig.)

Inversion of the fermion matrix and the equivalence of the conjugate gradient and Lanczos algorithms

International Nuclear Information System (INIS)

Burkitt, A.N.; Irving, A.C.

1990-01-01

The Lanczos and conjugate gradient algorithms are widely used in lattice QCD calculations. The previously known close relationship between the two methods is explored and two commonly used implementations are shown to give identically the same results at each iteration, in exact arithmetic, for matrix inversion. The identities between the coefficients of the two algorithms are given, and many of the features of the two algorithms can now be combined. The effects of finite arithmetic are investigated and the particular Lanczos formulation is found to be most stable with respect to rounding errors. (orig.)

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

Science.gov (United States)

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.

Planning fuel-conservative descents in an airline environmental using a small programmable calculator: algorithm development and flight test results

Energy Technology Data Exchange (ETDEWEB)

Knox, C.E.; Vicroy, D.D.; Simmon, D.A.

1985-05-01

A simple, airborne, flight-management descent algorithm was developed and programmed into a small programmable calculator. The algorithm may be operated in either a time mode or speed mode. The time mode was designed to aid the pilot in planning and executing a fuel-conservative descent to arrive at a metering fix at a time designated by the air traffic control system. The speed model was designed for planning fuel-conservative descents when time is not a consideration. The descent path for both modes was calculated for a constant with considerations given for the descent Mach/airspeed schedule, gross weight, wind, wind gradient, and nonstandard temperature effects. Flight tests, using the algorithm on the programmable calculator, showed that the open-loop guidance could be useful to airline flight crews for planning and executing fuel-conservative descents.

Terrain reconstruction based on descent images for the Chang’e III landing area

Directory of Open Access Journals (Sweden)

Xu Xinchao

2015-10-01

Full Text Available A new method that combined image matching and shape from shading for terrain reconstruction was proposed to solve the lack of terrain in the landing area of Chang'e III. First, the reflection equation was established based on the Lommel– Seeliger reflection model. After edge extraction, the gradients of points on the edge were solved. The normal vectors of adjacent points were obtained using the smoothness constraint. Furthermore, the gradients of residual points in the image were determined through evolution. The inadequacy of the reflection equation was eliminated by considering the gradient as the constraint of the reflection equation. The normal vector of each point could be obtained by solving the reflection equation. The terrain without coordinate information was reconstructed by iterating the vector field. After using scaleinvariant feature transform to extract matching points in the descent images, the terrain was converted to a lander centroid coordinate system. Experiments were carried out with MATLAB-simulated images, laboratory images, and descent images of Chang'e III. Results show that the proposed method performs better than the classical SFS algorithm. The new method can provide reference for other deep space exploration activities.

The application of projected conjugate gradient solvers on graphical processing units

International Nuclear Information System (INIS)

Lin, Youzuo; Renaut, Rosemary

2011-01-01

Graphical processing units introduce the capability for large scale computation at the desktop. Presented numerical results verify that efficiencies and accuracies of basic linear algebra subroutines of all levels when implemented in CUDA and Jacket are comparable. But experimental results demonstrate that the basic linear algebra subroutines of level three offer the greatest potential for improving efficiency of basic numerical algorithms. We consider the solution of the multiple right hand side set of linear equations using Krylov subspace-based solvers. Thus, for the multiple right hand side case, it is more efficient to make use of a block implementation of the conjugate gradient algorithm, rather than to solve each system independently. Jacket is used for the implementation. Furthermore, including projection from one system to another improves efficiency. A relevant example, for which simulated results are provided, is the reconstruction of a three dimensional medical image volume acquired from a positron emission tomography scanner. Efficiency of the reconstruction is improved by using projection across nearby slices.

The application of projected conjugate gradient solvers on graphical processing units

Energy Technology Data Exchange (ETDEWEB)

Lin, Youzuo [Los Alamos National Laboratory; Renaut, Rosemary [ARIZONA STATE UNIV.

2011-01-26

Graphical processing units introduce the capability for large scale computation at the desktop. Presented numerical results verify that efficiencies and accuracies of basic linear algebra subroutines of all levels when implemented in CUDA and Jacket are comparable. But experimental results demonstrate that the basic linear algebra subroutines of level three offer the greatest potential for improving efficiency of basic numerical algorithms. We consider the solution of the multiple right hand side set of linear equations using Krylov subspace-based solvers. Thus, for the multiple right hand side case, it is more efficient to make use of a block implementation of the conjugate gradient algorithm, rather than to solve each system independently. Jacket is used for the implementation. Furthermore, including projection from one system to another improves efficiency. A relevant example, for which simulated results are provided, is the reconstruction of a three dimensional medical image volume acquired from a positron emission tomography scanner. Efficiency of the reconstruction is improved by using projection across nearby slices.

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

Science.gov (United States)

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).

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

Science.gov (United States)

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.

Acceleration of monte Carlo solution by conjugate gradient method

International Nuclear Information System (INIS)

Toshihisa, Yamamoto

2005-01-01

The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)

Fully 3D PET image reconstruction using a fourier preconditioned conjugate-gradient algorithm

International Nuclear Information System (INIS)

Fessler, J.A.; Ficaro, E.P.

1996-01-01

Since the data sizes in fully 3D PET imaging are very large, iterative image reconstruction algorithms must converge in very few iterations to be useful. One can improve the convergence rate of the conjugate-gradient (CG) algorithm by incorporating preconditioning operators that approximate the inverse of the Hessian of the objective function. If the 3D cylindrical PET geometry were not truncated at the ends, then the Hessian of the penalized least-squares objective function would be approximately shift-invariant, i.e. G'G would be nearly block-circulant, where G is the system matrix. We propose a Fourier preconditioner based on this shift-invariant approximation to the Hessian. Results show that this preconditioner significantly accelerates the convergence of the CG algorithm with only a small increase in computation

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

JAC, 2-D Finite Element Method Program for Quasi Static Mechanics Problems by Nonlinear Conjugate Gradient (CG) Method

International Nuclear Information System (INIS)

Biffle, J.H.

1991-01-01

1 - Description of program or function: JAC is a two-dimensional finite element program for solving large deformation, temperature dependent, quasi-static mechanics problems with the nonlinear conjugate gradient (CG) technique. Either plane strain or axisymmetric geometry may be used with material descriptions which include temperature dependent elastic-plastic, temperature dependent secondary creep, and isothermal soil models. The nonlinear effects examined include material and geometric nonlinearities due to large rotations, large strains, and surface which slide relative to one another. JAC is vectorized to perform efficiently on the Cray1 computer. A restart capability is included. 2 - Method of solution: The nonlinear conjugate gradient method is employed in a two-dimensional plane strain or axisymmetric setting with various techniques for accelerating convergence. Sliding interface conditions are also implemented. A four-node Lagrangian uniform strain element is used with orthogonal hourglass viscosity to control the zero energy modes. Three sets of continuum equations are needed - kinematic statements, constitutive equations, and equations of equilibrium - to describe the deformed configuration of the body. 3 - Restrictions on the complexity of the problem - Maxima of: 10 load and solution control functions, 4 materials. The strain rate is assumed constant over a time interval. Current large rotation theory is applicable to a maximum shear strain of 1.0. JAC should be used with caution for large shear strains. Problem size is limited only by available memory

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Numerical solution to a multi-dimensional linear inverse heat conduction problem by a splitting-based conjugate gradient method

International Nuclear Information System (INIS)

Dinh Nho Hao; Nguyen Trung Thanh; Sahli, Hichem

2008-01-01

In this paper we consider a multi-dimensional inverse heat conduction problem with time-dependent coefficients in a box, which is well-known to be severely ill-posed, by a variational method. The gradient of the functional to be minimized is obtained by aids of an adjoint problem and the conjugate gradient method with a stopping rule is then applied to this ill-posed optimization problem. To enhance the stability and the accuracy of the numerical solution to the problem we apply this scheme to the discretized inverse problem rather than to the continuous one. The difficulties with large dimensions of discretized problems are overcome by a splitting method which only requires the solution of easy-to-solve one-dimensional problems. The numerical results provided by our method are very good and the techniques seem to be very promising.

Random versus Deterministic Descent in RNA Energy Landscape Analysis

Directory of Open Access Journals (Sweden)

Luke Day

2016-01-01

Full Text Available Identifying sets of metastable conformations is a major research topic in RNA energy landscape analysis, and recently several methods have been proposed for finding local minima in landscapes spawned by RNA secondary structures. An important and time-critical component of such methods is steepest, or gradient, descent in attraction basins of local minima. We analyse the speed-up achievable by randomised descent in attraction basins in the context of large sample sets where the size has an order of magnitude in the region of ~106. While the gain for each individual sample might be marginal, the overall run-time improvement can be significant. Moreover, for the two nongradient methods we analysed for partial energy landscapes induced by ten different RNA sequences, we obtained that the number of observed local minima is on average larger by 7.3% and 3.5%, respectively. The run-time improvement is approximately 16.6% and 6.8% on average over the ten partial energy landscapes. For the large sample size we selected for descent procedures, the coverage of local minima is very high up to energy values of the region where the samples were randomly selected from the partial energy landscapes; that is, the difference to the total set of local minima is mainly due to the upper area of the energy landscapes.

Preconditioned conjugate-gradient methods for low-speed flow calculations

Science.gov (United States)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A general class of preconditioners for statistical iterative reconstruction of emission computed tomography

International Nuclear Information System (INIS)

Chinn, G.; Huang, S.C.

1997-01-01

A major drawback of statistical iterative image reconstruction for emission computed tomography is its high computational cost. The ill-posed nature of tomography leads to slow convergence for standard gradient-based iterative approaches such as the steepest descent or the conjugate gradient algorithm. In this paper new theory and methods for a class of preconditioners are developed for accelerating the convergence rate of iterative reconstruction. To demonstrate the potential of this class of preconditioners, a preconditioned conjugate gradient (PCG) iterative algorithm for weighted least squares reconstruction (WLS) was formulated for emission tomography. Using simulated positron emission tomography (PET) data of the Hoffman brain phantom, it was shown that the convergence rate of the PCG can reduce the number of iterations of the standard conjugate gradient algorithm by a factor of 2--8 times depending on the convergence criterion

A computationally efficient P_1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods

International Nuclear Information System (INIS)

Krishnamoorthy, Gautham

2017-01-01

Highlights: • The P_1 radiation model was interfaced with high performance linear solvers. • Pre-conditioned conjugate gradient (PC CG) method improved convergence by 50% • PC CG was more than 30 times faster than classical iterative methods. • The time to solution scaled linearly with increase in problem size employing PC CG. • Employing WSGGM with P_1 model compared reasonably well against benchmark data. - Abstract: The iterative convergence of the P_1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P_1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P_1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P_1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Further, PC provided 50% computational savings compared to employing CG in a standalone mode. The P_1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P_1 model provided good agreement against benchmark data with L_2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Regression Analysis of Top of Descent Location for Idle-thrust Descents

Science.gov (United States)

Stell, Laurel; Bronsvoort, Jesper; McDonald, Greg

2013-01-01

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. The independent variables cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also recorded or computed post-operations. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajec- tory parameters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowl- edge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace. In particular, a model for TOD location that is linear in the independent variables would enable decision support tool human-machine interfaces for which a kinetic approach would be computationally too slow.

Rationally Engineering Phototherapy Modules of Eosin-Conjugated Responsive Polymeric Nanocarriers via Intracellular Endocytic pH Gradients.

Science.gov (United States)

Liu, Guhuan; Hu, Jinming; Zhang, Guoying; Liu, Shiyong

2015-07-15

Spatiotemporal switching of respective phototherapy modes at the cellular level with minimum side effects and high therapeutic efficacy is a major challenge for cancer phototherapy. Herein we demonstrate how to address this issue by employing photosensitizer-conjugated pH-responsive block copolymers in combination with intracellular endocytic pH gradients. At neutral pH corresponding to extracellular and cytosol milieu, the copolymers self-assemble into micelles with prominently quenched fluorescence emission and low (1)O2 generation capability, favoring a highly efficient photothermal module. Under mildly acidic pH associated with endolysosomes, protonation-triggered micelle-to-unimer transition results in recovered emission and enhanced photodynamic (1)O2 efficiency, which synergistically actuates release of encapsulated drugs, endosomal escape, and photochemical internalization processes.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

2008-01-01

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.

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

Science.gov (United States)

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.

Optimization of gadolinium burnable poison loading by the conjugate gradients method

International Nuclear Information System (INIS)

Drumm, C.R.

1984-01-01

Improved use of burnable poison is suggested for pressurized water reactors (PWR's) to insure a sufficiently negative moderator temperature coefficient of reactivity for extended burnup cycles and low leakage refueling patterns. The use of gadolinium as a burnable poison can lead to large axial fluctuations in the power distribution through the cycle. The goal of this work is to determine the optimal axial distribution of gadolinium burnable poison in a PWR to overcome the axial fluctuations, yielding an improved power distribution. The conjugate gradients optimization method is used in this work because of the high degree of nonlinearity of the problem. The neutron diffusion and depletion equations are solved for a one-dimensional one-group core model. The state variables are the flux, the critical soluble boron concentration, and the burnup. The control variables are the number of gadolinium pins per assembly and the beginning-of-cycle gadolinium concentration, which determine the gadolinium cross section. Two separate objectives are considered: 1) to minimize the power peaking factor, which will minimize the capital cost of the plant; and 2) to maximize the cycle length, which will minimize the fuel cost for the plant. It is shown in this work that optimizing the gadolinium distribution can yield an improved power distribution

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

Science.gov (United States)

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.

Optimization algorithm based on densification and dynamic canonical descent

Science.gov (United States)

Bousson, K.; Correia, S. D.

2006-07-01

Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, which reduces the search space by means of densification curves, coupled with the dynamic canonical descent algorithm. The performances of the new method are shown on several known problems classically used for testing optimization algorithms, and proved to outperform competitive algorithms such as simulated annealing and genetic algorithms.

Conjugate gradient determination of optimal plane changes for a class of three-impulse transfers between noncoplanar circular orbits

Science.gov (United States)

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.

3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method

Directory of Open Access Journals (Sweden)

Jian-ke Qiang

2013-01-01

Full Text Available During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.

Solution to Two-Dimensional Steady Inverse Heat Transfer Problems with Interior Heat Source Based on the Conjugate Gradient Method

Directory of Open Access Journals (Sweden)

Shoubin Wang

2017-01-01

Full Text Available The compound variable inverse problem which comprises boundary temperature distribution and surface convective heat conduction coefficient of two-dimensional steady heat transfer system with inner heat source is studied in this paper applying the conjugate gradient method. The introduction of complex variable to solve the gradient matrix of the objective function obtains more precise inversion results. This paper applies boundary element method to solve the temperature calculation of discrete points in forward problems. The factors of measuring error and the number of measuring points zero error which impact the measurement result are discussed and compared with L-MM method in inverse problems. Instance calculation and analysis prove that the method applied in this paper still has good effectiveness and accuracy even if measurement error exists and the boundary measurement points’ number is reduced. The comparison indicates that the influence of error on the inversion solution can be minimized effectively using this method.

Cosmic Microwave Background Mapmaking with a Messenger Field

Science.gov (United States)

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.

Regularized variable metric method versus the conjugate gradient method in solution of radiative boundary design problem

International Nuclear Information System (INIS)

Kowsary, F.; Pooladvand, K.; Pourshaghaghy, A.

2007-01-01

In this paper, an appropriate distribution of the heating elements' strengths in a radiation furnace is estimated using inverse methods so that a pre-specified temperature and heat flux distribution is attained on the design surface. Minimization of the sum of the squares of the error function is performed using the variable metric method (VMM), and the results are compared with those obtained by the conjugate gradient method (CGM) established previously in the literature. It is shown via test cases and a well-founded validation procedure that the VMM, when using a 'regularized' estimator, is more accurate and is able to reach at a higher quality final solution as compared to the CGM. The test cases used in this study were two-dimensional furnaces filled with an absorbing, emitting, and scattering gas

An inverse hyperbolic heat conduction problem in estimating surface heat flux by the conjugate gradient method

International Nuclear Information System (INIS)

Huang, C.-H.; Wu, H.-H.

2006-01-01

In the present study an inverse hyperbolic heat conduction problem is solved by the conjugate gradient method (CGM) in estimating the unknown boundary heat flux based on the boundary temperature measurements. Results obtained in this inverse problem will be justified based on the numerical experiments where three different heat flux distributions are to be determined. Results show that the inverse solutions can always be obtained with any arbitrary initial guesses of the boundary heat flux. Moreover, the drawbacks of the previous study for this similar inverse problem, such as (1) the inverse solution has phase error and (2) the inverse solution is sensitive to measurement error, can be avoided in the present algorithm. Finally, it is concluded that accurate boundary heat flux can be estimated in this study

A TLBO based gradient descent learning-functional link higher order ANN: An efficient model for learning from non-linear data

Directory of Open Access Journals (Sweden)

Bighnaraj Naik

2018-01-01

Full Text Available All the higher order ANNs (HONNs including functional link ANN (FLANN are sensitive to random initialization of weight and rely on the learning algorithms adopted. Although a selection of efficient learning algorithms for HONNs helps to improve the performance, on the other hand, initialization of weights with optimized weights rather than random weights also play important roles on its efficiency. In this paper, the problem solving approach of the teaching learning based optimization (TLBO along with learning ability of the gradient descent learning (GDL is used to obtain the optimal set of weight of FLANN learning model. TLBO does not require any specific parameters rather it requires only some of the common independent parameters like number of populations, number of iterations and stopping criteria, thereby eliminating the intricacy in selection of algorithmic parameters for adjusting the set of weights of FLANN model. The proposed TLBO-FLANN is implemented in MATLAB and compared with GA-FLANN, PSO-FLANN and HS-FLANN. The TLBO-FLANN is tested on various 5-fold cross validated benchmark data sets from UCI machine learning repository and analyzed under the null-hypothesis by using Friedman test, Holm’s procedure and post hoc ANOVA statistical analysis (Tukey test & Dunnett test.

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

Science.gov (United States)

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.

Refined isogeometric analysis for a preconditioned conjugate gradient solver

KAUST Repository

Garcia, Daniel

2018-02-12

Starting from a highly continuous Isogeometric Analysis (IGA) discretization, refined Isogeometric Analysis (rIGA) introduces C0 hyperplanes that act as separators for the direct LU factorization solver. As a result, the total computational cost required to solve the corresponding system of equations using a direct LU factorization solver dramatically reduces (up to a factor of 55) Garcia et al. (2017). At the same time, rIGA enriches the IGA spaces, thus improving the best approximation error. In this work, we extend the complexity analysis of rIGA to the case of iterative solvers. We build an iterative solver as follows: we first construct the Schur complements using a direct solver over small subdomains (macro-elements). We then assemble those Schur complements into a global skeleton system. Subsequently, we solve this system iteratively using Conjugate Gradients (CG) with an incomplete LU (ILU) preconditioner. For a 2D Poisson model problem with a structured mesh and a uniform polynomial degree of approximation, rIGA achieves moderate savings with respect to IGA in terms of the number of Floating Point Operations (FLOPs) and computational time (in seconds) required to solve the resulting system of linear equations. For instance, for a mesh with four million elements and polynomial degree p=3, the iterative solver is approximately 2.6 times faster (in time) when applied to the rIGA system than to the IGA one. These savings occur because the skeleton rIGA system contains fewer non-zero entries than the IGA one. The opposite situation occurs for 3D problems, and as a result, 3D rIGA discretizations provide no gains with respect to their IGA counterparts when considering iterative solvers.

Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Theseus' arid Peirithoos' descent into the underworld

NARCIS (Netherlands)

Bremmer, Jan N.

2015-01-01

In my contribution I will first briefly discuss the earliest known literary descent, that by Enkidu, which almost certainly influenced the poet of the Odyssey in his depiction of Odysseus' descent. Then I will take a brief look at some descents in the Archaic Age, in particular the earliest

Embedding SAS approach into conjugate gradient algorithms for asymmetric 3D elasticity problems

Energy Technology Data Exchange (ETDEWEB)

Chen, Hsin-Chu; Warsi, N.A. [Clark Atlanta Univ., GA (United States); Sameh, A. [Univ. of Minnesota, Minneapolis, MN (United States)

1996-12-31

In this paper, we present two strategies to embed the SAS (symmetric-and-antisymmetric) scheme into conjugate gradient (CG) algorithms to make solving 3D elasticity problems, with or without global reflexive symmetry, more efficient. The SAS approach is physically a domain decomposition scheme that takes advantage of reflexive symmetry of discretized physical problems, and algebraically a matrix transformation method that exploits special reflexivity properties of the matrix resulting from discretization. In addition to offering large-grain parallelism, which is valuable in a multiprocessing environment, the SAS scheme also has the potential for reducing arithmetic operations in the numerical solution of a reasonably wide class of scientific and engineering problems. This approach can be applied directly to problems that have global reflexive symmetry, yielding smaller and independent subproblems to solve, or indirectly to problems with partial symmetry, resulting in loosely coupled subproblems. The decomposition is achieved by separating the reflexive subspace from the antireflexive one, possessed by a special class of matrices A, A {element_of} C{sup n x n} that satisfy the relation A = PAP where P is a reflection matrix (symmetric signed permutation matrix).

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

International Nuclear Information System (INIS)

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

2015-01-01

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 optimal 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

Computation of fields in an arbitrarily shaped heterogeneous dielectric or biological body by an iterative conjugate gradient method

International Nuclear Information System (INIS)

Wang, J.J.H.; Dubberley, J.R.

1989-01-01

Electromagnetic (EM) fields in a three-dimensional, arbitrarily shaped heterogeneous dielectric or biological body illuminated by a plane wave are computed by an iterative conjugate gradient method. The method is a generalized method of moments applied to the volume integral equation. Because no matrix is explicitly involved or stored, the present iterative method is capable of computing EM fields in objects an order of magnitude larger than those that can be handled by the conventional method of moments. Excellent numerical convergence is achieved. Perfect convergence to the result of the conventional moment method using the same basis and weighted with delta functions is consistently achieved in all the cases computed, indicating that these two algorithms (direct and interactive) are equivalent

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics

Science.gov (United States)

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.

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.

Science.gov (United States)

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.

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

Science.gov (United States)

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.

Accurate conjugate gradient methods for families of shifted systems

NARCIS (Netherlands)

Eshof, J. van den; Sleijpen, G.L.G.

2003-01-01

We consider the solution of the linear system (ATA + σI)xσ = ATb, for various real values of σ. This family of shifted systems arises, for example, in Tikhonov regularization and computations in lattice quantum chromodynamics. For each single shift σ this system can be solved using the conjugate

An accelerated conjugate gradient algorithm to compute low-lying eigenvalues - a study for the Dirac operator in SU(2) lattice QCD

International Nuclear Information System (INIS)

Kalkreuter, T.; Simma, H.

1995-07-01

The low-lying eigenvalues of a (sparse) hermitian matrix can be computed with controlled numerical errors by a conjugate gradient (CG) method. This CG algorithm is accelerated by alternating it with exact diagonalizations in the subspace spanned by the numerically computed eigenvectors. We study this combined algorithm in case of the Dirac operator with (dynamical) Wilson fermions in four-dimensional SU(2) gauge fields. The algorithm is numerically very stable and can be parallelized in an efficient way. On lattices of sizes 4 4 - 16 4 an acceleration of the pure CG method by a factor of 4 - 8 is found. (orig.)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Use of the preconditioned conjugate gradient method to accelerate S/sub n/ iterations

International Nuclear Information System (INIS)

Derstine, K.L.; Gelbard, E.M.

1985-01-01

It is well known that specially tailored diffusion difference equations are required in the synthetic method. The tailoring process is not trivial, and for some S/sub n/ schemes (e.g., in hexagonal geometry) tailored diffusion operators are not available. The need for alternative acceleration methods has been noted by Larsen who has, in fact, proposed two alternatives. The proposed methods, however, do not converge to the S/sub n/ solution, and their accuracy is still largely unknown. Los Alamos acceleration methods are required to converge for any mesh, no matter how coarse. Since negative flux-fix ups (normally involved when mesh widths are large) may impede convergence, it is not clear that such a strict condition is really practical. Here a lesser objective is chosen. The authors wish to develop an acceleration method useful for a wide (though finite) range of mesh widths, but to avoid the use of special diffusion difference equations. It is shown that the conjugate gradient (CG) method, with the standard box-centered (BC) diffusion equation as a preconditioner, yields an algorithm that, for fixed-source problems with isotropic scattering, is mechanically very similar to the synthetic method; but, in two-dimensional test problems in various geometries, the CG method is substantially more stable

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

Science.gov (United States)

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.

Penyelesaian Persamaan Poisson 2D dengan Menggunakan Metode Gauss-Seidel dan Conjugate Gradien

OpenAIRE

Mahmudah, Dewi Erla; Naf'an, Muhammad Zidny

2017-01-01

In this paper we focus on solution of 2D Poisson equation numerically. 2D Poisson equation is a partial differential equation of second order elliptical type. This equation is a particular form or non-homogeneous form of the Laplace equation. The solution of 2D Poisson equation is performed numerically using Gauss Seidel method and Conjugate Gradient method. The result is the value using Gauss Seidel method and Conjugate Gradient method is same. But, consider the iteration process, the conver...

Continuous Descent Operations using Energy Principles

NARCIS (Netherlands)

De Jong, P.M.A.

2014-01-01

During today’s aircraft descents, Air Traf?c Control (ATC) commands aircraft to descend to specific altitudes and directions to maintain separation and spacing from other aircraft. When the aircraft is instructed to maintain an intermediate descent altitude, it requires engine thrust to maintain

Efficient CUDA Polynomial Preconditioned Conjugate Gradient Solver for Finite Element Computation of Elasticity Problems

Directory of Open Access Journals (Sweden)

Jianfei Zhang

2013-01-01

Full Text Available Graphics processing unit (GPU has obtained great success in scientific computations for its tremendous computational horsepower and very high memory bandwidth. This paper discusses the efficient way to implement polynomial preconditioned conjugate gradient solver for the finite element computation of elasticity on NVIDIA GPUs using compute unified device architecture (CUDA. Sliced block ELLPACK (SBELL format is introduced to store sparse matrix arising from finite element discretization of elasticity with fewer padding zeros than traditional ELLPACK-based formats. Polynomial preconditioning methods have been investigated both in convergence and running time. From the overall performance, the least-squares (L-S polynomial method is chosen as a preconditioner in PCG solver to finite element equations derived from elasticity for its best results on different example meshes. In the PCG solver, mixed precision algorithm is used not only to reduce the overall computational, storage requirements and bandwidth but to make full use of the capacity of the GPU devices. With SBELL format and mixed precision algorithm, the GPU-based L-S preconditioned CG can get a speedup of about 7–9 to CPU-implementation.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Quarter-Sweep Iteration Concept on Conjugate Gradient Normal Residual Method via Second Order Quadrature - Finite Difference Schemes for Solving Fredholm Integro-Differential Equations

International Nuclear Information System (INIS)

Aruchunan, E.

2015-01-01

In this paper, we have examined the effectiveness of the quarter-sweep iteration concept on conjugate gradient normal residual (CGNR) iterative method by using composite Simpson's (CS) and finite difference (FD) discretization schemes in solving Fredholm integro-differential equations. For comparison purposes, Gauss- Seidel (GS) and the standard or full- and half-sweep CGNR methods namely FSCGNR and HSCGNR are also presented. To validate the efficacy of the proposed method, several analyses were carried out such as computational complexity and percentage reduction on the proposed and existing methods. (author)

Acceptable solutions obtained by unfolding noisy data with a conjugate gradient technique

International Nuclear Information System (INIS)

Lang, D.W.

1976-01-01

A linear resolution function in a physical measurement leads to data values and standard deviations at, say, N points. It is noted that the associated resolution functions may require that a number n of particular linear combinations of the data values be each not significantly different from zero. One is left with at most N-n parameters to evaluate. If the resolution functions are reasonably behaved, one can show that one sensible way to describe the underlying spectrum treats it as a linear combination of the given resolution functions and includes all the significant information from the data. An iterative search for the best component available to minimize the chi-square of the next fit to the data leads to a conjugate gradient technique. Programs based on the technique have been successfully used to obtain neutron spectra as a function of energy; in raw data from a pulse height analysis of proton recoils in a proportional counter, and where the raw data are time of flight spectra from a time dependent pulse of known form. It is planned to incorporate these, together with working programs respectively for photonuclear analysis and to explore the impurity concentration profile in a surface, into a single ''work-bench'' type program. A suitably difficult model unfolding problem has been developed and used to show the strengths and weaknesses of a number of other methods that have been used for unfolding

Flight Management System Execution of Idle-Thrust Descents in Operations

Science.gov (United States)

Stell, Laurel L.

2011-01-01

To enable arriving aircraft to fly optimized descents computed by the flight management system (FMS) in congested airspace, ground automation must accurately predict descent trajectories. To support development of the trajectory predictor and its error models, commercial flights executed idle-thrust descents, and the recorded data includes the target speed profile and FMS intent trajectories. The FMS computes the intended descent path assuming idle thrust after top of descent (TOD), and any intervention by the controllers that alters the FMS execution of the descent is recorded so that such flights are discarded from the analysis. The horizontal flight path, cruise and meter fix altitudes, and actual TOD location are extracted from the radar data. Using more than 60 descents in Boeing 777 aircraft, the actual speeds are compared to the intended descent speed profile. In addition, three aspects of the accuracy of the FMS intent trajectory are analyzed: the meter fix crossing time, the TOD location, and the altitude at the meter fix. The actual TOD location is within 5 nmi of the intent location for over 95% of the descents. Roughly 90% of the time, the airspeed is within 0.01 of the target Mach number and within 10 KCAS of the target descent CAS, but the meter fix crossing time is only within 50 sec of the time computed by the FMS. Overall, the aircraft seem to be executing the descents as intended by the designers of the onboard automation.

Gradient-type methods in inverse parabolic problems

International Nuclear Information System (INIS)

Kabanikhin, Sergey; Penenko, Aleksey

2008-01-01

This article is devoted to gradient-based methods for inverse parabolic problems. In the first part, we present a priori convergence theorems based on the conditional stability estimates for linear inverse problems. These theorems are applied to backwards parabolic problem and sideways parabolic problem. The convergence conditions obtained coincide with sourcewise representability in the self-adjoint backwards parabolic case but they differ in the sideways case. In the second part, a variational approach is formulated for a coefficient identification problem. Using adjoint equations, a formal gradient of an objective functional is constructed. A numerical test illustrates the performance of conjugate gradient algorithm with the formal gradient.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

1989-10-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Implementation of a conjugate gradient algorithm for thermal diffusivity identification in a moving boundaries system

International Nuclear Information System (INIS)

Perez, L; Autrique, L; Gillet, M

2008-01-01

The aim of this paper is to investigate the thermal diffusivity identification of a multilayered material dedicated to fire protection. In a military framework, fire protection needs to meet specific requirements, and operational protective systems must be constantly improved in order to keep up with the development of new weapons. In the specific domain of passive fire protections, intumescent coatings can be an effective solution on the battlefield. Intumescent materials have the ability to swell up when they are heated, building a thick multi-layered coating which provides efficient thermal insulation to the underlying material. Due to the heat aggressions (fire or explosion) leading to the intumescent phenomena, high temperatures are considered and prevent from linearization of the mathematical model describing the system state evolution. Previous sensitivity analysis has shown that the thermal diffusivity of the multilayered intumescent coating is a key parameter in order to validate the predictive numerical tool and therefore for thermal protection optimisation. A conjugate gradient method is implemented in order to minimise the quadratic cost function related to the error between predicted temperature and measured temperature. This regularisation algorithm is well adapted for a large number of unknown parameters.

A neural method for determining electromagnetic shower positions in laterally segmented calorimeters

International Nuclear Information System (INIS)

Roy, A.; Ray, A.; Mitra, T.; Roy, A.

1995-01-01

A method based on a neural network technique is proposed to calculate the coordinates of an incident photon striking a laterally segmented calorimeter and depositing shower energies in different segments. The technique uses a multilayer perceptron trained by back-propagation implemented through standard gradient descent followed by conjugate gradient algorithms and has been demonstrated with GEANT simulations of a BAF2 detector array. The position resolution results obtained by using this method are found to be substantially better than the first moment method with logarithmic weighting. (orig.)

Luteinizing hormone in testicular descent

DEFF Research Database (Denmark)

Toppari, Jorma; Kaleva, Marko M; Virtanen, Helena E

2007-01-01

alone is not sufficient for normal testicular descent. The regulation of androgen production is influenced both by placental human chorionic gonadotropin (hCG) and pituitary luteinizing hormone (LH). There is evidence that the longer pregnancy continues, the more important role pituitary LH may have....... Insulin-like hormone-3 (INSL3) is suggested to be the main regulator of gubernacular development and therefore an apparent regulator of testicular descent. INSL3 production is also related to LH, and reduced INSL3 action is a possible cause for cryptorchidism. Cryptorchid boys have normal testosterone...

Regularized image denoising based on spectral gradient optimization

International Nuclear Information System (INIS)

Lukić, Tibor; Lindblad, Joakim; Sladoje, Nataša

2011-01-01

Image restoration methods, such as denoising, deblurring, inpainting, etc, are often based on the minimization of an appropriately defined energy function. We consider energy functions for image denoising which combine a quadratic data-fidelity term and a regularization term, where the properties of the latter are determined by a used potential function. Many potential functions are suggested for different purposes in the literature. We compare the denoising performance achieved by ten different potential functions. Several methods for efficient minimization of regularized energy functions exist. Most are only applicable to particular choices of potential functions, however. To enable a comparison of all the observed potential functions, we propose to minimize the objective function using a spectral gradient approach; spectral gradient methods put very weak restrictions on the used potential function. We present and evaluate the performance of one spectral conjugate gradient and one cyclic spectral gradient algorithm, and conclude from experiments that both are well suited for the task. We compare the performance with three total variation-based state-of-the-art methods for image denoising. From the empirical evaluation, we conclude that denoising using the Huber potential (for images degraded by higher levels of noise; signal-to-noise ratio below 10 dB) and the Geman and McClure potential (for less noisy images), in combination with the spectral conjugate gradient minimization algorithm, shows the overall best performance

Application of a Gradient Descent Continuous Actor-Critic Algorithm for Double-Side Day-Ahead Electricity Market Modeling

Directory of Open Access Journals (Sweden)

Huiru Zhao

2016-09-01

Full Text Available An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs and demanders (represented by DisCOs compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP and each rival’s bidding strategy as common knowledge (in dynamic game market models, and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models, which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n. The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare

Scintillation Reduction using Conjugate-Plane Imaging (Abstract)

Science.gov (United States)

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.

An Efficient Approach for Solving Mesh Optimization Problems Using Newton’s Method

Directory of Open Access Journals (Sweden)

Jibum Kim

2014-01-01

Full Text Available We present an efficient approach for solving various mesh optimization problems. Our approach is based on Newton’s method, which uses both first-order (gradient and second-order (Hessian derivatives of the nonlinear objective function. The volume and surface mesh optimization algorithms are developed such that mesh validity and surface constraints are satisfied. We also propose several Hessian modification methods when the Hessian matrix is not positive definite. We demonstrate our approach by comparing our method with nonlinear conjugate gradient and steepest descent methods in terms of both efficiency and mesh quality.

Experience with the Incomplete Cholesky Conjugate Gradient method in a diffusion code

International Nuclear Information System (INIS)

Hoebel, W.

1985-01-01

For the numerical solution of sparse systems of linear equations arising from finite difference approximation of the multidimensional neutron diffusion equation fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version DIXY2 of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries an Incomplete Cholesky Conjugate Gradient (ICCG) algorithm has been combined with the originally implemented Cyclically Reduced 4-Lines SOR (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU-times on a scalar computer. In a follow-up benchmark study necessary modifications to ICCG and CR4LSOR for their use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the 9-band-matrix in two triangular Cholesky matrices necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-Seidel iteration is replaced by Double Jacobi and Buneman technique for a vector computer. Compared to single line blocking over the original mesh the cyclical 4-lines reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU-times considerably

Experience with the incomplete Cholesky conjugate gradient method in a diffusion code

International Nuclear Information System (INIS)

Hoebel, W.

1986-01-01

For the numerical solution of sparse systems of linear equations arising from the finite difference approximation of the multidimensional neutron diffusion equation, fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version (DIXY2) of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries, an incomplete Cholesky conjugate gradient (ICCG) algorithm has been combined with the originally implemented cyclically reduced four-line successive overrelaxation (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU times on a scalar computer. In a follow-up benchmark study, necessary modifications to ICCG and CR4LSOR for use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the nine-band matrix in two triangular Cholesky matrices, necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction, and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-eidel iteration is replaced by Double Jacobi and Buneman techniques for a vector computer. Compared to single-line blocking over the original mesh, the cyclical four-line reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU times considerably

Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient

Directory of Open Access Journals (Sweden)

ChunPing Ren

2017-01-01

Full Text Available We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering. Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm. The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME-NCG algorithm is available for identifying the random dynamic force due to smaller root mean-square-error (RMSE, lower restoration time, and fewer iterative steps. Example of engineering application shows that L-curve method is introduced which is better than Generalized Cross Validation (GCV method and is applied to select regularization parameter; thus the proposed algorithm can be helpful to alleviate the ill-conditioned problem in identification of dynamic force and to acquire an optimal solution of inverse problem in practical engineering.

Comparative performance of the conjugate gradient and SOR [Successive Over Relaxation] methods for computational thermal hydraulics

International Nuclear Information System (INIS)

King, J.B.; Anghaie, S.; Domanus, H.M.

1987-01-01

Finite difference approximations to the continuity, momentum, and energy equations in thermal hydraulics codes result in a system of N by N equations for a problem having N field points. In a three dimensional problem, N increases as the problem becomes larger or more complex, and more rapidly as the computational mesh size is reduced. As a consequence, the execution time required to solve the problem increases, which may lead to placing limits on the problem resolution or accuracy. A conventinal method of solution of these systems of equations is the Successive Over Relaxation (SOR) technique. However, for a wide range of problems the execution time may be reduced by using a more efficient linear equation solver. One such method is the conjugate gradient method which was implemented in COMMIX-1B thermal hydraulics code. It was found that the execution time required to solve the resulting system of equations was reduced by a factor of about 2 for some problems. This paper summarizes the characteristics of these iterative solution procedures and compares their performance in modeling of a variety of reactor thermal hydraulic problems, using the COMMIX-1B computer code

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-05-01

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

Gender difference in metacarpal descent of fifth metacarpal

International Nuclear Information System (INIS)

Rafique, A.; Ali, H.; Ghani, S.

2006-01-01

To determine the difference in metacarpal descent of fifth metacarpal between men and women. Skyline of the 2nd and 3rd metacarpals were used as reference line, from which the descent of the 5th metacarpal head was measured. The position of 5th metacarpal head was documented as angle X. Metacarpal descent was defined as the difference between angle 'X' in relaxed and clenched fist position. The relaxed position was standardized by placing the forearm, wrist and palm on a shaped woodblock such that the wrist would be held in 25 - 30 degree in extension by a triangular spur, supported the 3rd metacarpal only. It was ensured that the movement of 4th and 5th metacarpals were not impaired. Analysis of variance was performed to compare the significance of means between genders at p < 0.05 level of significance. Metacarpal descent of the 5th metacarpal of both hands was significantly greater for women, with a mean of 7 degree as compared with a mean of 4 degree for the men. This decrease in angle 'X' was significant for the right 5th metacarpal relaxed and fist position and the fist position on the left. In contrast, women showed no significant differences between the various age groups for any of the variables tested.There was no relationship between metacarpal descent and hand dominance.Difference in metacarpal descent between men and women is significant and must be kept in mind when hand function is evaluated in both genders to assess the outcome of treatment and rehabilitation. (author)

Seasonal variability and descent of mid-latitude sporadic E layers at Arecibo

Directory of Open Access Journals (Sweden)

N. Christakis

2009-03-01

Full Text Available Sporadic E layers (Es follow regular daily patterns in variability and altitude descent, which are determined primarily by the vertical tidal wind shears in the lower thermosphere. In the present study a large set of sporadic E layer incoherent scatter radar (ISR measurements are analyzed. These were made at Arecibo (Geog. Lat. ~18° N; Magnetic Dip ~50° over many years with ISR runs lasting from several hours to several days, covering evenly all seasons. A new methodology is applied, in which both weak and strong layers are clearly traced by using the vertical electron density gradient as a function of altitude and time. Taking a time base equal to the 24-h local day, statistics were obtained on the seasonal behavior of the diurnal and semidiurnal tidal variability and altitude descent patterns of sporadic E at Arecibo. The diurnal tide, most likely the S(1,1 tide with a vertical wavelength around 25 km, controls fully the formation and descent of the metallic Es layers at low altitudes below 110 km. At higher altitudes, there are two prevailing layers formed presumably by vertical wind shears associated mainly with semidiurnal tides. These include: 1 a daytime layer starting at ~130 km around midday and descending down to 105 km by local midnight, and 2 a less frequent and weaker nighttime layer which starts prior to midnight at ~130 km, descending downwards at somewhat faster rate to reach 110 km by sunrise. The diurnal and semidiurnal-like pattern prevails, with some differences, in all seasons. The differences in occurrence, strength and descending speeds between the daytime and nighttime upper layers are not well understood from the present data alone and require further study.

Integrated Targeting and Guidance for Powered Planetary Descent

Science.gov (United States)

Azimov, Dilmurat M.; Bishop, Robert H.

2018-02-01

This paper presents an on-board guidance and targeting design that enables explicit state and thrust vector control and on-board targeting for planetary descent and landing. These capabilities are developed utilizing a new closed-form solution for the constant thrust arc of the braking phase of the powered descent trajectory. The key elements of proven targeting and guidance architectures, including braking and approach phase quartics, are employed. It is demonstrated that implementation of the proposed solution avoids numerical simulation iterations, thereby facilitating on-board execution of targeting procedures during the descent. It is shown that the shape of the braking phase constant thrust arc is highly dependent on initial mass and propulsion system parameters. The analytic solution process is explicit in terms of targeting and guidance parameters, while remaining generic with respect to planetary body and descent trajectory design. These features increase the feasibility of extending the proposed integrated targeting and guidance design to future cargo and robotic landing missions.

Noise annoyance caused by continuous descent approaches compared to regular descent procedures

NARCIS (Netherlands)

White, K.; Arntzen, M.; Walker, F.; Waiyaki, F.M.; Meeter, M.; Bronkhorst, A.W.

2017-01-01

During Continuous Descent Approaches (CDAs) aircraft glide towards the runway resulting in reduced noise and fuel usage. Here, we investigated whether such landings cause less noise annoyance than a regular stepwise approach. Both landing types were compared in a controlled laboratory setting with a

Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace

Science.gov (United States)

Coopenbarger, Richard A.

2010-01-01

Continuous descents at low engine power are desired to reduce fuel consumption, emissions and noise during arrival operations. The challenge is to allow airplanes to fly these types of efficient descents without interruption during busy traffic conditions. During busy conditions today, airplanes are commonly forced to fly inefficient, step-down descents as airtraffic controllers work to ensure separation and maximize throughput. NASA in collaboration with government and industry partners is developing new automation to help controllers accommodate continuous descents in the presence of complex traffic and airspace constraints. This automation relies on accurate trajectory predictions to compute strategic maneuver advisories. The talk will describe the concept behind this new automation and provide an overview of the simulations and flight testing used to develop and refine its underlying technology.

ExoMars entry, descent and landing science

OpenAIRE

Ferri, F.; Lewis, S. R.; Withers, P.; Aboudan, A.; Bettanini, C.; Colombatti, G.; Debei, S.; Golombek, M.; Harri, A. M.; Komatsu, G.; Leese, M. R.; Mäkinen, T.; Müller-Wodarg, I.; Ori, G. G.; Patel, M. R.

2011-01-01

The entry, descent and landing of ExoMars offer a rare (once-per-mission) opportunity to perform in situ investigation of the martian environment over a wide altitude range. Entry, Descent and Landing System (EDLS) measurements can provide essential data for atmospheric scientific investigations.\\ud \\ud We intend to perform atmospheric science measurements by exploiting data from EDLS engineering sensors and exploiting their readings beyond the expected engineering information.

A finite element conjugate gradient FFT method for scattering

Science.gov (United States)

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.

Design of automation tools for management of descent traffic

Science.gov (United States)

Erzberger, Heinz; Nedell, William

1988-01-01

The design of an automated air traffic control system based on a hierarchy of advisory tools for controllers is described. Compatibility of the tools with the human controller, a key objective of the design, is achieved by a judicious selection of tasks to be automated and careful attention to the design of the controller system interface. The design comprises three interconnected subsystems referred to as the Traffic Management Advisor, the Descent Advisor, and the Final Approach Spacing Tool. Each of these subsystems provides a collection of tools for specific controller positions and tasks. This paper focuses primarily on the Descent Advisor which provides automation tools for managing descent traffic. The algorithms, automation modes, and graphical interfaces incorporated in the design are described. Information generated by the Descent Advisor tools is integrated into a plan view traffic display consisting of a high-resolution color monitor. Estimated arrival times of aircraft are presented graphically on a time line, which is also used interactively in combination with a mouse input device to select and schedule arrival times. Other graphical markers indicate the location of the fuel-optimum top-of-descent point and the predicted separation distances of aircraft at a designated time-control point. Computer generated advisories provide speed and descent clearances which the controller can issue to aircraft to help them arrive at the feeder gate at the scheduled times or with specified separation distances. Two types of horizontal guidance modes, selectable by the controller, provide markers for managing the horizontal flightpaths of aircraft under various conditions. The entire system consisting of descent advisor algorithm, a library of aircraft performance models, national airspace system data bases, and interactive display software has been implemented on a workstation made by Sun Microsystems, Inc. It is planned to use this configuration in operational

A sensitivity function-based conjugate gradient method for optical tomography with the frequency-domain equation of radiative transfer

International Nuclear Information System (INIS)

Kim, Hyun Keol; Charette, Andre

2007-01-01

The Sensitivity Function-based Conjugate Gradient Method (SFCGM) is described. This method is used to solve the inverse problems of function estimation, such as the local maps of absorption and scattering coefficients, as applied to optical tomography for biomedical imaging. A highly scattering, absorbing, non-reflecting, non-emitting medium is considered here and simultaneous reconstructions of absorption and scattering coefficients inside the test medium are achieved with the proposed optimization technique, by using the exit intensity measured at boundary surfaces. The forward problem is solved with a discrete-ordinates finite-difference method on the framework of the frequency-domain full equation of radiative transfer. The modulation frequency is set to 600 MHz and the frequency data, obtained with the source modulation, is used as the input data. The inversion results demonstrate that the SFCGM can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by significantly reducing a cross-talk between inter-parameters. It is also observed that the closer-to-detector objects are better retrieved

Conjugated heat transfer in laminar flow between parallel-plates channel

International Nuclear Information System (INIS)

Guedes, R.O.C.; Cotta, R.M.; Brum, N.C.L.

1989-01-01

An analysis is made of conjugated convective-conductive heat transfer in laminar flow of a newtonian fluid between parallel-plates channel, taking into account the longitudinal conduction along the duct walls only, by neglecting the transversal temperature gradients in the solid. This extended Graetz-type problem is then analytically handled through the generalized integral transform technique, providing accurate numerical results for quantities of practical interest sucyh as bulk and wall temperatures, and Nusselt numbers. The effects of a conjugation parameter and Biot number on heat transfer behavior are then investigated. (author)

Energy minimization in medical image analysis: Methodologies and applications.

Science.gov (United States)

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.

Final descent for CMS

CERN Multimedia

The 15th and last section of the CMS detector was lowered on Tuesday 22 January. The YE-1 endcap (1430 tonnes) began its 100-metre descent at 7 am and arrived gently on the floor of the experiment hall at 5.30 pm.

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

Science.gov (United States)

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.

A detailed survey of numerical methods for unconstrained minimization. Pt. 1

International Nuclear Information System (INIS)

Mika, K.; Chaves, T.

1980-01-01

A detailed description of numerical methods for unconstrained minimization is presented. This first part surveys in particular conjugate direction and gradient methods, whereas variable metric methods will be the subject of the second part. Among the results of special interest we quote the following. The conjugate direction methods of Powell, Zangwill and Sutti can be best interpreted if the Smith approach is adopted. The conditions for quadratic termination of Powell's first procedure are analyzed. Numerical results based on nonlinear least squares problems are presented for the following conjugate direction codes: VA04AD from Harwell Subroutine Library and ZXPOW from IMSL, both implementations of Powell's second procedure, DFMND from IBM-SILMATH (Zangwill's method) and Brent's algorithm PRAXIS. VA04AD turns out to be superior in all cases, PRAXIS improves for high-dimensional problems. All codes clearly exhibit superlinear convergence. Akaike's result for the method of steepest descent is derived directly from a set of nonlinear recurrence relations. Numerical results obtained with the highly ill conditioned Hilbert function confirm the theoretical predictions. Several properties of the conjugate gradient method are presented and a new derivation of the equivalence of steepest descent partan and the CG method is given. A comparison of numerical results from the CG codes VA08AD (Fletcher-Reeves), DFMCG (the SSP version of the Fletcher-Reevens algorithm) and VA14AD (Powell's implementation of the Polak-Ribiere formula) reveals that VA14AD is clearly superior in all cases, but that the convergence rate of these codes is only weakly superlinear such that high accuracy solutions require extremely large numbers of function calls. (orig.)

A nonrecursive order N preconditioned conjugate gradient: Range space formulation of MDOF dynamics

Science.gov (United States)

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.

Antibody-radioisotope conjugates for tumor localization and treatment

International Nuclear Information System (INIS)

Larson, S.M.; Carrasquillo, J.A.

1985-01-01

In principle, anti-tumor antibodies can be used to carry radioactivity to tumors for in-vivo diagnosis and treatment of cancer. First, for diagnostic purposes, an antibody that targets a specific antigen (for example, the p97 antigen of human melanoma tumor), is labeled with a tracer amount of radioactivity. When this antibody-radioisotope conjugate is injected into the blood stream, the antibody carries the radioactivity throughout the body and in time, percolates through all the tissues of the body. Because the tumor has specific antigens to which the antibody can bind, the antibody conjugate progressively accumulates in the tumor. Using conventional nuclear medicine imaging equipment, the body of the patient is scanned for radioactivity content, and a map of the distribution of the radioactivity is displayed on photographic film. The tumor shows up as a dense area of radio-activity. These same antibody-radioisotope conjugates may be used for therapy of tumors, except that in this case large amounts of radioactivity are loaded on the antibody. After localization of the conjugate there is sufficient radiation deposited in the tumor of radiotherapy. The success of this approach in the clinic is determined in large measure by the concentration gradient that can be achieved between tissue antibody conjugate in tumor versus normal tissue

Further Applications of Sector-Based Detection and Short-Term Clustering

OpenAIRE

Lathoud, Guillaume

2006-01-01

This paper presents an effective implementation of detection-localization of multiple speech sources with microphone arrays. In particular, the Scaled Conjugate Gradient descent is used for fast and precise localization, within a pre-detected volume of space. The approach is fit for real-time implementation. An unsupervised approach to speech/non-speech discrimination is also proposed. The integrated system is then successfully applied to segmentation of spontaneous multi-party speech, as fou...

43 CFR 10.14 - Lineal descent and cultural affiliation.

Science.gov (United States)

2010-10-01

... Hawaiian organization and the human remains, funerary objects, sacred objects, or objects of cultural... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Lineal descent and cultural affiliation... GRAVES PROTECTION AND REPATRIATION REGULATIONS General § 10.14 Lineal descent and cultural affiliation...

LA GRANDE DESCENTE

CERN Multimedia

The first endcap disc of CMS being lowered slowly and carefully 100 m underground into the experimental cavern. The disc is one of 15 large pieces to make the grand descent.  The uniquely shaped slice, 16 m high, about 50 cm thick weighs 400 tonnes. The two HF that were lowered earlier in November can also be seen in the foreground and background.  

Development and descent of the testis in relation to cryptorchidism

DEFF Research Database (Denmark)

Virtanen, Helena E; Cortes, Dina; Rajpert-De Meyts, Ewa

2007-01-01

The testis descends in two phases. Animal studies suggest, that the transabdominal descent of the testis depends on the insulin-like hormone 3 (INSL3). Androgens are important in the inguinoscrotal testicular descent in animals and humans. In general, the cause of cryptorchidism is unknown...... and the aetiology is possibly multifactorial. Histological changes in cryptorchid testes demonstrate disturbed development. Conclusion: Since testicular descent is regulated by testis-derived hormones, cryptorchidism may reflect a functional defect of the testis....

Purification Efficacy of Synthetic Cannabinoid Conjugates Using High-Pressure Liquid Chromatography

Science.gov (United States)

conducted using high-pressure liquid chromatography and gradient screens to determine the most effective means of purifying the SC:dark quencher conjugates...to obtain the highest yields and purity. The purity was verified using liquid chromatographycoupled mass spectroscopy and nuclear magnetic resonance.

A Study on GPU Computing of Bi-conjugate Gradient Method for Finite Element Analysis of the Incompressible Navier-Stokes Equations

International Nuclear Information System (INIS)

Yoon, Jong Seon; Choi, Hyoung Gwon; Jeon, Byoung Jin; Jung, Hye Dong

2016-01-01

A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

A Study on GPU Computing of Bi-conjugate Gradient Method for Finite Element Analysis of the Incompressible Navier-Stokes Equations

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jong Seon; Choi, Hyoung Gwon [Seoul Nat’l Univ. of Science and Technology, Seoul (Korea, Republic of); Jeon, Byoung Jin [Yonsei Univ., Seoul (Korea, Republic of); Jung, Hye Dong [Korea Electronics Technology Institute, Seongnam (Korea, Republic of)

2016-09-15

A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

Studies of the hormonal control of postnatal testicular descent in the rat.

Science.gov (United States)

Spencer, J R; Vaughan, E D; Imperato-McGinley, J

1993-03-01

Dihydrotestosterone is believed to control the transinguinal phase of testicular descent based on hormonal manipulation studies performed in postnatal rats. In the present study, these hormonal manipulation experiments were repeated, and the results were compared with those obtained using the antiandrogens flutamide and cyproterone acetate. 17 beta-estradiol completely blocked testicular descent, but testosterone and dihydrotestosterone were equally effective in reversing this inhibition. Neither flutamide nor cyproterone acetate prevented testicular descent in postnatal rats despite marked peripheral antiandrogenic action. Further analysis of the data revealed a correlation between testicular size and descent. Androgen receptor blockade did not produce a marked reduction in testicular size and consequently did not prevent testicular descent, whereas estradiol alone caused marked testicular atrophy and testicular maldescent. Reduction of the estradiol dosage or concomitant administration of androgens or human chorionic gonadotropin resulted in both increased testicular size and degree of descent. These data suggest that growth of the neonatal rat testis may contribute to its passage into the scrotum.

Controlled time of arrival windows for already initiated energy-neutral continuous descent operations

OpenAIRE

Dalmau Codina, Ramon; Prats Menéndez, Xavier

2017-01-01

Continuous descent operations with controlled times of arrival at one or several metering fixes could enable environmentally friendly procedures without compromising terminal airspace capacity. This paper focuses on controlled time of arrival updates once the descent has been already initiated, assessing the feasible time window (and associated fuel consumption) of continuous descent operations requiring neither thrust nor speed-brake usage along the whole descent (i.e. only elevator control ...

Entry, Descent, and Landing With Propulsive Deceleration

Science.gov (United States)

Palaszewski, Bryan

2012-01-01

The future exploration of the Solar System will require innovations in transportation and the use of entry, descent, and landing (EDL) systems at many planetary landing sites. The cost of space missions has always been prohibitive, and using the natural planetary and planet s moons atmospheres for entry, descent, and landing can reduce the cost, mass, and complexity of these missions. This paper will describe some of the EDL ideas for planetary entry and survey the overall technologies for EDL that may be attractive for future Solar System missions.

Optimal Allocation of Thermal-Electric Decoupling Systems Based on the National Economy by an Improved Conjugate Gradient Method

Directory of Open Access Journals (Sweden)

Shuang Rong

2015-12-01

Full Text Available Aiming to relieve the large amount of wind power curtailment during the heating period in the North China region, a thermal-electric decoupling (TED approach is proposed to both bring down the constraint of forced power output of combined heat and power plants and increase the electric load level during valley load times that assist the power grid in consuming more wind power. The operating principles of the thermal-electric decoupling approach is described, the mathematical model of its profits is developed, the constraint conditions of its operation are listed, also, an improved parallel conjugate gradient is utilized to bypass the saddle problem and accelerate the optimal speed. Numerical simulations are implemented and reveal an optimal allocation of TED which with a rated power of 280 MW and 185 MWh heat storage capacity are possible. This allocation of TED could bring approximately 16.9 billion Yuan of economic profit and consume more than 80% of the surplus wind energy which would be curtailed without the participation of TED. The results in this article verify the effectiveness of this method that could provide a referential guidance for thermal-electric decoupling system allocation in practice.

Solar multi-conjugate adaptive optics performance improvement

Science.gov (United States)

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.

Management and Nonlinear Analysis of Disinfection System of Water Distribution Networks Using Data Driven Methods

Directory of Open Access Journals (Sweden)

Mohammad Zounemat-Kermani

2018-03-01

Full Text Available Chlorination unit is widely used to supply safe drinking water and removal of pathogens from water distribution networks. Data-driven approach is one appropriate method for analyzing performance of chlorine in water supply network. In this study, multi-layer perceptron neural network (MLP with three training algorithms (gradient descent, conjugate gradient and BFGS and support vector machine (SVM with RBF kernel function were used to predict the concentration of residual chlorine in water supply networks of Ahmadabad Dafeh and Ahruiyeh villages in Kerman Province. Daily data including discharge (flow, chlorine consumption and residual chlorine were employed from the beginning of 1391 Hijri until the end of 1393 Hijri (for 3 years. To assess the performance of studied models, the criteria such as Nash-Sutcliffe efficiency (NS, root mean square error (RMSE, mean absolute percentage error (MAPE and correlation coefficient (CORR were used that in best modeling situation were 0.9484, 0.0255, 1.081, and 0.974 respectively which resulted from BFGS algorithm. The criteria indicated that MLP model with BFGS and conjugate gradient algorithms were better than all other models in 90 and 10 percent of cases respectively; while the MLP model based on gradient descent algorithm and the SVM model were better in none of the cases. According to the results of this study, proper management of chlorine concentration can be implemented by predicted values of residual chlorine in water supply network. Thus, decreased performance of perceptron network and support vector machine in water supply network of Ahruiyeh in comparison to Ahmadabad Dafeh can be inferred from improper management of chlorination.

Evolutionary analyses of non-genealogical bonds produced by introgressive descent.

Science.gov (United States)

Bapteste, Eric; Lopez, Philippe; Bouchard, Frédéric; Baquero, Fernando; McInerney, James O; Burian, Richard M

2012-11-06

All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages. However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particular evolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material of a particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressive descent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds of evolutionary units, of which five involve mosaic lineages generated by introgressive descent. To facilitate detection of these units in resemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, and suggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond that is orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of these evolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g., the relations among evolutionary players in very early phases of evolutionary history, the origin and emergence of novelties, and the production of new lineages). This line of research will expand the study of biological complexity beyond the usual genealogical bonds, revealing additional sources of biodiversity. It provides an important step to a more realistic pluralist treatment of evolutionary complexity.

Enumerating set partitions according to the number of descents of ...

Indian Academy of Sciences (India)

) according to the number of descents of size or more, where ≥ 1 is fixed. An explicit expression in terms of Stirling numbers of the second kind may be given for the total number of such descents in all the members of (,). We also ...

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

Science.gov (United States)

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.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

Science.gov (United States)

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.

Testicular descent: INSL3, testosterone, genes and the intrauterine milieu

DEFF Research Database (Denmark)

Bay, Katrine; Main, Katharina M; Toppari, Jorma

2011-01-01

Complete testicular descent is a sign of, and a prerequisite for, normal testicular function in adult life. The process of testis descent is dependent on gubernacular growth and reorganization, which is regulated by the Leydig cell hormones insulin-like peptide 3 (INSL3) and testosterone. Investi...

A systematic approach to robust preconditioning for gradient-based inverse scattering algorithms

International Nuclear Information System (INIS)

Nordebo, Sven; Fhager, Andreas; Persson, Mikael; Gustafsson, Mats

2008-01-01

This paper presents a systematic approach to robust preconditioning for gradient-based nonlinear inverse scattering algorithms. In particular, one- and two-dimensional inverse problems are considered where the permittivity and conductivity profiles are unknown and the input data consist of the scattered field over a certain bandwidth. A time-domain least-squares formulation is employed and the inversion algorithm is based on a conjugate gradient or quasi-Newton algorithm together with an FDTD-electromagnetic solver. A Fisher information analysis is used to estimate the Hessian of the error functional. A robust preconditioner is then obtained by incorporating a parameter scaling such that the scaled Fisher information has a unit diagonal. By improving the conditioning of the Hessian, the convergence rate of the conjugate gradient or quasi-Newton methods are improved. The preconditioner is robust in the sense that the scaling, i.e. the diagonal Fisher information, is virtually invariant to the numerical resolution and the discretization model that is employed. Numerical examples of image reconstruction are included to illustrate the efficiency of the proposed technique

JAC2D: A two-dimensional finite element computer program for the nonlinear quasi-static response of solids with the conjugate gradient method

International Nuclear Information System (INIS)

Biffle, J.H.; Blanford, M.L.

1994-05-01

JAC2D is a two-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equations. The method is implemented in a two-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. A four-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic/plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere

JAC3D -- A three-dimensional finite element computer program for the nonlinear quasi-static response of solids with the conjugate gradient method

International Nuclear Information System (INIS)

Biffle, J.H.

1993-02-01

JAC3D is a three-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equation. The method is implemented in a three-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. An eight-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic-plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere

Evaluation of vertical profiles to design continuous descent approach procedure

Science.gov (United States)

Pradeep, Priyank

The current research focuses on predictability, variability and operational feasibility aspect of Continuous Descent Approach (CDA), which is among the key concepts of the Next Generation Air Transportation System (NextGen). The idle-thrust CDA is a fuel economical, noise and emission abatement procedure, but requires increased separation to accommodate for variability and uncertainties in vertical and speed profiles of arriving aircraft. Although a considerable amount of researches have been devoted to the estimation of potential benefits of the CDA, only few have attempted to explain the predictability, variability and operational feasibility aspect of CDA. The analytical equations derived using flight dynamics and Base of Aircraft and Data (BADA) Total Energy Model (TEM) in this research gives insight into dependency of vertical profile of CDA on various factors like wind speed and gradient, weight, aircraft type and configuration, thrust settings, atmospheric factors (deviation from ISA (DISA), pressure and density of the air) and descent speed profile. Application of the derived equations to idle-thrust CDA gives an insight into sensitivity of its vertical profile to multiple factors. This suggests fixed geometric flight path angle (FPA) CDA has higher degree of predictability and lesser variability at the cost of non-idle and low thrust engine settings. However, with optimized design this impact can be overall minimized. The CDA simulations were performed using Future ATM Concept Evaluation Tool (FACET) based on radar-track and aircraft type data (BADA) of the real air-traffic to some of the busiest airports in the USA (ATL, SFO and New York Metroplex (JFK, EWR and LGA)). The statistical analysis of the vertical profiles of CDA shows 1) mean geometric FPAs derived from various simulated vertical profiles are consistently shallower than 3° glideslope angle and 2) high level of variability in vertical profiles of idle-thrust CDA even in absence of

Conjugate heat transfer effects on wall bubble nucleation in subcooled flashing flows

International Nuclear Information System (INIS)

Peterson, P.F.; Hijikata, K.

1990-01-01

A variety of models have been proposed to explain observations that large liquid superheat is required to initiate nucleation in flashing flows of subcooled liquids in nozzles, cracks and pipes. In such flows an abrupt change in the fluid temperature occurs downstream of the nucleating cavities. This paper examines the subcooling of the nucleating cavities due to conjugate heat transfer to the cold downstream fluid. This examination suggests a mechanism limiting the maximum active cavity size. Simple analysis shows that, of the total superheat required to initiate flashing, a substantial portion results from conjugate wall subcooling, which decreases the cavity vapor pressure. The specific case of flashing critical nozzle flow is examined in detail. Here boundary-layer laminarization due to the strong favorable pressure gradient aids the analysis of conjugate heat transfer

Crosswind Shear Gradient Affect on Wake Vortices

Science.gov (United States)

Proctor, Fred H.; Ahmad, Nashat N.

2011-01-01

Parametric simulations with a Large Eddy Simulation (LES) model are used to explore the influence of crosswind shear on aircraft wake vortices. Previous studies based on field measurements, laboratory experiments, as well as LES, have shown that the vertical gradient of crosswind shear, i.e. the second vertical derivative of the environmental crosswind, can influence wake vortex transport. The presence of nonlinear vertical shear of the crosswind velocity can reduce the descent rate, causing a wake vortex pair to tilt and change in its lateral separation. The LES parametric studies confirm that the vertical gradient of crosswind shear does influence vortex trajectories. The parametric results also show that vortex decay from the effects of shear are complex since the crosswind shear, along with the vertical gradient of crosswind shear, can affect whether the lateral separation between wake vortices is increased or decreased. If the separation is decreased, the vortex linking time is decreased, and a more rapid decay of wake vortex circulation occurs. If the separation is increased, the time to link is increased, and at least one of the vortices of the vortex pair may have a longer life time than in the case without shear. In some cases, the wake vortices may never link.

Hazard avoidance via descent images for safe landing

Science.gov (United States)

Yan, Ruicheng; Cao, Zhiguo; Zhu, Lei; Fang, Zhiwen

2013-10-01

In planetary or lunar landing missions, hazard avoidance is critical for landing safety. Therefore, it is very important to correctly detect hazards and effectively find a safe landing area during the last stage of descent. In this paper, we propose a passive sensing based HDA (hazard detection and avoidance) approach via descent images to lower the landing risk. In hazard detection stage, a statistical probability model on the basis of the hazard similarity is adopted to evaluate the image and detect hazardous areas, so that a binary hazard image can be generated. Afterwards, a safety coefficient, which jointly utilized the proportion of hazards in the local region and the inside hazard distribution, is proposed to find potential regions with less hazards in the binary hazard image. By using the safety coefficient in a coarse-to-fine procedure and combining it with the local ISD (intensity standard deviation) measure, the safe landing area is determined. The algorithm is evaluated and verified with many simulated descent downward looking images rendered from lunar orbital satellite images.

THE GREAT DESCENT CONTINUES

CERN Document Server

    With precise coordination YE+1 was lowered into the cavern (9-Jan), soon joined by the ?rst barrel wheel YB+2 (19-Jan), then YB+1(4-Feb) and HB+ (13-Feb). The 1920 ton central barrel wheel YB0 rests brie?y on the pit-head cover in anticipation of a monumental descent (28-Feb) that will also trigger an intense campaign of installation of services and detectors underground.  

Propulsive Descent Technologies (PDT): Original Content Project

Data.gov (United States)

National Aeronautics and Space Administration — Future missions to Mars require landed mass that exceeds the capability of current entry, descent, and landing technology.  New technology and techniques are...

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

Science.gov (United States)

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.

Wavelet methods in multi-conjugate adaptive optics

International Nuclear Information System (INIS)

Helin, T; Yudytskiy, M

2013-01-01

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. (paper)

Dictionary descent in optimization

OpenAIRE

Temlyakov, Vladimir

2015-01-01

The problem of convex optimization is studied. Usually in convex optimization the minimization is over a d-dimensional domain. Very often the convergence rate of an optimization algorithm depends on the dimension d. The algorithms studied in this paper utilize dictionaries instead of a canonical basis used in the coordinate descent algorithms. We show how this approach allows us to reduce dimensionality of the problem. Also, we investigate which properties of a dictionary are beneficial for t...

Additive genetic variation in schizophrenia risk is shared by populations of African and European descent

NARCIS (Netherlands)

De Candia, T.r.; Lee, S.H.; Yang, J.; Browning, B.L.; Gejman, P. V.; Levinson, D. F.; Mowry, B. J.; Hewitt, J.K.; Goddard, M.E.; O'Donovan, M.C.; Purcell, S.M.; Posthuma, D.; Visscher, P. M.; Wray, N.R.; Keller, M. C.

2013-01-01

To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control

Analysis of foot clearance in firefighters during ascent and descent of stairs.

Science.gov (United States)

Kesler, Richard M; Horn, Gavin P; Rosengren, Karl S; Hsiao-Wecksler, Elizabeth T

2016-01-01

Slips, trips, and falls are a leading cause of injury to firefighters with many injuries occurring while traversing stairs, possibly exaggerated by acute fatigue from firefighting activities and/or asymmetric load carriage. This study examined the effects that fatigue, induced by simulated firefighting activities, and hose load carriage have on foot clearance while traversing stairs. Landing and passing foot clearances for each stair during ascent and descent of a short staircase were investigated. Clearances decreased significantly (p < 0.05) post-exercise for nine of 12 ascent parameters and increased for two of eight descent parameters. Load carriage resulted in significantly decreased (p < 0.05) clearance over three ascent parameters, and one increase during descent. Decreased clearances during ascent caused by fatigue or load carriage may result in an increased trip risk. Increased clearances during descent may suggest use of a compensation strategy to ensure stair clearance or an increased risk of over-stepping during descent. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Steepest descent approximations for accretive operator equations

International Nuclear Information System (INIS)

Chidume, C.E.

1993-03-01

A necessary and sufficient condition is established for the strong convergence of the steepest descent approximation to a solution of equations involving quasi-accretive operators defined on a uniformly smooth Banach space. (author). 49 refs

Ground reaction forces and frictional demands during stair descent: effects of age and illumination.

Science.gov (United States)

Christina, Kathryn A; Cavanagh, Peter R

2002-04-01

Stair descent is an inherently risky and demanding task that older adults often encounter in everyday life. It is believed that slip between the foot or shoe sole and the stair surface may play a role in stair related falls, however, there are no reports on slip resistance requirements for stair descent. The aim of this study was to determine the required coefficient of friction (RCOF) necessary for safe stair descent in 12 young and 12 older adults, under varied illuminance conditions. The RCOF during stair descent was found to be comparable in magnitude and time to that for overground walking, and thus, with adequate footwear and dry stair surfaces, friction does not appear to be a major determinant of stair safety. Illuminance level had little effect on the dependent variables quantified in this study. However, the older participants demonstrated safer strategies than the young during stair descent, as reflected by differences in the ground reaction forces and lower RCOF.

Frequency-domain full-waveform inversion with non-linear descent directions

Science.gov (United States)

Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.

2018-05-01

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. We examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss-Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s0 is, in our scheme, proportional to at most (Δs/s0)3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss-Newton FWI update is proportional to (Δs/s0)2. For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. The inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a

Inflammatory bowel disease in children of middle eastern descent.

Science.gov (United States)

Naidoo, Christina Mai Ying; Leach, Steven T; Day, Andrew S; Lemberg, Daniel A

2014-01-01

Increasing rates of inflammatory bowel disease (IBD) are now seen in populations where it was once uncommon. The pattern of IBD in children of Middle Eastern descent in Australia has never been reported. This study aimed to investigate the burden of IBD in children of Middle Eastern descent at the Sydney Children's Hospital, Randwick (SCHR). The SCHR IBD database was used to identify patients of self-reported Middle Eastern ethnicity diagnosed between 1987 and 2011. Demographic, diagnosis, and management data was collected for all Middle Eastern children and an age and gender matched non-Middle Eastern IBD control group. Twenty-four patients of Middle Eastern descent were identified. Middle Eastern Crohn's disease patients had higher disease activity at diagnosis, higher use of thiopurines, and less restricted colonic disease than controls. Although there were limitations with this dataset, we estimated a higher prevalence of IBD in Middle Eastern children and they had a different disease phenotype and behavior compared to the control group, with less disease restricted to the colon and likely a more active disease course.

Environmental effects on hormonal regulation of testicular descent

DEFF Research Database (Denmark)

Toppari, J; Virtanen, H E; Skakkebaek, N E

2006-01-01

cause some cases of undescended testis. Similarly, androgen insensitivity or androgen deficiency can cause cryptorchidism. Estrogens have been shown to down regulate INSL3 and thereby cause maldescent. Thus, a reduced androgen-estrogen ratio may disturb testicular descent. Environmental effects changing......Regulation of testicular descent is hormonally regulated, but the reasons for maldescent remain unknown in most cases. The main regulatory hormones are Leydig cell-derived testosterone and insulin-like factor 3 (INSL3). Luteinizing hormone (LH) stimulates the secretion of these hormones...... hypothesize that an exposure to a mixture of chemicals with anti-androgenic or estrogenic properties (either their own activity or their effect on androgen-estrogen ratio) may be involved in cryptorchidism....

Whole-body angular momentum during stair ascent and descent.

Science.gov (United States)

Silverman, Anne K; Neptune, Richard R; Sinitski, Emily H; Wilken, Jason M

2014-04-01

The generation of whole-body angular momentum is essential in many locomotor tasks and must be regulated in order to maintain dynamic balance. However, angular momentum has not been investigated during stair walking, which is an activity that presents a biomechanical challenge for balance-impaired populations. We investigated three-dimensional whole-body angular momentum during stair ascent and descent and compared it to level walking. Three-dimensional body-segment kinematic and ground reaction force (GRF) data were collected from 30 healthy subjects. Angular momentum was calculated using a 13-segment whole-body model. GRFs, external moment arms and net joint moments were used to interpret the angular momentum results. The range of frontal plane angular momentum was greater for stair ascent relative to level walking. In the transverse and sagittal planes, the range of angular momentum was smaller in stair ascent and descent relative to level walking. Significant differences were also found in the ground reaction forces, external moment arms and net joint moments. The sagittal plane angular momentum results suggest that individuals alter angular momentum to effectively counteract potential trips during stair ascent, and reduce the range of angular momentum to avoid falling forward during stair descent. Further, significant differences in joint moments suggest potential neuromuscular mechanisms that account for the differences in angular momentum between walking conditions. These results provide a baseline for comparison to impaired populations that have difficulty maintaining dynamic balance, particularly during stair ascent and descent. Copyright © 2014 Elsevier B.V. All rights reserved.

Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images

International Nuclear Information System (INIS)

Mumcuglu, E.U.; Leahy, R.; Zhou, Z.; Cherry, S.R.

1994-01-01

The authors describe conjugate gradient algorithms for reconstruction of transmission and emission PET images. The reconstructions are based on a Bayesian formulation, where the data are modeled as a collection of independent Poisson random variables and the image is modeled using a Markov random field. A conjugate gradient algorithm is used to compute a maximum a posteriori (MAP) estimate of the image by maximizing over the posterior density. To ensure nonnegativity of the solution, a penalty function is used to convert the problem to one of unconstrained optimization. Preconditioners are used to enhance convergence rates. These methods generally achieve effective convergence in 15--25 iterations. Reconstructions are presented of an 18 FDG whole body scan from data collected using a Siemens/CTI ECAT931 whole body system. These results indicate significant improvements in emission image quality using the Bayesian approach, in comparison to filtered backprojection, particularly when reprojections of the MAP transmission image are used in place of the standard attenuation correction factors

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

Science.gov (United States)

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.

Descent construction for GSpin groups

CERN Document Server

Hundley, Joseph

2016-01-01

In this paper the authors provide an extension of the theory of descent of Ginzburg-Rallis-Soudry to the context of essentially self-dual representations, that is, representations which are isomorphic to the twist of their own contragredient by some Hecke character. The authors' theory supplements the recent work of Asgari-Shahidi on the functorial lift from (split and quasisplit forms of) GSpin_{2n} to GL_{2n}.

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

Science.gov (United States)

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.

LEARNING ALGORITHM EFFECT ON MULTILAYER FEED FORWARD ARTIFICIAL NEURAL NETWORK PERFORMANCE IN IMAGE CODING

Directory of Open Access Journals (Sweden)

OMER MAHMOUD

2007-08-01

Full Text Available One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.

Convective descent simulations of drilling discharges on Georges and Sable Island banks

International Nuclear Information System (INIS)

Andrade, Y.; Loder, J.W.

1997-01-01

Factors affecting the fate of drilling mud discharges on Georges and Sable Island Banks were examined. The Koh and Chang jet discharge model was used to simulate the convective descent of a jet discharge of relatively dense materials at sites representing different hydrographic and depth regimes with a range of mud densities, and different discharge configurations, ocean currents and seasonal stratifications. The study revealed the dependence of the depth of descent and properties of the discharge plume on the discharge configuration and oceanographic conditions. The factors that affected the depth of descent were mud density, depth of release, initial downward volume flux of the discharge, current strength and ocean stratification. 22 refs., 3 tabs., 59 figs

Non-linear extension of FFT-based methods accelerated by conjugate gradients to evaluate the mechanical behavior of composite materials

International Nuclear Information System (INIS)

Gelebart, Lionel; Mondon-Cancel, Romain

2013-01-01

FFT-based methods are used to solve the problem of a heterogeneous unit-cell submitted to periodic boundary conditions, which is of a great interest in the context of numerical homogenization. Recently (in 2010), Brisard and Zeman proposed simultaneously to use Conjugate Gradient based solvers in order to improve the convergence properties (when compared to the basic scheme, proposed initially in 1994). The purpose of the paper is to extend this idea to the case of non-linear behaviors. The proposed method is based on a Newton-Raphson algorithm and can be applied to various kinds of behaviors (time dependant or independent, with or without internal variables) through a conventional integration procedure as used in finite element codes. It must be pointed out that this approach is fundamentally different from the traditional FFT-based approaches which rely on a fixed-point algorithm (e.g. basic scheme, Eyre and Milton accelerated scheme, Augmented Lagrangian scheme, etc.). The method is compared to the basic scheme on the basis of a simple application (a linear elastic spherical inclusion within a non-linear elastic matrix): a low sensitivity to the reference material and an improved efficiency, for a soft or a stiff inclusion, are observed. At first proposed for a prescribed macroscopic strain, the method is then extended to mixed loadings. (authors)

Purification of SUMO conjugating enzymes and kinetic analysis of substrate conjugation

Science.gov (United States)

Yunus, Ali A.; Lima, Christopher D.

2009-01-01

SUMO conjugation to protein substrates requires the concerted action of a dedicated E2 ubiquitin conjugation enzyme (Ubc9) and associated E3 ligases. Although Ubc9 can directly recognize and modify substrate lysine residues that occur within a consensus site for SUMO modification, E3 ligases can redirect specificity and enhance conjugation rates during SUMO conjugation in vitro and in vivo. In this chapter, we will describe methods utilized to purify SUMO conjugating enzymes and model substrates which can be used for analysis of SUMO conjugation in vitro. We will also describe methods to extract kinetic parameters during E3-dependent or E3-independent substrate conjugation. PMID:19107417

On Nonconvex Decentralized Gradient Descent

Science.gov (United States)

2016-08-01

and J. Bolte, On the convergence of the proximal algorithm for nonsmooth functions involving analytic features, Math . Program., 116: 5-16, 2009. [2] H...splitting, and regularized Gauss-Seidel methods, Math . Pro- gram., Ser. A, 137: 91-129, 2013. [3] P. Bianchi and J. Jakubowicz, Convergence of a multi-agent...subgradient method under random communication topologies , IEEE J. Sel. Top. Signal Process., 5:754-771, 2011. [11] A. Nedic and A. Ozdaglar, Distributed

Immediate effects of a distal gait modification during stair descent in individuals with patellofemoral pain.

Science.gov (United States)

Aliberti, Sandra; Mezêncio, Bruno; Amadio, Alberto Carlos; Serrão, Julio Cerca; Mochizuki, Luis

2018-05-23

Knee pain during stair managing is a common complaint among individuals with PFP and can negatively affect their activities of daily living. Gait modification programs can be used to decrease patellofemoral pain. Immediate effects of a stair descent distal gait modification session that intended to emphasize forefoot landing during stair descent are described in this study. To analyze the immediate effects of a distal gait modification session on lower extremity movements and intensity of pain in women with patellofemoral pain during stair descent. Nonrandomized controlled trial. Sixteen women with patellofemoral pain were allocated into two groups: (1) Gait Modification Group (n = 8); and 2) Control Group (n = 8). The intensity of pain (visual analog scale) and kinematics of knee, ankle, and forefoot (multi-segmental foot model) during stair descent were assessed before and after the intervention. After the gait modification session, there was an increase of forefoot eversion and ankle plantarflexion as well as a decrease of knee flexion. An immediate decrease in patellofemoral pain intensity during stair descent was also observed. The distal gait modification session changed the lower extremity kinetic chain strategy of movement, increasing foot and ankle movement contribution and decreasing knee contribution to the task. An immediate decrease in patellofemoral pain intensity during stair descent was also observed. To emphasize forefoot landing may be a useful intervention to immediately relieve pain in patients with patellofemoral pain during stair descent. Clinical studies are needed to verify the gait modification session effects in medium and long terms.

Ascent, descent, nullity, defect, and related notions for linear relations in linear spaces

NARCIS (Netherlands)

Sandovici, Adrian; de Snoo, Henk; Winkler, Henrik

2007-01-01

For a linear relation in a linear space the concepts of ascent, descent, nullity, and defect are introduced and studied. It is shown that the results of A.E. Taylor and M.A. Kaashoek concerning the relationship between ascent, descent, nullity, and defect for the case of linear operators remain

Testicular descent: INSL3, testosterone, genes and the intrauterine milieu.

Science.gov (United States)

Bay, Katrine; Main, Katharina M; Toppari, Jorma; Skakkebæk, Niels E

2011-04-01

Complete testicular descent is a sign of, and a prerequisite for, normal testicular function in adult life. The process of testis descent is dependent on gubernacular growth and reorganization, which is regulated by the Leydig cell hormones insulin-like peptide 3 (INSL3) and testosterone. Investigation of the role of INSL3 and its receptor, relaxin-family peptide receptor 2 (RXFP2), has contributed substantially to our understanding of the hormonal control of testicular descent. Cryptorchidism is a common congenital malformation, which is seen in 2-9% of newborn boys, and confers an increased risk of infertility and testicular cancer in adulthood. Although some cases of isolated cryptorchidism in humans can be ascribed to known genetic defects, such as mutations in INSL3 or RXFP2, the cause of cryptorchidism remains unknown in most patients. Several animal and human studies are currently underway to test the hypothesis that in utero factors, including environmental and maternal lifestyle factors, may be involved in the etiology of cryptorchidism. Overall, the etiology of isolated cryptorchidism seems to be complex and multifactorial, involving both genetic and nongenetic components.

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

International Nuclear Information System (INIS)

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

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 fin 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

Impact of race on the professional lives of physicians of African descent.

Science.gov (United States)

Nunez-Smith, Marcella; Curry, Leslie A; Bigby, JudyAnn; Berg, David; Krumholz, Harlan M; Bradley, Elizabeth H

2007-01-02

Increasing the racial and ethnic diversity of the physician workforce is a national priority. However, insight into the professional experiences of minority physicians is limited. This knowledge is fundamental to developing effective strategies to recruit, retain, and support a diverse physician workforce. To characterize how physicians of African descent experience race in the workplace. Qualitative study based on in-person and in-depth racially concordant interviews using a standard discussion guide. The 6 New England states in the United States. 25 practicing physicians of African descent representing a diverse range of primary practice settings, specialties, and ages. Professional experiences of physicians of African descent. 1) Awareness of race permeates the experience of physicians of African descent in the health care workplace; 2) race-related experiences shape interpersonal interactions and define the institutional climate; 3) responses to perceived racism at work vary along a spectrum from minimization to confrontation; 4) the health care workplace is often silent on issues of race; and 5) collective race-related experiences can result in "racial fatigue," with personal and professional consequences for physicians. The study was restricted to New England and may not reflect the experiences of physicians in other geographic regions. The findings are meant to be hypothesis-generating and require additional follow-up studies. The issue of race remains a pervasive influence in the work lives of physicians of African descent. Without sufficient attention to the specific ways in which race shapes physicians' work experiences, health care organizations are unlikely to create environments that successfully foster and sustain a diverse physician workforce.

Counseling and Psychotherapy with Clients of Middle Eastern Descent: A Qualitative Inquiry

OpenAIRE

Boghosian, Sara

2011-01-01

It is becoming increasingly important for clinical and counseling psychologists to have multicultural competence skills for treating an increasingly diverse client population. The psychology literature related to culturally competent treatment with persons of Middle Eastern descent is currently limited. In this study, qualitative methodology was utilized to explore the mental health attitudes and psychotherapy experiences of clients of Middle Eastern descent. Participants described culturally...

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

Science.gov (United States)

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.

Entry, Descent and Landing Systems Analysis Study: Phase 1 Report

Science.gov (United States)

DwyerCianciolo, Alicia M.; Davis, Jody L.; Komar, David R.; Munk, Michelle M.; Samareh, Jamshid A.; Powell, Richard W.; Shidner, Jeremy D.; Stanley, Douglas O.; Wilhite, Alan W.; Kinney, David J.;

Global Patterns of Prostate Cancer Incidence, Aggressiveness, and Mortality in Men of African Descent

Directory of Open Access Journals (Sweden)

Timothy R. Rebbeck

2013-01-01

Full Text Available Prostate cancer (CaP is the leading cancer among men of African descent in the USA, Caribbean, and Sub-Saharan Africa (SSA. The estimated number of CaP deaths in SSA during 2008 was more than five times that among African Americans and is expected to double in Africa by 2030. We summarize publicly available CaP data and collected data from the men of African descent and Carcinoma of the Prostate (MADCaP Consortium and the African Caribbean Cancer Consortium (AC3 to evaluate CaP incidence and mortality in men of African descent worldwide. CaP incidence and mortality are highest in men of African descent in the USA and the Caribbean. Tumor stage and grade were highest in SSA. We report a higher proportion of T1 stage prostate tumors in countries with greater percent gross domestic product spent on health care and physicians per 100,000 persons. We also observed that regions with a higher proportion of advanced tumors reported lower mortality rates. This finding suggests that CaP is underdiagnosed and/or underreported in SSA men. Nonetheless, CaP incidence and mortality represent a significant public health problem in men of African descent around the world.

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

Science.gov (United States)

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.

Corrugated thimble tube for controlling control rod descent in nuclear reactor

International Nuclear Information System (INIS)

Luetzow, H.J.

1981-01-01

A thimble tube construction is described which will provide a controlled descent for a control rod while minimizing the reaction forces which must be absorbed by the thimble tube and reducing the possibility that a foreign particle could interfere with the free descent of a control rod. A thimble tube is formed with helically-corrugate internal walls which cooperate with a control rod contained in the tube in an emergency situation to provide a progressively-increasing hydraulic restraining force as each adjacent corrugation is encountered

JAC3D -- A three-dimensional finite element computer program for the nonlinear quasi-static response of solids with the conjugate gradient method; Yucca Mountain Site Characterization Project

Energy Technology Data Exchange (ETDEWEB)

Biffle, J.H.

1993-02-01

JAC3D is a three-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equation. The method is implemented in a three-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. An eight-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic-plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere.

JAC2D: A two-dimensional finite element computer program for the nonlinear quasi-static response of solids with the conjugate gradient method; Yucca Mountain Site Characterization Project

Energy Technology Data Exchange (ETDEWEB)

Biffle, J.H.; Blanford, M.L.

1994-05-01

JAC2D is a two-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equations. The method is implemented in a two-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. A four-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic/plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere.

The glucokinase mutation p.T206P is common among MODY patients of Jewish Ashkenazi descent.

Science.gov (United States)

Gozlan, Yael; Tenenbaum, Ariel; Shalitin, Shlomit; Lebenthal, Yael; Oron, Tal; Cohen, Ohad; Phillip, Moshe; Gat-Yablonski, Galia

2012-09-01

Maturity-onset diabetes of the young (MODY) is characterized by an autosomal dominant mode of inheritance; a primary defect in insulin secretion with non-ketotic hyperglycemia, age of onset under 25 yr; and lack of autoantibodies. Heterozygous mutations in glucokinase (GCK) are associated with mild fasting hyperglycemia and gestational diabetes mellitus while homozygous or compound heterozygous GCK mutations result in permanent neonatal diabetes mellitus. Given that both the Israeli-Arabic and the various Israeli-Jewish communities tend to maintain ethnic seclusion, we speculated that it would be possible to identify a relatively narrow spectrum of mutations in the Israeli population. To characterize the genetic basis of GCK-MODY in the different ethnic groups of the Israeli population. Patients with clinically identified GCK-MODY and their first degree family members. Molecular analysis of GCK was performed on genomic DNA using polymerase chain reaction, denaturing gradient gel electrophoresis (DGGE), and sequencing. Bioinformatic model was preformed using the NEST program. Mutations in GCK were identified in 25 families and were all family-specific, except c.616A>C. p.T206P. This mutation was identified in six unrelated families, all patients from a Jewish-Ashkenazi descent, thus indicating an ethno-genetic correlation. A simple, fast, and relatively cheap DGGE/restriction-digestion assay was developed. The high incidence of the mutant allele in GCK-MODY patients of Jewish-Ashkenazi descent suggests a founder effect. We propose that clinically identified GCK-MODY patients of Jewish-Ashkenazi origin be first tested for this mutation. © 2011 John Wiley & Sons A/S.

Minimizing convex functions by continuous descent methods

Directory of Open Access Journals (Sweden)

Sergiu Aizicovici

2010-01-01

Full Text Available We study continuous descent methods for minimizing convex functions, defined on general Banach spaces, which are associated with an appropriate complete metric space of vector fields. We show that there exists an everywhere dense open set in this space of vector fields such that each of its elements generates strongly convergent trajectories.

The grand descent has begun for CMS

CERN Multimedia

2006-01-01

Until recently, the CMS experimental cavern looked relatively empty; its detector was assembled entirely at ground level, to be lowered underground in 15 sections. On 2 November, the first hadronic forward calorimeter led the way with a grand descent. The first section of the CMS detector (centre of photo) arriving from the vertical shaft, viewed from the cavern floor. There is something unusual about the construction of the CMS detector. Instead of being built in the experimental cavern, like all the other detectors in the LHC experiments, it was constructed at ground level. This was to allow for easy access during the assembly of the detector and to minimise the size of the excavated cavern. The slightly nerve-wracking task of lowering it safely into the cavern in separate sections came after the complete detector was successfully tested with a magnetic field at ground level. In the early morning of 2 November, the first section of the CMS detector began its eagerly awaited descent into the underground ca...

Ethnic Identity and Acculturative Stress as Mediators of Depression in Students of Asian Descent

Science.gov (United States)

Lantrip, Crystal; Mazzetti, Francesco; Grasso, Joseph; Gill, Sara; Miller, Janna; Haner, Morgynn; Rude, Stephanie; Awad, Germine

2015-01-01

This study underscored the importance of addressing the well-being of college students of Asian descent, because these students had higher rates of depression and lower positive feelings about their ethnic group compared with students of European descent, as measured by the Affirmation subscale of the Ethnic Identity Scale. Affirmation mediated…

Videodefaecography combined with measurement of the anorectal angle and of perineal descent

International Nuclear Information System (INIS)

Skomorowska, E.; Henrichsen, S.; Christiansen, J.; Hegedues, V.; Glostrup Sygehus, Copenhagen

1987-01-01

Cineradiographic defaecography combined with measurement of the anorectal angle and descent of the pelvic floor is proposed. The method used in 73 women gave valuable information in 48 patients who complained of anal incompetence, rectal tenesmus, and chronic constipation. In these patients, high and low rectal intussusception, rectocele, and pathologic movement of the pelvic floor were detected. Some of these phenomena could only be diagnosed by the radiologic method here described. Quantitations of the anorectal angle and descent of the pelvic floor placed the group with constipation halfway between normal individuals and those with anal incompetence. The value of this finding is discussed. Recent improvements in anorectal surgery often make videodefaecography decisive for the choice of the optimal operative method. Therefore, videodefaecography together with measurement of the anorectal angle and pelvic floor descent is recommended whenever anorectal surgery for correction of functional disturbances is contemplated. (orig.)

Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent

KAUST Repository

Desmal, Abdulla

2016-11-02

An efficient and accurate scheme for solving the nonlinear electromagnetic inverse scattering problem on three-dimensional sparse investigation domains is proposed. The minimization problem is constructed in such a way that the data misfit between measurements and scattered fields (which are expressed as a nonlinear function of the contrast) is constrained by the contrast\\'s first norm. The resulting minimization problem is solved using nonlinear Landweber iterations accelerated using a steepest descent algorithm. A projection operator is applied at every iteration to enforce the sparsity constraint by thresholding the result of that iteration. Steepest descent algorithm ensures accelerated and convergent solution by utilizing larger iteration steps selected based on a necessary B-condition.

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

Science.gov (United States)

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.

Entry, Descent, and Landing for Human Mars Missions

Science.gov (United States)

Munk, Michelle M.; DwyerCianciolo, Alicia M.

2012-01-01

One of the most challenging aspects of a human mission to Mars is landing safely on the Martian surface. Mars has such low atmospheric density that decelerating large masses (tens of metric tons) requires methods that have not yet been demonstrated, and are not yet planned in future Mars missions. To identify the most promising options for Mars entry, descent, and landing, and to plan development of the needed technologies, NASA's Human Architecture Team (HAT) has refined candidate methods for emplacing needed elements of the human Mars exploration architecture (such as ascent vehicles and habitats) on the Mars surface. This paper explains the detailed, optimized simulations that have been developed to define the mass needed at Mars arrival to accomplish the entry, descent, and landing functions. Based on previous work, technology options for hypersonic deceleration include rigid, mid-L/D (lift-to-drag ratio) aeroshells, and inflatable aerodynamic decelerators (IADs). The hypersonic IADs, or HIADs, are about 20% less massive than the rigid vehicles, but both have their technology development challenges. For the supersonic regime, supersonic retropropulsion (SRP) is an attractive option, since a propulsive stage must be carried for terminal descent and can be ignited at higher speeds. The use of SRP eliminates the need for an additional deceleration system, but SRP is at a low Technology Readiness Level (TRL) in that the interacting plumes are not well-characterized, and their effect on vehicle stability has not been studied, to date. These architecture-level assessments have been used to define the key performance parameters and a technology development strategy for achieving the challenging mission of landing large payloads on Mars.

Correlation Between Echodefecography and 3-Dimensional Vaginal Ultrasonography in the Detection of Perineal Descent in Women With Constipation Symptoms.

Science.gov (United States)

Murad-Regadas, Sthela M; Pinheiro Regadas, Francisco Sergio; Rodrigues, Lusmar V; da Silva Vilarinho, Adjra; Buchen, Guilherme; Borges, Livia Olinda; Veras, Lara B; da Cruz, Mariana Murad

2016-12-01

Defecography is an established method of evaluating dynamic anorectal dysfunction, but conventional defecography does not allow for visualization of anatomic structures. The purpose of this study was to describe the use of dynamic 3-dimensional endovaginal ultrasonography for evaluating perineal descent in comparison with echodefecography (3-dimensional anorectal ultrasonography) and to study the relationship between perineal descent and symptoms and anatomic/functional abnormalities of the pelvic floor. This was a prospective study. The study was conducted at a large university tertiary care hospital. Consecutive female patients were eligible if they had pelvic floor dysfunction, obstructed defecation symptoms, and a score >6 on the Cleveland Clinic Florida Constipation Scale. Each patient underwent both echodefecography and dynamic 3-dimensional endovaginal ultrasonography to evaluate posterior pelvic floor dysfunction. Normal perineal descent was defined on echodefecography as puborectalis muscle displacement ≤2.5 cm; excessive perineal descent was defined as displacement >2.5 cm. Of 61 women, 29 (48%) had normal perineal descent; 32 (52%) had excessive perineal descent. Endovaginal ultrasonography identified 27 of the 29 patients in the normal group as having anorectal junction displacement ≤1 cm (mean = 0.6 cm; range, 0.1-1.0 cm) and a mean anorectal junction position of 0.6 cm (range, 0-2.3 cm) above the symphysis pubis during the Valsalva maneuver and correctly identified 30 of the 32 patients in the excessive perineal descent group. The κ statistic showed almost perfect agreement (κ = 0.86) between the 2 methods for categorization into the normal and excessive perineal descent groups. Perineal descent was not related to fecal or urinary incontinence or anatomic and functional factors (sphincter defects, pubovisceral muscle defects, levator hiatus area, grade II or III rectocele, intussusception, or anismus). The study did not include a

A comparison of three optimization algorithms for intensity modulated radiation therapy

International Nuclear Information System (INIS)

Pflugfelder, D.; Wilkens, J.J.; Nill, S.; Oelfke, U.

2008-01-01

In intensity modulated treatment techniques, the modulation of each treatment field is obtained using an optimization algorithm. Multiple optimization algorithms have been proposed in the literature, e.g. steepest descent, conjugate gradient, quasi-Newton methods to name a few. The standard optimization algorithm in our in-house inverse planning tool KonRad is a quasi-Newton algorithm. Although this algorithm yields good results, it also has some drawbacks. Thus we implemented an improved optimization algorithm based on the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) routine. In this paper the improved optimization algorithm is described. To compare the two algorithms, several treatment plans are optimized using both algorithms. This included photon (IMRT) as well as proton (IMPT) intensity modulated therapy treatment plans. To present the results in a larger context the widely used conjugate gradient algorithm was also included into this comparison. On average, the improved optimization algorithm was six times faster to reach the same objective function value. However, it resulted not only in an acceleration of the optimization. Due to the faster convergence, the improved optimization algorithm usually terminates the optimization process at a lower objective function value. The average of the observed improvement in the objective function value was 37%. This improvement is clearly visible in the corresponding dose-volume-histograms. The benefit of the improved optimization algorithm is particularly pronounced in proton therapy plans. The conjugate gradient algorithm ranked in between the other two algorithms with an average speedup factor of two and an average improvement of the objective function value of 30%. (orig.)

Descent in buildings (AM-190)

CERN Document Server

Mühlherr, Bernhard; Weiss, Richard M

2015-01-01

Descent in Buildings begins with the resolution of a major open question about the local structure of Bruhat-Tits buildings. The authors then put their algebraic solution into a geometric context by developing a general fixed point theory for groups acting on buildings of arbitrary type, giving necessary and sufficient conditions for the residues fixed by a group to form a kind of subbuilding or "form" of the original building. At the center of this theory is the notion of a Tits index, a combinatorial version of the notion of an index in the relative theory of algebraic groups. These results

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

Science.gov (United States)

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.

RITD - Adapting Mars Entry, Descent and Landing System for Earth

Science.gov (United States)

Haukka, H.; Heilimo, J.; Harri, A.-M.; Aleksashkin, S.; Koryanov, V.; Arruego, I.; Schmidt, W.; Finchenko, V.; Martynov, M.; Ponomarenko, A.; Kazakovtsev, V.; Martin, S.

2015-10-01

We have developed an atmospheric re-entry and descent system concept based on inflatable hypersonic decelerator techniques that were originally developed for Mars. The ultimate goal of this EU-funded RITD-project (Re-entry: Inflatable Technology Development) was to assess the benefits of this technology when deploying small payloads from low Earth orbits to the surface of the Earth with modest costs. The principal goal was to assess and develop a preliminary EDLS design for the entire relevant range of aerodynamic regimes expected to be encountered in Earth's atmosphere during entry, descent and landing. Low Earth Orbit (LEO) and even Lunar applications envisaged include the use of the EDLS approach in returning payloads of 4-8 kg down to the surface.

Reversible cerebral vasoconstriction syndrome precipitated by airplane descent: Case report.

Science.gov (United States)

Hiraga, Akiyuki; Aotsuka, Yuya; Koide, Kyosuke; Kuwabara, Satoshi

2017-10-01

Background Reversible cerebral vasoconstriction syndrome (RCVS) is characterized by segmental vasospasm. Vasoactive agents and childbirth have been reported as precipitating factors for RCVS; however, RCVS induced by altitude change or air travel has rarely been reported. Case We present a case of a 74-year-old woman who presented with thunderclap headache during airplane descent. Magnetic resonance angiography demonstrated segmental vasoconstriction that improved 9 days after onset. Conclusion These findings indicate that airplane descent may be a trigger of RCVS. The time course of headache in the present case was similar to that of prolonged headache attributed to airplane travel, indicating that RCVS during air travel may have previously been overlooked and that some headache attributed to airplane travel cases may represent a milder form of RCVS.

Entry, Descent and Landing Systems Analysis: Exploration Class Simulation Overview and Results

Science.gov (United States)

DwyerCianciolo, Alicia M.; Davis, Jody L.; Shidner, Jeremy D.; Powell, Richard W.

2010-01-01

NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to make in order to successfully land large payloads at Mars for both robotic and exploration or human-scale missions. The year one exploration class mission activity considered technologies capable of delivering a 40-mt payload. This paper provides an overview of the exploration class mission study, including technologies considered, models developed and initial simulation results from the EDL-SA year one effort.

Conjugated heat transfer and temperature distributions in a gas turbine combustion liner under base-load operation

International Nuclear Information System (INIS)

Kim, Kyung Min; Yun, Nam Geon; Jeon, Yun Heung; Lee, Dong Hyun; Cho, Yung Hee

2010-01-01

Prediction of temperature distributions on hot components is important in development of a gas turbine combustion liner. The present study investigated conjugated heat transfer to obtain temperature distributions in a combustion liner with six combustion nozzles. 3D numerical simulations using FVM commercial codes, Fluent and CFX were performed to calculate combustion and heat transfer distributions. The temperature distributions in the combustor liner were calculated by conjugation of conduction and convection (heat transfer coefficients) obtained by combustion and cooling flow analysis. The wall temperature was the highest on the attachment points of the combustion gas from combustion nozzles, but the temperature gradient was high at the after shell section with low wall temperature

Gender differences of sagittal knee and ankle biomechanics during stair-to-ground descent transition.

Science.gov (United States)

Hong, Yoon No Gregory; Shin, Choongsoo S

2015-12-01

Falls on stairs often result in severe injury and occur twice as frequently in women. However, gender differences in kinetics and kinematics during stair descent are unknown. Thus, this study aimed to determine whether gender differences of knee and ankle biomechanics exist in the sagittal plane during the stair-to-ground descending transition. It was hypothesized that 1) women would reveal higher ground-toe-trochanter angle and lower ground-toe length during stair-to-ground descent transition than men; and 2) women would reveal lower peak knee extension moment during stair-to-ground descent transition than men. Fifteen men and fifteen women were recruited and performed a stair descent activity. Kinetic and kinematic data were obtained using a force plate and motion capture system. The women performed the stair descent with a lower peak knee extension moment and a peak knee power at the early weight acceptance phase. The women also revealed a higher ground-toe-trochanter angle and a lower ground-toe length, which indicated a more forward position of the lower extremity relative to the toe contact point at both the initial contact and at the time of peak kinematic and kinetic events. This study found that knee and ankle kinematics and kinetics differed significantly between the genders due to differences in ground-toe-trochanter angle. Women have a different stair descending strategy that reduces the demand of the lower extremity muscle function, but this strategy seems to increase the risk of falls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Double diffusive conjugate heat transfer: Part I

Science.gov (United States)

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.

Real-time aircraft continuous descent trajectory optimization with ATC time constraints using direct collocation methods.

OpenAIRE

Verhoeven, Ronald; Dalmau Codina, Ramon; Prats Menéndez, Xavier; de Gelder, Nico

2014-01-01

1 Abstract In this paper an initial implementation of a real - time aircraft trajectory optimization algorithm is presented . The aircraft trajectory for descent and approach is computed for minimum use of thrust and speed brake in support of a “green” continuous descent and approach flight operation, while complying with ATC time constraints for maintaining runway throughput and co...

Machado-Joseph Disease in Pedigrees of Azorean descent is Linked to Chromosome 14

OpenAIRE

George-Hyslop, P. St; Rogaeva, E.; Huterer, J.; Tsuda, T.; Santos, J.; Haines, J. L.; Schlumpf, K.; Rogaev, E. I.; Liang, Y.; McLachlan, D. R. Crapper; Kennedy, J.; Weissenbach, J.; Billingsley, G. D.; Cox, D. W.; Lang, A. E.

1994-01-01

A locus for Machado-Joseph disease (MJD) has recently been mapped to a 30-cM region of chromosome 14q in five pedigrees of Japanese descent. MJD is a clinically pleomorphic neurodegenerative disease that was originally described in subjects of Azorean descent. In light of the nonallelic heterogeneity in other inherited spinocere-bellar ataxias, we were interested to determine if the MJD phenotype in Japanese and Azorean pedigrees arose from mutations at the same locus. We provide evidence tha...

Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm

KAUST Repository

Desmal, Abdulla; Bagci, Hakan

2017-01-01

steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without

Shape tracking with occlusions via coarse-to-fine region-based sobolev descent

KAUST Repository

Yang, Yanchao

2015-05-01

We present a method to track the shape of an object from video. The method uses a joint shape and appearance model of the object, which is propagated to match shape and radiance in subsequent frames, determining object shape. Self-occlusions and dis-occlusions of the object from camera and object motion pose difficulties to joint shape and appearance models in tracking. They are unable to adapt to new shape and appearance information, leading to inaccurate shape detection. In this work, we model self-occlusions and dis-occlusions in a joint shape and appearance tracking framework. Self-occlusions and the warp to propagate the model are coupled, thus we formulate a joint optimization problem. We derive a coarse-to-fine optimization method, advantageous in tracking, that initially perturbs the model by coarse perturbations before transitioning to finer-scale perturbations seamlessly. This coarse-to-fine behavior is automatically induced by gradient descent on a novel infinite-dimensional Riemannian manifold that we introduce. The manifold consists of planar parameterized regions, and the metric that we introduce is a novel Sobolev metric. Experiments on video exhibiting occlusions/dis-occlusions, complex radiance and background show that occlusion/dis-occlusion modeling leads to superior shape accuracy. © 2014 IEEE.

Is prenatal urethral descent a risk factor for urinary incontinence during pregnancy and the postpartum period?

Science.gov (United States)

Pizzoferrato, Anne-Cécile; Fauconnier, Arnaud; Bader, Georges; de Tayrac, Renaud; Fort, Julie; Fritel, Xavier

2016-07-01

Obstetric trauma during childbirth is considered a major risk factor for postpartum urinary incontinence (UI), particularly stress urinary incontinence. Our aim was to investigate the relation between postpartum UI, mode of delivery, and urethral descent, and to define a group of women who are particularly at risk of postnatal UI. A total of 186 women were included their first pregnancy. Validated questionnaires about urinary symptoms during pregnancy, 2 and 12 months after delivery, were administered. Urethral descent was assessed clinically and by ultrasound at inclusion. Multivariate logistic regression analysis was used to determine the risk factors for UI during pregnancy, at 2 months and 1 year after first delivery. The prevalence of UI was 38.6, 46.5, 35.6, and 34.4 % at inclusion, late pregnancy, 2 months postpartum, and 1 year postpartum respectively. No significant association was found between UI at late pregnancy and urethral descent assessed clinically or by ultrasound. The only risk factor for UI at 2 months postpartum was UI at inclusion (OR 6.27 [95 % CI 2.70-14.6]). The risk factors for UI at 1 year postpartum were UI at inclusion (6.14 [2.22-16.9]), body mass index (BMI), and urethral descent at inclusion, assessed clinically (7.21 [2.20-23.7]) or by ultrasound. The mode of delivery was not associated with urethral descent. Prenatal urethral descent and UI during pregnancy are risk factors for UI at 1 year postpartum. These results indicate that postnatal UI is more strongly influenced by susceptibility factors existing before first delivery than by the mode of delivery.

Local flow management/profile descent algorithm. Fuel-efficient, time-controlled profiles for the NASA TSRV airplane

Science.gov (United States)

Groce, J. L.; Izumi, K. H.; Markham, C. H.; Schwab, R. W.; Thompson, J. L.

1986-01-01

The Local Flow Management/Profile Descent (LFM/PD) algorithm designed for the NASA Transport System Research Vehicle program is described. The algorithm provides fuel-efficient altitude and airspeed profiles consistent with ATC restrictions in a time-based metering environment over a fixed ground track. The model design constraints include accommodation of both published profile descent procedures and unpublished profile descents, incorporation of fuel efficiency as a flight profile criterion, operation within the performance capabilities of the Boeing 737-100 airplane with JT8D-7 engines, and conformity to standard air traffic navigation and control procedures. Holding and path stretching capabilities are included for long delay situations.

A different approach to estimate nonlinear regression model using numerical methods

Science.gov (United States)

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].

Evaluation of iodovinyl antibody conjugates: Comparison with a p-iodobenzoyl conjugate and direct radioiodination

International Nuclear Information System (INIS)

Hadley, S.W.; Wilbur, D.S.

1990-01-01

The preparations and conjugations of 2,3,5,6-tetrafluorophenyl 5-[125I/131I]iodo-4-pentenoate (7a) and 2,3,5,6-tetrafluorophenyl 3,3-dimethyl-5-[125I/131I]iodo-4-pentenoate (7b) to monoclonal antibodies are reported. Reagents 7a and 7b were prepared in high radiochemical yield by iododestannylation of their corresponding 5-tri-n-butylstannyl precursors. Radioiodinated antibody conjugates were prepared by reaction of 7a or 7b with the protein at basic pH. Evaluation of these conjugates by several in vitro procedures demonstrated that the radiolabel was attached to the antibody in a stable manner and that the conjugates maintained immunoreactivity. Comparative dual-isotope biodistribution studies of a monoclonal antibody Fab fragment conjugate of 7a and 7b with the same Fab fragment labeled with N-succinimidyl p-[131I]iodobenzoate (PIB, p-iodobenzoate, 2) or directly radioiodinated have been carried out in tumor-bearing nude mice. Coinjection of the Fab conjugate of 7a with the Fab conjugate of 2 demonstrated that the biodistributions were similar in most organs, except the neck tissue (thyroid-containing) and the stomach, which contained substantially increased levels of the 7a label. Coinjection of the Fab conjugate of 7a with the Fab fragment radioiodinated by using the chloramine-T method demonstrated that the biodistributions were remarkably similar, suggesting roughly equivalent in vivo deiodination of these labeled antibody fragments. Coinjection of the Fab conjugate of 7a with the Fab conjugate of 7b indicated that there was ∼ a 2-fold reduction in the amount of in vivo deiodination of the 7b conjugate as compared to the 7a conjugate

Development of {sup 177}Lu-DTPA-SPIO conjugates for potential use as a dual contrast SPECT/MRI imaging agent

Energy Technology Data Exchange (ETDEWEB)

Shanehsazzadeh, Saeed; Yousefnia, Hassan [Nuclear Science and Technology Research Institute (NSTRI), Tehran (Iran, Islamic Republic of); Gruettner, Cordula [Micromod Partikeltechnologie GmbH, Rostock (Germany); and others

2016-08-01

This study describes the preparation, biodistribution of {sup 177}Lu-DTPA-SPIO after intravenous injection in rats. The chelator DTPA dianhydride was conjugated to SPIO NPs using a small modification of the well-known cyclic anhydride method. Conjugation was done at a 1:2 (SPIO:ccDTPA) molar ratio. Conjugation reaction was purified with Magnetic assorting column (MACs) using high gradient magnetic field following incubation, the radio labeled conjugate was checked using RTLC method for labeling and purity checked. The RTLC showed that labeling yield was above 99% after purification and the compound have good in-vitro stabilities until 48 h post injection in the presence of human serum. The biodistribution of {sup 177}Lu-DTPA-SPIO in rats showed dramatic uptake in the reticuloendothelial system (RES) and their clearance is so fast in other organs especially in the blood. In conclusion, due to high uptakes of this radiotracer in the liver and spleen and their fast clearance from other tissues, especially in blood, it is suggested that this radiotracer would be suitable for RES studies.

Screening for homozygosity by descent in families with autosomal

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics; Volume 81; Issue 2 ... Perspectives Volume 81 Issue 2 August 2002 pp 59-63 ... disease locus in families with the recessive form of the disease, we used the approach of screening for homozygosity by descent in offspring of consanguineous and nonconsanguineous families with RP.

Gradient-based estimation of Manning's friction coefficient from noisy data

KAUST Repository

Calo, Victor M.

2013-01-01

We study the numerical recovery of Manning\\'s roughness coefficient for the diffusive wave approximation of the shallow water equation. We describe a conjugate gradient method for the numerical inversion. Numerical results for one-dimensional models are presented to illustrate the feasibility of the approach. Also we provide a proof of the differentiability of the weak form with respect to the coefficient as well as the continuity and boundedness of the linearized operator under reasonable assumptions using the maximal parabolic regularity theory. © 2012 Elsevier B.V. All rights reserved.

Gradient-based estimation of Manning's friction coefficient from noisy data

KAUST Repository

Calo, Victor M.; Collier, Nathan; Gehre, Matthias; Jin, Bangti; Radwan, Hany G.; Santillana, Mauricio

2013-01-01

We study the numerical recovery of Manning's roughness coefficient for the diffusive wave approximation of the shallow water equation. We describe a conjugate gradient method for the numerical inversion. Numerical results for one-dimensional models are presented to illustrate the feasibility of the approach. Also we provide a proof of the differentiability of the weak form with respect to the coefficient as well as the continuity and boundedness of the linearized operator under reasonable assumptions using the maximal parabolic regularity theory. © 2012 Elsevier B.V. All rights reserved.

Airborne Management of Traffic Conflicts in Descent With Arrival Constraints

Science.gov (United States)

Doble, Nathan A.; Barhydt, Richard; Krishnamurthy, Karthik

2005-01-01

NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.

Intelligent Data Understanding for Architecture Analysis of Entry, Descent, and Landing

Data.gov (United States)

National Aeronautics and Space Administration — Because Entry, Descent and Landing (EDL) system validations are limited in Earth environments, these technologies rely heavily on models and analysis tools to...

Co-conjugation vis-à-vis individual conjugation of α-amylase and glucoamylase for hydrolysis of starch.

Science.gov (United States)

Jadhav, Swati B; Singhal, Rekha S

2013-10-15

Two enzymes, α-amylase and glucoamylase have been individually and co-conjugated to pectin by covalent binding. Both the enzyme systems showed better thermal and pH stability over the free enzyme system with the complete retention of original activities. Mixture of individually conjugated enzymes showed lower inactivation rate constant with longer half life than the co-conjugated enzyme system. Individually conjugated enzymes showed an increase of 56.48 kJ/mole and 38.22 kJ/mole in activation energy for denaturation than the free enzymes and co-conjugated enzymes, respectively. Km as well as Vmax of individually and co-conjugated enzymes was found to be higher than the free enzymes. SDS-polyacrylamide gel electrophoresis confirmed the formation of conjugate and co-conjugate as evident by increased molecular weight. Both the enzyme systems were used for starch hydrolysis where individually conjugated enzymes showed highest release of glucose at 60 °C and pH 5.0 as compared to free and co-conjugated enzyme. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Role of la Familia for Women of Mexican Descent Who Are Leaders in Higher Education

Science.gov (United States)

Elizondo, Sandra Gray

2012-01-01

The purpose of this qualitative case study was to describe the role of "la familia" for women of Mexican descent as it relates to their development as leaders and their leadership in academia. Purposeful sampling was utilized to reach the goal of 18 participants who were female academic leaders of Mexican descent teaching full time in…

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

A Wind Tunnel Study on the Mars Pathfinder (MPF) Lander Descent Pressure Sensor

Science.gov (United States)

Soriano, J. Francisco; Coquilla, Rachael V.; Wilson, Gregory R.; Seiff, Alvin; Rivell, Tomas

2001-01-01

The primary focus of this study was to determine the accuracy of the Mars Pathfinder lander local pressure readings in accordance with the actual ambient atmospheric pressures of Mars during parachute descent. In order to obtain good measurements, the plane of the lander pressure sensor opening should ideally be situated so that it is parallel to the freestream. However, due to two unfavorable conditions, the sensor was positioned in locations where correction factors are required. One of these disadvantages is due to the fact that the parachute attachment point rotated the lander's center of gravity forcing the location of the pressure sensor opening to be off tangent to the freestream. The second and most troublesome factor was that the lander descends with slight oscillations that could vary the amplitude of the sensor readings. In order to accurately map the correction factors required at each sensor position, an experiment simulating the lander descent was conducted in the Martian Surface Wind Tunnel at NASA Ames Research Center. Using a 115 scale model at Earth ambient pressures, the test settings provided the necessary Reynolds number conditions in which the actual lander was possibly subjected to during the descent. In the analysis and results of this experiment, the readings from the lander sensor were converted to the form of pressure coefficients. With a contour map of pressure coefficients at each lander oscillatory position, this report will provide a guideline to determine the correction factors required for the Mars Pathfinder lander descent pressure sensor readings.

Non-homogeneous updates for the iterative coordinate descent algorithm

Science.gov (United States)

Yu, Zhou; Thibault, Jean-Baptiste; Bouman, Charles A.; Sauer, Ken D.; Hsieh, Jiang

2007-02-01

Statistical reconstruction methods show great promise for improving resolution, and reducing noise and artifacts in helical X-ray CT. In fact, statistical reconstruction seems to be particularly valuable in maintaining reconstructed image quality when the dosage is low and the noise is therefore high. However, high computational cost and long reconstruction times remain as a barrier to the use of statistical reconstruction in practical applications. Among the various iterative methods that have been studied for statistical reconstruction, iterative coordinate descent (ICD) has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a novel method for further speeding the convergence of the ICD algorithm, and therefore reducing the overall reconstruction time for statistical reconstruction. The method, which we call nonhomogeneous iterative coordinate descent (NH-ICD) uses spatially non-homogeneous updates to speed convergence by focusing computation where it is most needed. Experimental results with real data indicate that the method speeds reconstruction by roughly a factor of two for typical 3D multi-slice geometries.

Steepest descent moment method for three-dimensional magnetohydrodynamic equilibria

International Nuclear Information System (INIS)

Hirshman, S.P.; Whitson, J.C.

1983-11-01

An energy principle is used to obtain the solution of the magnetohydrodynamic (MHD) equilibrium equation J Vector x B Vector - del p = 0 for nested magnetic flux surfaces that are expressed in the inverse coordinate representation x Vector = x Vector(rho, theta, zeta). Here, theta and zeta are poloidal and toroidal flux coordinate angles, respectively, and p = p(rho) labels a magnetic surface. Ordinary differential equations in rho are obtained for the Fourier amplitudes (moments) in the doubly periodic spectral decomposition of x Vector. A steepest descent iteration is developed for efficiently solving these nonlinear, coupled moment equations. The existence of a positive-definite energy functional guarantees the monotonic convergence of this iteration toward an equilibrium solution (in the absence of magnetic island formation). A renormalization parameter lambda is introduced to ensure the rapid convergence of the Fourier series for x Vector, while simultaneously satisfying the MHD requirement that magnetic field lines are straight in flux coordinates. A descent iteration is also developed for determining the self-consistent value for lambda

Arachnid aloft: directed aerial descent in neotropical canopy spiders.

Science.gov (United States)

Yanoviak, Stephen P; Munk, Yonatan; Dudley, Robert

2015-09-06

The behaviour of directed aerial descent has been described for numerous taxa of wingless hexapods as they fall from the tropical rainforest canopy, but is not known in other terrestrial arthropods. Here, we describe similar controlled aerial behaviours for large arboreal spiders in the genus Selenops (Selenopidae). We dropped 59 such spiders from either canopy platforms or tree crowns in Panama and Peru; the majority (93%) directed their aerial trajectories towards and then landed upon nearby tree trunks. Following initial dorsoventral righting when necessary, falling spiders oriented themselves and then translated head-first towards targets; directional changes were correlated with bilaterally asymmetric motions of the anterolaterally extended forelegs. Aerial performance (i.e. the glide index) decreased with increasing body mass and wing loading, but not with projected surface area of the spider. Along with the occurrence of directed aerial descent in ants, jumping bristletails, and other wingless hexapods, this discovery of targeted gliding in selenopid spiders further indicates strong selective pressures against uncontrolled falls into the understory for arboreal taxa. © 2015 The Author(s).

Mars Exploration Rover Terminal Descent Mission Modeling and Simulation

Science.gov (United States)

Raiszadeh, Behzad; Queen, Eric M.

2004-01-01

Because of NASA's added reliance on simulation for successful interplanetary missions, the MER mission has developed a detailed EDL trajectory modeling and simulation. This paper summarizes how the MER EDL sequence of events are modeled, verification of the methods used, and the inputs. This simulation is built upon a multibody parachute trajectory simulation tool that has been developed in POST I1 that accurately simulates the trajectory of multiple vehicles in flight with interacting forces. In this model the parachute and the suspended bodies are treated as 6 Degree-of-Freedom (6 DOF) bodies. The terminal descent phase of the mission consists of several Entry, Descent, Landing (EDL) events, such as parachute deployment, heatshield separation, deployment of the lander from the backshell, deployment of the airbags, RAD firings, TIRS firings, etc. For an accurate, reliable simulation these events need to be modeled seamlessly and robustly so that the simulations will remain numerically stable during Monte-Carlo simulations. This paper also summarizes how the events have been modeled, the numerical issues, and modeling challenges.

Neuromuscular function during stair descent in meniscectomized patients and controls

DEFF Research Database (Denmark)

Thorlund, Jonas Bloch; Roos, Ewa M; Aagaard, Per

2011-01-01

The aim of this study was to identify differences in knee range of motion (ROM), movement speed, ground reaction forces (GRF) profile, neuromuscular activity, and muscle coactivation during the transition between stair descent and level walking in meniscectomized patients at high risk of knee...

Experimental studies of the rotor flow downwash on the Stability of multi-rotor crafts in descent

Science.gov (United States)

Veismann, Marcel; Dougherty, Christopher; Gharib, Morteza

2017-11-01

All rotorcrafts, including helicopters and multicopters, have the inherent problem of entering rotor downwash during vertical descent. As a result, the craft is subject to highly unsteady flow, called vortex ring state (VRS), which leads to a loss of lift and reduced stability. To date, experimental efforts to investigate this phenomenon have been largely limited to analysis of a single, fixed rotor mounted in a horizontal wind tunnel. Our current work aims to understand the interaction of multiple rotors in vertical descent by mounting a multi-rotor craft in a low speed, vertical wind tunnel. Experiments were performed with a fixed and rotationally free mounting; the latter allowing us to better capture the dynamics of a free flying drone. The effect of rotor separation on stability, generated thrust, and rotor wake interaction was characterized using force gauge data and PIV analysis for various descent velocities. The results obtained help us better understand fluid-craft interactions of drones in vertical descent and identify possible sources of instability. The presented material is based upon work supported by the Center for Autonomous Systems and Technologies (CAST) at the Graduate Aerospace Laboratories of the California Institute of Technology (GALCIT).

Stereotypes of women of Asian descent in midwifery: some evidence.

Science.gov (United States)

Bowler, I M

1993-03-01

The subject of this paper is part of a larger study which investigated the delivery of maternity care to women of South Asian descent in Britain (Bowler, 1990). An ethnographic approach was used and the main method of data collection was non-participant observation in antenatal clinics, labour and postnatal wards in a teaching hospital maternity unit. These observations were supported by data from interviews with midwives. It was found that the midwives commonly use stereotypes of women in order to help them to provide care. These stereotypes are particularly likely to be used in situations where the midwife has difficulty (through pressure of time or other circumstances) in getting to know an individual woman. The stereotype of women of Asian descent contained four main themes: communication problems; failure to comply with care and service abuse; making a fuss about nothing; a lack of normal maternal instinct. Reasons for stereotyping are explored. Effects on service provision in the areas of family planning and breast feeding are highlighted.

Minimum-fuel turning climbout and descent guidance of transport jets

Science.gov (United States)

Neuman, F.; Kreindler, E.

1983-01-01

The complete flightpath optimization problem for minimum fuel consumption from takeoff to landing including the initial and final turns from and to the runway heading is solved. However, only the initial and final segments which contain the turns are treated, since the straight-line climbout, cruise, and descent problems have already been solved. The paths are derived by generating fields of extremals, using the necessary conditions of optimal control together with singular arcs and state constraints. Results show that the speed profiles for straight flight and turning flight are essentially identical except for the final horizontal accelerating or decelerating turns. The optimal turns require no abrupt maneuvers, and an approximation of the optimal turns could be easily integrated with present straight-line climb-cruise-descent fuel-optimization algorithms. Climbout at the optimal IAS rather than the 250-knot terminal-area speed limit would save 36 lb of fuel for the 727-100 aircraft.

Entry, Descent, and Landing Performance for a Mid-Lift-to-Drag Ratio Vehicle at Mars

Science.gov (United States)

Johnson, Breanna J.; Braden, Ellen M.; Sostaric, Ronald R.; Cerimele, Christopher J.; Lu, Ping

2018-01-01

In an effort to mature the design of the Mid-Lift-to-Drag ratio Rigid Vehicle (MRV) candidate of the NASA Evolvable Mars Campaign (EMC) architecture study, end-to-end six-degree-of-freedom (6DOF) simulations are needed to ensure a successful entry, descent, and landing (EDL) design. The EMC study is assessing different vehicle and mission architectures to determine which candidate would be best to deliver a 20 metric ton payload to the surface of Mars. Due to the large mass payload and the relatively low atmospheric density of Mars, all candidates of the EMC study propose to use Supersonic Retro-Propulsion (SRP) throughout the descent and landing phase, as opposed to parachutes, in order to decelerate to a subsonic touchdown. This paper presents a 6DOF entry-to-landing performance and controllability study with sensitivities to dispersions, particularly in the powered descent and landing phases.

Myocardial perfusion magnetic resonance imaging using sliding-window conjugate-gradient HYPR methods in canine with stenotic coronary arteries.

Science.gov (United States)

Ge, Lan; Kino, Aya; Lee, Daniel; Dharmakumar, Rohan; Carr, James C; Li, Debiao

2010-01-01

First-pass perfusion magnetic resonance imaging (MRI) is a promising technique for detecting ischemic heart disease. However, the diagnostic value of the method is limited by the low spatial coverage, resolution, signal-to-noise ratio (SNR), and cardiac motion-related image artifacts. A combination of sliding window and conjugate-gradient HighlY constrained back-PRojection reconstruction (SW-CG-HYPR) method has been proposed in healthy volunteer studies to reduce the acquisition window for each slice while maintaining the temporal resolution of 1 frame per heartbeat in myocardial perfusion MRI. This method allows for improved spatial coverage, resolution, and SNR. In this study, we use a controlled animal model to test whether the myocardial territory supplied by a stenotic coronary artery can be detected accurately by SW-CG-HYPR perfusion method under pharmacological stress. Results from 6 mongrel dogs (15-25 kg) studies demonstrate the feasibility of SW-CG-HYPR to detect regional perfusion defects. Using this method, the acquisition time per cardiac cycle was reduced by a factor of 4, and the spatial coverage was increased from 2 to 3 slices to 6 slices as compared with the conventional techniques including both turbo-Fast Low Angle Short (FLASH) and echoplanar imaging (EPI). The SNR of the healthy myocardium at peak enhancement with SW-CG-HYPR (12.68 ± 2.46) is significantly higher (P < 0.01) than the turbo-FLASH (8.65 ± 1.93) and EPI (5.48 ± 1.24). The spatial resolution of SW-CG-HYPR images is 1.2 × 1.2 × 8.0 mm, which is better than the turbo-FLASH (1.8 × 1.8 × 8.0 mm) and EPI (2.0 × 1.8 × 8.0 mm). Sliding-window CG-HYPR is a promising technique for myocardial perfusion MRI. This technique provides higher image quality with respect to significantly improved SNR and spatial resolution of the myocardial perfusion images, which might improve myocardial perfusion imaging in a clinical setting.

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

Science.gov (United States)

Koppenhoefer, Kyle C.; Gullerud, Arne S.; Ruggieri, Claudio; Dodds, Robert H., Jr.; Healy, Brian E.

1998-01-01

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves

Machado-Joseph disease in pedigrees of Azorean descent is linked to chromosome 14.

Science.gov (United States)

St George-Hyslop, P; Rogaeva, E; Huterer, J; Tsuda, T; Santos, J; Haines, J L; Schlumpf, K; Rogaev, E I; Liang, Y; McLachlan, D R

1994-07-01

A locus for Machado-Joseph disease (MJD) has recently been mapped to a 30-cM region of chromosome 14q in five pedigrees of Japanese descent. MJD is a clinically pleomorphic neurodegenerative disease that was originally described in subjects of Azorean descent. In light of the nonallelic heterogeneity in other inherited spinocerebellar ataxias, we were interested to determine if the MJD phenotype in Japanese and Azorean pedigrees arose from mutations at the same locus. We provide evidence that MJD in five pedigrees of Azorean descent is also linked to chromosome 14q in an 18-cM region between the markers D14S67 and AACT (multipoint lod score +7.00 near D14S81). We also report molecular evidence for homozygosity at the MJD locus in an MJD-affected subject with severe, early-onset symptoms. These observations confirm the initial report of linkage of MJD to chromosome 14; suggest that MJD in Japanese and Azorean subjects may represent allelic or identical mutations at the same locus; and provide one possible explanation (MJD gene dosage) for the observed phenotypic heterogeneity in this disease.

Bacteriophytochromes control conjugation in Agrobacterium fabrum.

Science.gov (United States)

Bai, Yingnan; Rottwinkel, Gregor; Feng, Juan; Liu, Yiyao; Lamparter, Tilman

2016-08-01

Bacterial conjugation, the transfer of single stranded plasmid DNA from donor to recipient cell, is mediated through the type IV secretion system. We performed conjugation assays using a transmissible artificial plasmid as reporter. With this assay, conjugation in Agrobacterium fabrum was modulated by the phytochromes Agp1 and Agp2, photoreceptors that are most sensitive in the red region of visible light. In conjugation studies with wild-type donor cells carrying a pBIN-GUSINT plasmid as reporter that lacked the Ti (tumor inducing) plasmid, no conjugation was observed. When either agp1(-) or agp2(-) knockout donor strains were used, plasmid DNA was delivered to the recipient, indicating that both phytochromes suppress conjugation in the wild type donor. In the recipient strains, the loss of Agp1 or Agp2 led to diminished conjugation. When wild type cells with Ti plasmid and pBIN-GUS reporter plasmid were used as donor, a high rate of conjugation was observed. The DNA transfer was down regulated by red or far-red light by a factor of 3.5. With agp1(-) or agp2(-) knockout donor cells, conjugation in the dark was about 10 times lower than with the wild type donor, and with the double knockout donor no conjugation was observed. These results imply that the phytochrome system has evolved to inhibit conjugation in the light. The decrease of conjugation under different temperature correlated with the decrease of phytochrome autophosphorylation. Copyright © 2015 Elsevier B.V. All rights reserved.

Additive preservers of the ascent, descent and related subsets

Czech Academy of Sciences Publication Activity Database

Mbekhta, M.; Müller, Vladimír; Oudghiri, M.

2014-01-01

Roč. 71, č. 1 (2014), s. 63-83 ISSN 0379-4024 R&D Projects: GA ČR GA201/09/0473; GA AV ČR IAA100190903 Institutional support: RVO:67985840 Keywords : additive preservers * ascent * descent Subject RIV: BA - General Mathematics Impact factor: 0.550, year: 2014 http://www.mathjournals.org/jot/2014-071-001/2014-071-001-004.html

Polymers for Protein Conjugation

Directory of Open Access Journals (Sweden)

Gianfranco Pasut

2014-01-01

Full Text Available Polyethylene glycol (PEG at the moment is considered the leading polymer for protein conjugation in view of its unique properties, as well as to its low toxicity in humans, qualities which have been confirmed by its extensive use in clinical practice. Other polymers that are safe, biodegradable and custom-designed have, nevertheless, also been investigated as potential candidates for protein conjugation. This review will focus on natural polymers and synthetic linear polymers that have been used for protein delivery and the results associated with their use. Genetic fusion approaches for the preparation of protein-polypeptide conjugates will be also reviewed and compared with the best known chemical conjugation ones.

Antibiotic Conjugated Fluorescent Carbon Dots as a Theranostic Agent for Controlled Drug Release, Bioimaging, and Enhanced Antimicrobial Activity

Directory of Open Access Journals (Sweden)

Mukeshchand Thakur

2014-01-01

Full Text Available A novel report on microwave assisted synthesis of bright carbon dots (C-dots using gum arabic (GA and its use as molecular vehicle to ferry ciprofloxacin hydrochloride, a broad spectrum antibiotic, is reported in the present work. Density gradient centrifugation (DGC was used to separate different types of C-dots. After careful analysis of the fractions obtained after centrifugation, ciprofloxacin was attached to synthesize ciprofloxacin conjugated with C-dots (Cipro@C-dots conjugate. Release of ciprofloxacin was found to be extremely regulated under physiological conditions. Cipro@C-dots were found to be biocompatible on Vero cells as compared to free ciprofloxacin (1.2 mM even at very high concentrations. Bare C-dots (∼13 mg mL−1 were used for microbial imaging of the simplest eukaryotic model—Saccharomyces cerevisiae (yeast. Bright green fluorescent was obtained when live imaging was performed to view yeast cells under fluorescent microscope suggesting C-dots incorporation inside the cells. Cipro@C-dots conjugate also showed enhanced antimicrobial activity against both model gram positive and gram negative microorganisms. Thus, the Cipro@C-dots conjugate paves not only a way for bioimaging but also an efficient new nanocarrier for controlled drug release with high antimicrobial activity, thereby serving potential tool for theranostics.

Myocardial perfusion magnetic resonance imaging using sliding-window conjugate-gradient highly constrained back-projection reconstruction for detection of coronary artery disease.

Science.gov (United States)

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.

Assessing the ability to derive rates of polar middle-atmospheric descent using trace gas measurements from remote sensors

Science.gov (United States)

Ryan, Niall J.; Kinnison, Douglas E.; Garcia, Rolando R.; Hoffmann, Christoph G.; Palm, Mathias; Raffalski, Uwe; Notholt, Justus

2018-02-01

We investigate the reliability of using trace gas measurements from remote sensing instruments to infer polar atmospheric descent rates during winter within 46-86 km altitude. Using output from the Specified Dynamics Whole Atmosphere Community Climate Model (SD-WACCM) between 2008 and 2014, tendencies of carbon monoxide (CO) volume mixing ratios (VMRs) are used to assess a common assumption of dominant vertical advection of tracers during polar winter. The results show that dynamical processes other than vertical advection are not negligible, meaning that the transport rates derived from trace gas measurements do not represent the mean descent of the atmosphere. The relative importance of vertical advection is lessened, and exceeded by other processes, during periods directly before and after a sudden stratospheric warming, mainly due to an increase in eddy transport. It was also found that CO chemistry cannot be ignored in the mesosphere due to the night-time layer of OH at approximately 80 km altitude. CO VMR profiles from the Kiruna Microwave Radiometer and the Microwave Limb Sounder were compared to SD-WACCM output, and show good agreement on daily and seasonal timescales. SD-WACCM CO profiles are combined with the CO tendencies to estimate errors involved in calculating the mean descent of the atmosphere from remote sensing measurements. The results indicate errors on the same scale as the calculated descent rates, and that the method is prone to a misinterpretation of the direction of air motion. The true rate of atmospheric descent is seen to be masked by processes, other than vertical advection, that affect CO. We suggest an alternative definition of the rate calculated using remote sensing measurements: not as the mean descent of the atmosphere, but as an effective rate of vertical transport for the trace gas under observation.

Planetary entry, descent, and landing technologies

Science.gov (United States)

Pichkhadze, K.; Vorontsov, V.; Polyakov, A.; Ivankov, A.; Taalas, P.; Pellinen, R.; Harri, A.-M.; Linkin, V.

2003-04-01

Martian meteorological lander (MML) is intended for landing on the Martian surface in order to monitor the atmosphere at landing point for one Martian year. MMLs shall become the basic elements of a global network of meteorological mini-landers, observing the dynamics of changes of the atmospheric parameters on the Red Planet. The MML main scientific tasks are as follows: (1) Study of vertical structure of the Martian atmosphere throughout the MML descent; (2) On-surface meteorological observations for one Martian year. One of the essential factors influencing the lander's design is its entry, descent, and landing (EDL) sequence. During Phase A of the MML development, five different options for the lander's design were carefully analyzed. All of these options ensure the accomplishment of the above-mentioned scientific tasks with high effectiveness. CONCEPT A (conventional approach): Two lander options (with a parachute system + airbag and an inflatable airbrake + airbag) were analyzed. They are similar in terms of fulfilling braking phases and completely analogous in landing by means of airbags. CONCEPT B (innovative approach): Three lander options were analyzed. The distinguishing feature is the presence of inflatable braking units (IBU) in their configurations. SELECTED OPTION (innovative approach): Incorporating a unique design approach and modern technologies, the selected option of the lander represents a combination of the options analyzed in the framework of Concept B study. Currently, the selected lander option undergoes systems testing (Phase D1). Several MMLs can be delivered to Mars in frameworks of various missions as primary or piggybacking payload: (1) USA-led "Mars Scout" (2007); (2) France-led "NetLander" (2007/2009); (3) Russia-led "Mars-Deimos-Phobos sample return" (2007); (4) Independent mission (currently under preliminary study); etc.

On the efficiency of a randomized mirror descent algorithm in online optimization problems

Science.gov (United States)

Gasnikov, A. V.; Nesterov, Yu. E.; Spokoiny, V. G.

2015-04-01

A randomized online version of the mirror descent method is proposed. It differs from the existing versions by the randomization method. Randomization is performed at the stage of the projection of a subgradient of the function being optimized onto the unit simplex rather than at the stage of the computation of a subgradient, which is common practice. As a result, a componentwise subgradient descent with a randomly chosen component is obtained, which admits an online interpretation. This observation, for example, has made it possible to uniformly interpret results on weighting expert decisions and propose the most efficient method for searching for an equilibrium in a zero-sum two-person matrix game with sparse matrix.

Implementing the Mars Science Laboratory Terminal Descent Sensor Field Test Campaign

Science.gov (United States)

Montgomery, James F.; Bodie, James H.; Brown, Joseph D.; Chen, Allen; Chen, Curtis W.; Essmiller, John C.; Fisher, Charles D.; Goldberg, Hannah R.; Lee, Steven W.; Shaffer, Scott J.

2012-01-01

The Mars Science Laboratory (MSL) will deliver a 900 kg rover to the surface of Mars in August 2012. MSL will utilize a new pulse-Doppler landing radar, the Terminal Descent Sensor (TDS). The TDS employs six narrow-beam antennas to provide unprecedented slant range and velocity performance at Mars to enable soft touchdown of the MSL rover using a unique sky crane Entry, De-scent, and Landing (EDL) technique. Prior to use on MSL, the TDS was put through a rigorous verification and validation (V&V) process. A key element of this V&V was operating the TDS over a series of field tests, using flight-like profiles expected during the descent and landing of MSL over Mars-like terrain on Earth. Limits of TDS performance were characterized with additional testing meant to stress operational modes outside of the expected EDL flight profiles. The flight envelope over which the TDS must operate on Mars encompasses such a large range of altitudes and velocities that a variety of venues were neces-sary to cover the test space. These venues included an F/A-18 high performance aircraft, a Eurocopter AS350 AStar helicopter and 100-meter tall Echo Towers at the China Lake Naval Air Warfare Center. Testing was carried out over a five year period from July 2006 to June 2011. TDS performance was shown, in gen-eral, to be excellent over all venues. This paper describes the planning, design, and implementation of the field test campaign plus results and lessons learned.

Development and test results of a flight management algorithm for fuel conservative descents in a time-based metered traffic environment

Science.gov (United States)

Knox, C. E.; Cannon, D. G.

1980-01-01

A simple flight management descent algorithm designed to improve the accuracy of delivering an airplane in a fuel-conservative manner to a metering fix at a time designated by air traffic control was developed and flight tested. This algorithm provides a three dimensional path with terminal area time constraints (four dimensional) for an airplane to make an idle thrust, clean configured (landing gear up, flaps zero, and speed brakes retracted) descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path was calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithm is described. The results of the flight tests flown with the Terminal Configured Vehicle airplane are presented.

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

Science.gov (United States)

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

A Cockpit Comfort Level of the Descent Capsule-Shaped Vehicles

Directory of Open Access Journals (Sweden)

V. E. Minenko

2017-01-01

Full Text Available The article formulates the task of selecting a design-layout pattern for a transport spacecraft, in terms of reaching a proper comfort level for the crew to have appropriate functioning. Using the example of a domestic spacecraft and an American one, it has been shown that the type of launch vehicle, the launch specifics, the operational overloads, and the overall mass restrictions have a dramatic impact on the choice of the design-layout pattern of the spacecraft. The free volume of the pressure cockpit per each member of the crew is considered as the main characteristic to show a level of the spacecraft comfort. Using the average statistical data on the layout density of different equipment, the article estimates the possible increase of this characteristic for the cutting-edge descent vehicles. Using the example of the descent vehicles of Soyuz and Apollo class, the article shows a dependence of the raising weight of a descent vehicle on the free volume of its pressure cockpit. Attention is drawn to the fact that the limit of increasing free space of the spacecraft compartments to achieve maximum comfort should correspond to a set of functions that the crew performs in the compartments considered. Otherwise, the increase in the spacecraft mass will prove to be unjustified. The results stated in the article can be useful to developers of manned spacecraft, as well as to teachers and students. In the long term it is worthwhile adding the article material with the mass and volume indicators, as well as with the estimate results of the comfort level of modern manned spacecrafts being under design in Russia and USA, such as PTK NP (“Federation”, “Orion”, “Dragon V2”.

Optical phase conjugation

CERN Document Server

Fisher, Robert A

1983-01-01

This book appears at a time of intense activity in optical phase conjugation. We chose not to await the maturation of the field, but instead to provide this material in time to be useful in its development. We have tried very hard to elucidate and interrelate the various nonlinear phenomena which can be used for optical phase conjugation.

Qualidade conjugal: mapeando conceitos

Directory of Open Access Journals (Sweden)

Clarisse Mosmann

2006-12-01

Full Text Available Apesar da ampla utilização do conceito de qualidade conjugal, identifica-se falta de clareza conceitual acerca das variáveis que o compõem. Esse artigo apresenta revisão da literatura na área com o objetivo de mapear o conceito de qualidade conjugal. Foram analisadas sete principais teorias sobre o tema: Troca Social, Comportamental, Apego, Teoria da Crise, Interacionismo Simbólico. Pelos postulados propostos nas diferentes teorias, podem-se identificar três grupos de variáveis fundamentais na definição da qualidade conjugal: recursos pessoais dos cônjuges, contexto de inserção do casal e processos adaptativos. Neste sentido, a qualidade conjugal é resultado do processo dinâmico e interativo do casal, razão deste caráter multidimensional.

Are pregnant women of non-Northern European descent more anaemic than women of Northern European descent? A study into the prevalence of anaemia in pregnant women in Amsterdam.

NARCIS (Netherlands)

Jans, S.M.; Daemers, D.O.A.; Vos, R.; Lagro-Janssen, A.L.M.

2009-01-01

OBJECTIVES: to investigate the prevalence of anaemia in pregnancy according to the cut-off points used in the national clinical guideline 'Anaemia in Primary Care Midwifery Practice', and to investigate a possible difference in prevalence between pregnant women of Northern European descent compared

Optimal control of a variable spin speed CMG system for space vehicles. [Control Moment Gyros

Science.gov (United States)

Liu, T. C.; Chubb, W. B.; Seltzer, S. M.; Thompson, Z.

1973-01-01

Many future NASA programs require very high accurate pointing stability. These pointing requirements are well beyond anything attempted to date. This paper suggests a control system which has the capability of meeting these requirements. An optimal control law for the suggested system is specified. However, since no direct method of solution is known for this complicated system, a computation technique using successive approximations is used to develop the required solution. The method of calculus of variations is applied for estimating the changes of index of performance as well as those constraints of inequality of state variables and terminal conditions. Thus, an algorithm is obtained by the steepest descent method and/or conjugate gradient method. Numerical examples are given to show the optimal controls.

Cross-Conjugated n-Dopable Aromatic Polyketone

NARCIS (Netherlands)

Voortman, Thomas P.; Bartesaghi, Davide; Koster, L. Jan Anton; Chiechi, Ryan C.

2015-01-01

This paper describes the synthesis and characterization of a high molecular weight cross-conjugated polyketone synthesized via scalable Friedel Crafts chemistry. Cross-conjugated polyketones are precursors to conjugated polyions; they become orders of magnitude more conductive after a two-electron

Are pregnant women of non-Northern European descent more anaemic than women of Northern European descent? A study into the prevalence of anaemia in pregnant women in Amsterdam

NARCIS (Netherlands)

Jans, S. M. P. J.; Daemers, D. O. A.; de Vos, R.; Lagro-Jansen, A. L. M.

2009-01-01

to investigate the prevalence of anaemia in pregnancy according to the cut-off points used in the national clinical guideline 'Anaemia in Primary Care Midwifery Practice', and to investigate a possible difference in prevalence between pregnant women of Northern European descent compared with women

Are pregnant women of non-Northern European descent more anaemic than women of Northern European descent? A study into the prevalence of anaemia in pregnant women in Amsterdam

NARCIS (Netherlands)

Jans, S.M.P.J.; Daemers, D.O.A.; Vos, R. de; Lagro-Janssen, A.L.M.

2009-01-01

Objectives - to investigate the prevalence of anaemia in pregnancy according to the cut-off points used in the national clinical guideline ‘Anaemia in Primary Care Midwifery Practice’, and to investigate a possible difference in prevalence between pregnant women of Northern European descent compared

Anticipatory kinematics and muscle activity preceding transitions from level-ground walking to stair ascent and descent.

Science.gov (United States)

Peng, Joshua; Fey, Nicholas P; Kuiken, Todd A; Hargrove, Levi J

2016-02-29

The majority of fall-related accidents are during stair ambulation-occurring commonly at the top and bottom stairs of each flight, locations in which individuals are transitioning to stairs. Little is known about how individuals adjust their biomechanics in anticipation of walking-stair transitions. We identified the anticipatory stride mechanics of nine able-bodied individuals as they approached transitions from level ground walking to stair ascent and descent. Unlike prior investigations of stair ambulation, we analyzed two consecutive "anticipation" strides preceding the transitions strides to stairs, and tested a comprehensive set of kinematic and electromyographic (EMG) data from both the leading and trailing legs. Subjects completed ten trials of baseline overground walking and ten trials of walking to stair ascent and descent. Deviations relative to baseline were assessed. Significant changes in mechanics and EMG occurred in the earliest anticipation strides analyzed for both ascent and descent transitions. For stair descent, these changes were consistent with observed reductions in walking speed, which occurred in all anticipation strides tested. For stair ascent, subjects maintained their speed until the swing phase of the latest anticipation stride, and changes were found that would normally be observed for decreasing speed. Given the timing and nature of the observed changes, this study has implications for enhancing intent recognition systems and evaluating fall-prone or disabled individuals, by testing their abilities to sense upcoming transitions and decelerate during locomotion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nurses of African descent and career advancement.

Science.gov (United States)

Wesley, Yvonne; Dobal, May T

2009-01-01

The purpose of this article is to evaluate a leadership institute designed to promote career advancement and leadership in administration, education, and research among nurses of African descent. Government reports indicate that Black Americans receive lower quality health care than other racial groups even when insurance and income are equal. Moreover, the literature suggests that less than 10% of practicing professional nurses in America are Black-and of these, less than 1% are in senior executive leadership positions. However, the literature lacks detailed discussion of the effectiveness of leadership programs. This article provides an in-depth look at a leadership institute for Black nurses and outlines the impact of the program.

Protein carriers of conjugate vaccines

Science.gov (United States)

Pichichero, Michael E

2013-01-01

The immunogenicity of polysaccharides as human vaccines was enhanced by coupling to protein carriers. Conjugation transformed the T cell-independent polysaccharide vaccines of the past to T cell-dependent antigenic vaccines that were much more immunogenic and launched a renaissance in vaccinology. This review discusses the conjugate vaccines for prevention of infections caused by Hemophilus influenzae type b, Streptococcus pneumoniae, and Neisseria meningitidis. Specifically, the characteristics of the proteins used in the construction of the vaccines including CRM, tetanus toxoid, diphtheria toxoid, Neisseria meningitidis outer membrane complex, and Hemophilus influenzae protein D are discussed. The studies that established differences among and key features of conjugate vaccines including immunologic memory induction, reduction of nasopharyngeal colonization and herd immunity, and antibody avidity and avidity maturation are presented. Studies of dose, schedule, response to boosters, of single protein carriers with single and multiple polysaccharides, of multiple protein carriers with multiple polysaccharides and conjugate vaccines administered concurrently with other vaccines are discussed along with undesirable consequences of conjugate vaccines. The clear benefits of conjugate vaccines in improving the protective responses of the immature immune systems of young infants and the senescent immune systems of the elderly have been made clear and opened the way to development of additional vaccines using this technology for future vaccine products. PMID:23955057

Atmospheric Mars Entry and Landing Investigations & Analysis (AMELIA) by ExoMars 2016 Schiaparelli Entry Descent Module

Science.gov (United States)

Ferri, F.; Karatekin, O.; Aboudan, A.; VanHove, B.; Colombatti, C.; Bettanini, C.; Debei, S.; Lewis, S.; Forget, F.

2017-09-01

On the 19th October 2016, Schiaparelli, the Entry Demonstrator Module (EDM) of the ESA ExoMars Program entered into the martian atmosphere. Although it did not complete a safe landing on Mars, it transmitted data throughout its descent to the surface, until the loss of signal at 1 minute before the expected touch-down on Mars' surface. From the flight data, we reconstruct the actual dynamics of the vehicle during its descent towards Mars's surface and retrieve the atmospheric profile, in terms of density, pressure and temperature, along its trajectory for atmospheric investigations.

Conjugated polymer zwitterions and solar cells comprising conjugated polymer zwitterions

Science.gov (United States)

Emrick, Todd; Russell, Thomas; Page, Zachariah; Liu, Yao

2018-06-05

A conjugated polymer zwitterion includes repeating units having structure (I), (II), or a combination thereof ##STR00001## wherein Ar is independently at each occurrence a divalent substituted or unsubstituted C3-30 arylene or heteroarylene group; L is independently at each occurrence a divalent C1-16 alkylene group, C6-30arylene or heteroarylene group, or alkylene oxide group; and R1 is independently at each occurrence a zwitterion. A polymer solar cell including the conjugated polymer zwitterion is also disclosed.

Research study of conjugate materials; Conjugate material no chosa kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-03-01

The paper reported an introductory research on possibilities of new glass `conjugate materials.` The report took up the structure and synthetic process of conjugate materials to be researched/developed, classified them according to structural elements on molecular, nanometer and cluster levels, and introduced the structures and functions. Further, as glasses with new functions to be proposed, the paper introduced transparent and high-strength glass used for houses and vehicles, light modulation glass which realizes energy saving and optical data processing, and environmentally functional glass which realizes environmental cleaning or high performance biosensor. An initial survey was also conducted on rights of intellectual property to be taken notice of in Japan and abroad in the present situation. Reports were summed up and introduced of Osaka National Research Institute, Electrotechnical Laboratory, and National Industrial Research Institute of Nagoya which are all carrying out leading studies of conjugate materials. 235 refs., 135 figs., 6 tabs.

Trajectory Guidance for Mars Robotic Precursors: Aerocapture, Entry, Descent, and Landing

Science.gov (United States)

Sostaric, Ronald R.; Zumwalt, Carlie; Garcia-Llama, Eduardo; Powell, Richard; Shidner, Jeremy

2011-01-01

Future crewed missions to Mars require improvements in landed mass capability beyond that which is possible using state-of-the-art Mars Entry, Descent, and Landing (EDL) systems. Current systems are capable of an estimated maximum landed mass of 1-1.5 metric tons (MT), while human Mars studies require 20-40 MT. A set of technologies were investigated by the EDL Systems Analysis (SA) project to assess the performance of candidate EDL architectures. A single architecture was selected for the design of a robotic precursor mission, entitled Exploration Feed Forward (EFF), whose objective is to demonstrate these technologies. In particular, inflatable aerodynamic decelerators (IADs) and supersonic retro-propulsion (SRP) have been shown to have the greatest mass benefit and extensibility to future exploration missions. In order to evaluate these technologies and develop the mission, candidate guidance algorithms have been coded into the simulation for the purposes of studying system performance. These guidance algorithms include aerocapture, entry, and powered descent. The performance of the algorithms for each of these phases in the presence of dispersions has been assessed using a Monte Carlo technique.

'The full has never been told': building a theory of sexual health for heterosexual Black men of Caribbean descent.

Science.gov (United States)

Crowell, Candice N; Delgado-Romero, Edward A; Mosley, Della V; Huynh, Sophia

2016-08-01

Research on Black sexual health often fails to represent the heterogeneity of Black ethnic groups. For people of Caribbean descent in the USA, ethnicity is a salient cultural factor that influences definitions and experiences of sexual health. Most research on people of Caribbean descent focuses on the relatively high rate of STIs, but sexual health is defined more broadly than STI prevalence. Psychological and emotional indicators and the voice of participants are important to consider when exploring the sexual health of a minority culture. The purpose of this study was to qualitatively explore how heterosexual Black men of Caribbean descent define and understand sexual health for themselves. Eleven men who self-identified as Black, Caribbean and heterosexual participated in three focus groups and were asked to define sexual health, critique behaviours expertly identified as healthy and address what encourages and discourages sexual health in their lives. Findings point to six dimensions of sexual health for heterosexual Black men of Caribbean descent. These include: heterosexually privileged, protective, contextual, interpersonal, cultural and pleasurable dimensions. There were some notable departures from current expert definitions of sexual health. Recommendations for further theory development are provided.

Misonidazole-glutathione conjugates in CHO cells

International Nuclear Information System (INIS)

Varghese, A.J.; Whitmore, G.F.

1984-01-01

Misonidazole, after reduction to the hydroxylamine derivative, reacts with glutathione (GSH) under physiological conditions. The reaction product has been identified as a mixture of two isomeric conjugates. When water soluble extracts of CHO cells exposed to misonidazole under hypoxic conditions are subjected to HPLC analysis, misonidazole derivatives, having the same chromatographic properties as the GSH-MISO conjugates, were detected. When CHO cells were incubated with misonidazole in the presence of added GSH, a substantial increase in the amount of the conjugate was detected. When extracts of CHO cells exposed to misonidazole under hypoxia were subsequently exposed to GSH, an increased formation of the conjugate was observed. A rearrangement product of the hydroxylamine derivative of misonidazole is postulated as the reactive intermediate responsible for the formation of the conjugate

Modelling conjugation with stochastic differential equations

DEFF Research Database (Denmark)

Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Hasman, Henrik

2010-01-01

Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared......Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two...... using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared...

Poly(2-oxazoline)-Antibiotic Conjugates with Penicillins.

Science.gov (United States)

Schmidt, Martin; Bast, Livia K; Lanfer, Franziska; Richter, Lena; Hennes, Elisabeth; Seymen, Rana; Krumm, Christian; Tiller, Joerg C

2017-09-20

The conjugation of antibiotics with polymers is rarely done, but it might be a promising alternative to low-molecular-weight derivatization. The two penicillins penicillin G (PenG) and penicillin V (PenV) were attached to the end groups of different water-soluble poly(2-oxazoline)s (POx) via their carboxylic acid function. This ester group was shown to be more stable against hydrolysis than the β-lactam ring of the penicillins. The conjugates are still antimicrobially active and up to 20 times more stable against penicillinase catalyzed hydrolysis. The antibiotic activity of the conjugates against Staphylococcus aureus in the presence of penicillinase is up to 350 times higher compared with the free antibiotics. Conjugates with a second antimicrobial function, a dodecyltrimethylammonium group (DDA-X), at the starting end of the PenG and PenV POx conjugates are more antimicrobially active than the conjugates without DDA-X and show high activity in the presence of penicillinase. For example, the conjugates DDA-X-PEtOx-PenG and DDA-X-PEtOx-PenV are 200 to 350 times more active against S. aureus in the presence of penicillinase and almost as effective as the penicillinase stable cloxacollin (Clox) under these conditions. These conjugates show even greater activity compared to cloxacollin without this enzyme present. Further, both conjugates kill Escherichia coli more effectively than PenG and Clox.

Cardiovascular disease, diabetes and established risk factors among populations of sub-Saharan African descent in Europe: a literature review

Directory of Open Access Journals (Sweden)

de Graft Aikins Ama

2009-08-01

Full Text Available Abstract Background Most European countries are ethnically and culturally diverse. Globally, cardiovascular disease (CVD is the leading cause of death. The major risk factors for CVD have been well established. This picture holds true for all regions of the world and in different ethnic groups. However, the prevalence of CVD and related risk factors vary among ethnic groups. Methods This article provides a review of current understanding of the epidemiology of vascular disease, principally coronary heart disease (CHD, stroke and related risk factors among populations of Sub-Sahara African descent (henceforth, African descent in comparison with the European populations in Europe. Results Compared with European populations, populations of African descent have an increased risk of stroke, whereas CHD is less common. They also have higher rates of hypertension and diabetes than European populations. Obesity is highly prevalent, but smoking rate is lower among African descent women. Older people of African descent have more favourable lipid profile and dietary habits than their European counterparts. Alcohol consumption is less common among populations of African descent. The rate of physical activity differs between European countries. Dutch African-Suriname men and women are less physically active than the White-Dutch whereas British African women are more physically active than women in the general population. Literature on psychosocial stress shows inconsistent results. Conclusion Hypertension and diabetes are highly prevalent among African populations, which may explain their high rate of stroke in Europe. The relatively low rate of CHD may be explained by the low rates of other risk factors including a more favourable lipid profile and the low prevalence of smoking. The risk factors are changing, and on the whole, getting worse especially among African women. Cohort studies and clinical trials are therefore needed among these groups to

Distributed Coordinate Descent Method for Learning with Big Data

OpenAIRE

Richtárik, Peter; Takáč, Martin

2013-01-01

In this paper we develop and analyze Hydra: HYbriD cooRdinAte descent method for solving loss minimization problems with big data. We initially partition the coordinates (features) and assign each partition to a different node of a cluster. At every iteration, each node picks a random subset of the coordinates from those it owns, independently from the other computers, and in parallel computes and applies updates to the selected coordinates based on a simple closed-form formula. We give bound...

Convergence results for a class of abstract continuous descent methods

Directory of Open Access Journals (Sweden)

Sergiu Aizicovici

2004-03-01

Full Text Available We study continuous descent methods for the minimization of Lipschitzian functions defined on a general Banach space. We establish convergence theorems for those methods which are generated by approximate solutions to evolution equations governed by regular vector fields. Since the complement of the set of regular vector fields is $sigma$-porous, we conclude that our results apply to most vector fields in the sense of Baire's categories.

Gradient-based methods for production optimization of oil reservoirs

Energy Technology Data Exchange (ETDEWEB)

Suwartadi, Eka

2012-07-01

Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM

Preparation, structural analysis and bioactivity of ribonuclease A-albumin conjugate: tetra-conjugation or PEG as the linker.

Science.gov (United States)

Li, Chunju; Lin, Qixun; Wang, Jun; Shen, Lijuan; Ma, Guanghui; Su, Zhiguo; Hu, Tao

2012-12-31

Ribonuclease A (RNase A) is a therapeutic enzyme with cytotoxic action against tumor cells. Its clinical application is limited by the short half-life and insufficient stability. Conjugation of albumin can overcome the limitation, whereas dramatically decrease the enzymatic activity of RNase A. Here, three strategies were proposed to prepare the RNase A-bovine serum albumin (BSA) conjugates. R-SMCC-B (a conjugate of four RNase A attached with one BSA) and R-PEG-B (a mono-conjugate) were prepared using Sulfo-SMCC (a short bifunctional linker) and mal-PEG-NHS (a bifunctional PEG), respectively. Mal-PEG-NHS and hexadecylamine (HDA) were used to prepare the mono-conjugate, R-HDA-B, where HDA was adopted to bind BSA. The PEG linker can elongate the proximity between RNase A and BSA. In contrast, four RNase A were closely located on BSA in R-SMCC-B. R-SMCC-B showed the lowest K(m) and the highest relative enzymatic activity and k(cat)/K(m) in the three conjugates. Presumably, the tetravalent interaction of RNase A in R-SMCC-B can increase the binding affinity to its substrate. In addition, the slow release of BSA from R-HDA-B may increase the enzymatic activity of R-HDA-B. Our study is expected to provide strategies to develop protein-albumin conjugate with high therapeutic potential. Copyright © 2012 Elsevier B.V. All rights reserved.

Predictive Modeling for NASA Entry, Descent and Landing Missions

Science.gov (United States)

Wright, Michael

2016-01-01

Entry, Descent and Landing (EDL) Modeling and Simulation (MS) is an enabling capability for complex NASA entry missions such as MSL and Orion. MS is used in every mission phase to define mission concepts, select appropriate architectures, design EDL systems, quantify margin and risk, ensure correct system operation, and analyze data returned from the entry. In an environment where it is impossible to fully test EDL concepts on the ground prior to use, accurate MS capability is required to extrapolate ground test results to expected flight performance.

Chemical de-conjugation for investigating the stability of small molecule drugs in antibody-drug conjugates.

Science.gov (United States)

Chen, Tao; Su, Dian; Gruenhagen, Jason; Gu, Christine; Li, Yi; Yehl, Peter; Chetwyn, Nik P; Medley, Colin D

2016-01-05

Antibody-drug conjugates (ADCs) offer new therapeutic options for advanced cancer patients through precision killing with fewer side effects. The stability and efficacy of ADCs are closely related, emphasizing the urgency and importance of gaining a comprehensive understanding of ADC stability. In this work, a chemical de-conjugation approach was developed to investigate the in-situ stability of the small molecule drug while it is conjugated to the antibody. This method involves chemical-mediated release of the small molecule drug from the ADC and subsequent characterization of the released small molecule drug by HPLC. The feasibility of this technique was demonstrated utilizing a model ADC containing a disulfide linker that is sensitive to the reducing environment within cancer cells. Five reducing agents were screened for use in de-conjugation; tris(2-carboxyethyl) phosphine (TCEP) was selected for further optimization due to its high efficiency and clean impurity profile. The optimized de-conjugation assay was shown to have excellent specificity and precision. More importantly, it was shown to be stability indicating, enabling the identification and quantification of the small molecule drug and its degradation products under different formulation pHs and storage temperatures. In summary, the chemical de-conjugation strategy demonstrated here offers a powerful tool to assess the in-situ stability of small molecule drugs on ADCs and the resulting information will shed light on ADC formulation/process development and storage condition selection. Copyright © 2015 Elsevier B.V. All rights reserved.

Long-Time Asymptotics for the Korteweg-de Vries Equation via Nonlinear Steepest Descent

International Nuclear Information System (INIS)

Grunert, Katrin; Teschl, Gerald

2009-01-01

We apply the method of nonlinear steepest descent to compute the long-time asymptotics of the Korteweg-de Vries equation for decaying initial data in the soliton and similarity region. This paper can be viewed as an expository introduction to this method

Photoluminescence in conjugated polymers

International Nuclear Information System (INIS)

Furst, J.E.; Laugesen, R.; Dastoor, P.; McNeill, C.

2002-01-01

Full text: Conjugated polymers combine the electronic and optical properties of semiconductors with the processability of polymers. They contain a sequence of alternate single and double carbon bonds so that the overlap of unhybridised p z orbitals creates a delocalised ρ system which gives semiconducting properties with p-bonding (valence) and p* -antibonding (conduction) bands. Photoluminesence (PL) in conjugated polymers results from the radiative decay of singlet excitons confined to a single chain. The present work is the first in a series of studies in our laboratory that will characterize the optical properties of conjugated polymers. The experiment involves the illumination of thin films of conjugated polymer with UV light (I=360 nm) and observing the subsequent fluorescence using a custom-built, fluorescence spectrometer. Photoluminesence spectra provide basic information about the structure of the polymer film. A typical spectrum is shown in the accompanying figure. The position of the first peak is related to the polymer chain length and resolved multiple vibronic peaks are an indication of film structure and morphology. We will also present results related to the optical degradation of these materials when exposed to air and UV light

Improving Robot Locomotion Through Learning Methods for Expensive Black-Box Systems

Science.gov (United States)

2013-11-01

in an industrial process, or the prescribed dosage of a drug during development. Definition (Environment Parameter). The environment parameter space...line indicates the deviation of this approximation from the original (right axis scale). The secondary gradient descent optimization over the linear...done through gradient descent on the representational error, cycling through all points one at a. t ime until convergence is reached. Figure 7.5 shows

Bio-Conjugates for Nanoscale Applications

DEFF Research Database (Denmark)

Villadsen, Klaus

Bio-conjugates for Nanoscale Applications is the title of this thesis, which covers three different projects in chemical bio-conjugation research, namely synthesis and applications of: Lipidated fluorescent peptides, carbohydrate oxime-azide linkers and N-aryl O-R2 oxyamine derivatives. Lipidated...

Attitudes towards and perceptions about contraceptive use among married refugee women of Somali descent living in Finland.

Science.gov (United States)

Degni, F; Koivusilta, L; Ojanlatva, A

2006-09-01

To assess attitudes towards and perceptions about contraceptive use among married refugee women of Somali descent living in Finland. A sample of 100 married refugee women of Somali descent (18-50 years of age) were invited to participate in a study on contraceptive use in Finland (30 women refused). Qualitative and quantitative methods were used to collect the data. Questionnaire of the first data set was written in the Somali language. Interviews were conducted in the Somali language. The attitudes and opinions of these women towards contraceptive use (73% did not use contraceptives, 27% did use them) were connected with religious beliefs and issues involving marital relations. Religious or gender issues did not seem to influence those who used contraception. The findings indicated that the majority of the married refugee women of Somali descent living in Finland did not use contraception. The process of starting the use of contraception was possible because of an access to good reproductive health care and family planning services, changes in life situations, and adaptations to Finnish social and cultural norms.

Interplay of alternative conjugated pathways and steric interactions on the electronic and optical properties of donor-acceptor conjugated polymers

KAUST Repository

Lima, Igo T.; Risko, Chad; Aziz, Saadullah Gary; Da Silva Filho, Demé trio A Da Silva; Bredas, Jean-Luc

2014-01-01

Donor-acceptor π-conjugated copolymers are of interest for a wide range of electronic applications, including field-effect transistors and solar cells. Here, we present a density functional theory (DFT) study of the impact of varying the conjugation pathway on the geometric, electronic, and optical properties of donor-acceptor systems. We consider both linear ("in series"), traditional conjugation among the donor-acceptor moieties versus structures where the acceptor units are appended orthogonally to the linear, donor-only conjugated backbone. Long-range-corrected hybrid functionals are used in the investigation with the values of the tuned long-range separation parameters providing an estimate of the extent of conjugation as a function of the oligomer architecture. Considerable differences in the electronic and optical properties are determined as a function of the nature of the conjugation pathway, features that should be taken into account in the design of donor-acceptor copolymers.

Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent

Directory of Open Access Journals (Sweden)

Zunyi Tang

2013-01-01

Full Text Available Sparse representation of signals via an overcomplete dictionary has recently received much attention as it has produced promising results in various applications. Since the nonnegativities of the signals and the dictionary are required in some applications, for example, multispectral data analysis, the conventional dictionary learning methods imposed simply with nonnegativity may become inapplicable. In this paper, we propose a novel method for learning a nonnegative, overcomplete dictionary for such a case. This is accomplished by posing the sparse representation of nonnegative signals as a problem of nonnegative matrix factorization (NMF with a sparsity constraint. By employing the coordinate descent strategy for optimization and extending it to multivariable case for processing in parallel, we develop a so-called parallel coordinate descent dictionary learning (PCDDL algorithm, which is structured by iteratively solving the two optimal problems, the learning process of the dictionary and the estimating process of the coefficients for constructing the signals. Numerical experiments demonstrate that the proposed algorithm performs better than the conventional nonnegative K-SVD (NN-KSVD algorithm and several other algorithms for comparison. What is more, its computational consumption is remarkably lower than that of the compared algorithms.

Kinematic analyses during stair descent in young women with patellofemoral pain.

Science.gov (United States)

Grenholm, Anton; Stensdotter, Ann-Katrin; Häger-Ross, Charlotte

2009-01-01

Compensatory movement strategies may develop in response to pain to avoid stress on the affected area. Patellofemoral pain is characterised by intermittent periods of pain and the present study addresses whether long-term pain leads to compensatory movement strategies that remain even when the pain is absent. Lower extremity kinematics in three dimensions was studied in stair descent in 17 women with patellofemoral and in 17 matched controls. A two-dimensional geometric model was constructed to normalise kinematic data for subjects with varying anthropometrics when negotiating stairs of fixed proportions. There were minor differences in movement patterns between groups. Knee joint angular velocity in the stance leg at foot contact was lower and the movement trajectory tended to be jerkier in the patellofemoral group. The two-dimensional model showed greater plantar flexion in the swing leg in preparation for foot placement in the patellofemoral group. The results indicate that an altered stair descent strategy in the patellofemoral group may remain also in the absence of pain. The biomechanical interpretation presumes that the strategy is aimed to reduce knee joint loading by less knee joint moment and lower impact force.

Vertical Descent and Landing Tests of a 0.13-Scale Model of the Convair XFY-1 Vertically Rising Airplane in Still Air, TED No. NACA DE 368

Science.gov (United States)

Smith, Charlee C., Jr.; Lovell, Powell M., Jr.

1954-01-01

An investigation is being conducted to determine the dynamic stability and control characteristics of a 0.13-scale flying model of Convair XFY-1 vertically rising airplane. This paper presents the results of flight and force tests to determine the stability and control characteristics of the model in vertical descent and landings in still air. The tests indicated that landings, including vertical descent from altitudes representing up to 400 feet for the full-scale airplane and at rates of descent up to 15 or 20 feet per second (full scale), can be performed satisfactorily. Sustained vertical descent in still air probably will be more difficult to perform because of large random trim changes that become greater as the descent velocity is increased. A slight steady head wind or cross wind might be sufficient to eliminate the random trim changes.

Vehicle Staging Analysis of the Transition to Supersonic Retropropulsion During Mars Entry, Descent, and Landing

Data.gov (United States)

National Aeronautics and Space Administration — The landing of the Mars Science Laboratory represents the upper limit of current Entry, Descent, and Landing (EDL) capabilities for Mars exploration. The succession...

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems

Energy Technology Data Exchange (ETDEWEB)

Scherrer, Chad; Halappanavar, Mahantesh; Tewari, Ambuj; Haglin, David J.

2012-07-03

We present a generic framework for parallel coordinate descent (CD) algorithms that has as special cases the original sequential algorithms of Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm of Bradley et al. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and Coloring-Based CD---and give performance measurements for an OpenMP implementation of these.

Organometallic B12-DNA conjugate

DEFF Research Database (Denmark)

Hunger, Miriam; Mutti, Elena; Rieder, Alexander

2014-01-01

Design, synthesis, and structural characterization of a B12-octadecanucleotide are presented herein, a new organometallic B12-DNA conjugate. In such covalent conjugates, the natural B12 moiety may be a versatile vector for controlled in vivo delivery of oligonucleotides to cellular targets in hum...

The Conjugate Acid-Base Chart.

Science.gov (United States)

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)

A unified framework of descent algorithms for nonlinear programs and variational inequalities

International Nuclear Information System (INIS)

Patriksson, M.

1993-01-01

We present a framework of algorithms for the solution of continuous optimization and variational inequality problems. In the general algorithm, a search direction finding auxiliary problems is obtained by replacing the original cost function with an approximating monotone cost function. The proposed framework encompasses algorithm classes presented earlier by Cohen, Dafermos, Migdalas, and Tseng, and includes numerous descent and successive approximation type methods, such as Newton methods, Jacobi and Gauss-Siedel type decomposition methods for problems defined over Cartesian product sets, and proximal point methods, among others. The auxiliary problem of the general algorithm also induces equivalent optimization reformulation and descent methods for asymmetric variational inequalities. We study the convergence properties of the general algorithm when applied to unconstrained optimization, nondifferentiable optimization, constrained differentiable optimization, and variational inequalities; the emphasis of the convergence analyses is placed on basic convergence results, convergence using different line search strategies and truncated subproblem solutions, and convergence rate results. This analysis offer a unification of known results; moreover, it provides strengthenings of convergence results for many existing algorithms, and indicates possible improvements of their realizations. 482 refs

Entry, Descent, and Landing Communications for the 2011 Mars Science Laboratory

Science.gov (United States)

Abilleira, Fernando; Shidner, Jeremy D.

2012-01-01

The Mars Science Laboratory (MSL), established as the most advanced rover to land on the surface of Mars to date, launched on November 26th, 2011 and arrived to the Martian Gale Crater during the night of August 5th, 2012 (PDT). MSL will investigate whether the landing region was ever suitable to support carbon-based life, and examine rocks, soil, and the atmosphere with a sophisticated suite of tools. This paper addresses the flight system requirement by which the vehicle transmitted indications of the following events using both X-band tones and UHF telemetry to allow identification of probable root causes should a mission anomaly have occurred: Heat-Rejection System (HRS) venting, completion of the cruise stage separation, turn to entry attitude, atmospheric deceleration, bank angle reversal commanded, parachute deployment, heatshield separation, radar ground acquisition, powered descent initiation, rover separation from the descent stage, and rover release. During Entry, Descent, and Landing (EDL), the flight system transmitted a UHF telemetry stream adequate to determine the state of the spacecraft (including the presence of faults) at 8 kbps initiating from cruise stage separation through at least one minute after positive indication of rover release on the surface of Mars. The flight system also transmitted X-band semaphore tones from Entry to Landing plus one minute although since MSL was occulted, as predicted, by Mars as seen from the Earth, Direct-To-Earth (DTE) communications were interrupted at approximately is approx. 5 min after Entry ( approximately 130 prior to Landing). The primary data return paths were through the Deep Space Network (DSN) for DTE and the existing Mars network of orbiting assets for UHF, which included the Mars Reconnaissance Orbiter (MRO), Mars Odyssey (ODY), and Mars Express (MEX) elements. These orbiters recorded the telemetry data stream and returned it back to Earth via the DSN. The paper also discusses the total power

REVIEW ARTICLE Conjugated Hyperbilirubinaemia in Early Infancy ...

African Journals Online (AJOL)

REVIEW ARTICLE Conjugated Hyperbilirubinaemia in Early Infancy. AOK Johnson. Abstract. Conjugated hyperbilirubinaemia exists when the conjugated serum bilirubin level is more than 2 mg/dl or more than 20 per cent of the total serum bilirubin. It is always pathological in early infancy. The causes are many and diverse ...

Modelling the descent of nitric oxide during the elevated stratopause event of January 2013

Science.gov (United States)

Orsolini, Yvan J.; Limpasuvan, Varavut; Pérot, Kristell; Espy, Patrick; Hibbins, Robert; Lossow, Stefan; Raaholt Larsson, Katarina; Murtagh, Donal

2017-03-01

Using simulations with a whole-atmosphere chemistry-climate model nudged by meteorological analyses, global satellite observations of nitrogen oxide (NO) and water vapour by the Sub-Millimetre Radiometer instrument (SMR), of temperature by the Microwave Limb Sounder (MLS), as well as local radar observations, this study examines the recent major stratospheric sudden warming accompanied by an elevated stratopause event (ESE) that occurred in January 2013. We examine dynamical processes during the ESE, including the role of planetary wave, gravity wave and tidal forcing on the initiation of the descent in the mesosphere-lower thermosphere (MLT) and its continuation throughout the mesosphere and stratosphere, as well as the impact of model eddy diffusion. We analyse the transport of NO and find the model underestimates the large descent of NO compared to SMR observations. We demonstrate that the discrepancy arises abruptly in the MLT region at a time when the resolved wave forcing and the planetary wave activity increase, just before the elevated stratopause reforms. The discrepancy persists despite doubling the model eddy diffusion. While the simulations reproduce an enhancement of the semi-diurnal tide following the onset of the 2013 SSW, corroborating new meteor radar observations at high northern latitudes over Trondheim (63.4°N), the modelled tidal contribution to the forcing of the mean meridional circulation and to the descent is a small portion of the resolved wave forcing, and lags it by about ten days.

Smooth and robust solutions for Dirichlet boundary control of fluid-solid conjugate heat transfer problems

KAUST Repository

Yan, Yan

2015-01-01

We study a new optimization scheme that generates smooth and robust solutions for Dirichlet velocity boundary control (DVBC) of conjugate heat transfer (CHT) processes. The solutions to the DVBC of the incompressible Navier-Stokes equations are typically nonsmooth, due to the regularity degradation of the boundary stress in the adjoint Navier-Stokes equations. This nonsmoothness is inherited by the solutions to the DVBC of CHT processes, since the CHT process couples the Navier-Stokes equations of fluid motion with the convection-diffusion equations of fluid-solid thermal interaction. Our objective in the CHT boundary control problem is to select optimally the fluid inflow profile that minimizes an objective function that involves the sum of the mismatch between the temperature distribution in the fluid system and a prescribed temperature profile and the cost of the control.Our strategy to resolve the nonsmoothness of the boundary control solution is based on two features, namely, the objective function with a regularization term on the gradient of the control profile on both the continuous and the discrete levels, and the optimization scheme with either explicit or implicit smoothing effects, such as the smoothed Steepest Descent and the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) methods. Our strategy to achieve the robustness of the solution process is based on combining the smoothed optimization scheme with the numerical continuation technique on the regularization parameters in the objective function. In the section of numerical studies, we present two suites of experiments. In the first one, we demonstrate the feasibility and effectiveness of our numerical schemes in recovering the boundary control profile of the standard case of a Poiseuille flow. In the second one, we illustrate the robustness of our optimization schemes via solving more challenging DVBC problems for both the channel flow and the flow past a square cylinder, which use initial

Broiler weight estimation based on machine vision and artificial neural network.

Science.gov (United States)

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.

Entry, Descent and Landing Systems Analysis: Exploration Feed Forward Internal Peer Review Slide Package

Science.gov (United States)

Dwyer Cianciolo, Alicia M. (Editor)

2011-01-01

NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to successfully land large payloads at Mars for both robotic and human-scale missions. Year 1 of the study focused on technologies required for Exploration-class missions to land payloads of 10 to 50 mt. Inflatable decelerators, rigid aeroshell and supersonic retro-propulsion emerged as the top candidate technologies. In Year 2 of the study, low TRL technologies identified in Year 1, inflatables aeroshells and supersonic retropropulsion, were combined to create a demonstration precursor robotic mission. This part of the EDL-SA Year 2 effort, called Exploration Feed Forward (EFF), took much of the systems analysis simulation and component model development from Year 1 to the next level of detail.

Application of optical phase conjugation to plasma diagnostics (invited)

International Nuclear Information System (INIS)

Jahoda, F.C.; Anderson, B.T.; Forman, P.R.; Weber, P.G.

1985-01-01

Several possibilities for plasma diagnostics provided by optical phase conjugation and, in particular, self-pumped phase conjugation in barium titanate (BaTiO 3 ) are discussed. These include placing a plasma within a dye laser cavity equipped with a phase conjugate mirror for intracavity absorption measurements, time differential refractometry with high spatial resolution, and simplified real-time holographic interferometry. The principles of phase conjugation with particular reference to photorefractive media and the special advantages of self-pumped phase conjugation are reviewed prior to the discussion of the applications. Distinctions are made in the applications between those for which photorefractive conjugators are essential and those for which they only offer experimental simplification relative to other types of phase conjugators

Self-assembly of pi-conjugated peptides in aqueous environments leading to energy-transporting bioelectronic nanostructures

Energy Technology Data Exchange (ETDEWEB)

Tavor, John [Johns Hopkins Univ., Baltimore, MD (United States)

2016-12-06

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 to 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.

Global Convergence of Arbitrary-Block Gradient Methods for Generalized Polyak-{\\L} ojasiewicz Functions

KAUST Repository

Csiba, Dominik

2017-09-09

In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.

Global Convergence of Arbitrary-Block Gradient Methods for Generalized Polyak-{\\L} ojasiewicz Functions

KAUST Repository

Csiba, Dominik; Richtarik, Peter

2017-01-01

In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.

Methotrexate and epirubicin conjugates as potential antitumor drugs

Directory of Open Access Journals (Sweden)

Szymon Wojciech Kmiecik

2017-07-01

Full Text Available Introduction: The use of hybrid molecules has become one of the most significant approaches in new cytotoxic drug design. This study describes synthesis and characterization of conjugates consisting of two well-known and characterized chemotherapeutic agents: methotrexate (MTX and epirubicin (EPR. The synthesized conjugates combine two significant anticancer strategies: combinatory therapy and targeted therapy. These two drugs were chosen because they have different mechanisms of action, which can increase the anticancer effect of the obtained conjugates. MTX, which is a folic acid analog, has high cytotoxic properties and can serve as a targeting moiety that can reach folate receptors (FRs overexpresing tumor cells. Combination of nonselective drugs such as EPR with MTX can increase the selectivity of the obtained conjugates, while maintaining the high cytotoxic properties.Materials and methods: Conjugates were purified by RP-HPLC and the structure was investigated by MS and MS/MS methods. The effect of the conjugates on proliferation of LoVo, LoVo/Dx, MCF-7 and MV-4-11 human cancer cell lines was determined by SRB or MTT assay.Results: The conjugation reaction results in the formation of monosubstituted (α, γ and disubstituted MTX derivatives. In vitro proliferation data demonstrate that the conjugates synthesized in our study show lower cytotoxic properties than both chemotherapeutics used alone.Discussion: Epirubicin cytotoxicity was not observed in obtained conjugates. Effective drugs release after internalization needs further investigation.

Effects of Conjugate Gradient Methods and Step-Length Formulas on the Multiscale Full Waveform Inversion in Time Domain: Numerical Experiments

Science.gov (United States)

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

Non-covalent functionalization of single wall carbon nanotubes and graphene by a conjugated polymer

KAUST Repository

Jiwuer, Jilili

2014-07-07

We report first-principles calculations on the binding of poly[(9,9-bis-(6-bromohexylfluorene-2,7-diyl)-co-(benzene-1,4-diyl)] to a (8,0) single wall carbon nanotube (SWCNT) and to graphene. Considering different relative orientations of the subsystems, we find for the generalized gradient approximation a non-binding state, whereas the local density approximation predicts reasonable binding energies. The results coincide after inclusion of van der Waals corrections, which demonstrates a weak interaction between the polymer and SWCNT/graphene, mostly of van der Waals type. Accordingly, the density of states shows essentially no hybridization. The physisorption mechanism explains recent experimental observations and suggests that the conjugated polymer can be used for non-covalent functionalization.

Non-covalent functionalization of single wall carbon nanotubes and graphene by a conjugated polymer

KAUST Repository

Jiwuer, Jilili; Abdurahman, Ayjamal; Gü lseren, Oğuz; Schwingenschlö gl, Udo

2014-01-01

We report first-principles calculations on the binding of poly[(9,9-bis-(6-bromohexylfluorene-2,7-diyl)-co-(benzene-1,4-diyl)] to a (8,0) single wall carbon nanotube (SWCNT) and to graphene. Considering different relative orientations of the subsystems, we find for the generalized gradient approximation a non-binding state, whereas the local density approximation predicts reasonable binding energies. The results coincide after inclusion of van der Waals corrections, which demonstrates a weak interaction between the polymer and SWCNT/graphene, mostly of van der Waals type. Accordingly, the density of states shows essentially no hybridization. The physisorption mechanism explains recent experimental observations and suggests that the conjugated polymer can be used for non-covalent functionalization.

Interaction between ADH1B*3 and alcohol-facilitating social environments in alcohol behaviors among college students of african descent.

Science.gov (United States)

Desalu, Jessica M; Zaso, Michelle J; Kim, Jueun; Belote, John M; Park, Aesoon

2017-06-01

Although alcohol-facilitating social environmental factors, such as alcohol offers and high perceived peer drinking norms, have been extensively studied as determinants of college drinking, their role among college students of African descent remains understudied. Furthermore, gene-environment interaction research suggests that the effects of alcohol-facilitating environments may differ as a function of genetic factors. Specifically, the alcohol dehydrogenase gene's ADH1B*3 allele, found almost exclusively in persons of African descent, may modulate the association of risky social environments with alcohol behaviors. The current study examined whether the ADH1B*3 allele attenuated the relationship between alcohol-facilitating environments (ie, alcohol offers and perceived peer drinking norms) and alcohol behaviors. Participants were 241 undergraduate students who self-identified as being of African descent (mean age = 20 years [SD = 4.11]; 66% female). Significant interaction effects of ADH1B*3 with alcohol offers were found on alcohol use frequency (incidence rate ratio [IRR] = 1.14) and on drinking consequences (IRR = 1.21). ADH1B*3 also interacted with perceived peer norms on drinking consequences (IRR = 1.41). Carriers of the ADH1B*3 allele drank less frequently and experienced fewer negative consequences than non-carriers when exposed to lower levels of alcohol offers and perceived peer drinking. In contrast, in high alcohol-facilitating environments, no protective genetic effect was observed. This study demonstrates that ADH1B*3 may protect college students of African descent against alcohol outcomes, although only in low alcohol-facilitating environments. Findings add to the growing body of knowledge regarding genetic and social determinants of alcohol behaviors among college students of African descent. (Am J Addict 2017;26:349-356). © 2017 American Academy of Addiction Psychiatry.

Multivalent peptidic linker enables identification of preferred sites of conjugation for a potent thialanstatin antibody drug conjugate.

Directory of Open Access Journals (Sweden)

Sujiet Puthenveetil

Full Text Available Antibody drug conjugates (ADCs are no longer an unknown entity in the field of cancer therapy with the success of marketed ADCs like ADCETRIS and KADCYLA and numerous others advancing through clinical trials. The pursuit of novel cytotoxic payloads beyond the mictotubule inhibitors and DNA damaging agents has led us to the recent discovery of an mRNA splicing inhibitor, thailanstatin, as a potent ADC payload. In our previous work, we observed that the potency of this payload was uniquely tied to the method of conjugation, with lysine conjugates showing much superior potency as compared to cysteine conjugates. However, the ADC field is rapidly shifting towards site-specific ADCs due to their advantages in manufacturability, characterization and safety. In this work we report the identification of a highly efficacious site-specific thailanstatin ADC. The site of conjugation played a critical role on both the in vitro and in vivo potency of these ADCs. During the course of this study, we developed a novel methodology of loading a single site with multiple payloads using an in situ generated multi-drug carrying peptidic linker that allowed us to rapidly screen for optimal conjugation sites. Using this methodology, we were able to identify a double-cysteine mutant ADC delivering four-loaded thailanstatin that was very efficacious in a gastric cancer xenograft model at 3mg/kg and was also shown to be efficacious against T-DM1 resistant and MDR1 overexpressing tumor cell lines.

Multivalent peptidic linker enables identification of preferred sites of conjugation for a potent thialanstatin antibody drug conjugate.

Science.gov (United States)

Puthenveetil, Sujiet; He, Haiyin; Loganzo, Frank; Musto, Sylvia; Teske, Jesse; Green, Michael; Tan, Xingzhi; Hosselet, Christine; Lucas, Judy; Tumey, L Nathan; Sapra, Puja; Subramanyam, Chakrapani; O'Donnell, Christopher J; Graziani, Edmund I

2017-01-01

Antibody drug conjugates (ADCs) are no longer an unknown entity in the field of cancer therapy with the success of marketed ADCs like ADCETRIS and KADCYLA and numerous others advancing through clinical trials. The pursuit of novel cytotoxic payloads beyond the mictotubule inhibitors and DNA damaging agents has led us to the recent discovery of an mRNA splicing inhibitor, thailanstatin, as a potent ADC payload. In our previous work, we observed that the potency of this payload was uniquely tied to the method of conjugation, with lysine conjugates showing much superior potency as compared to cysteine conjugates. However, the ADC field is rapidly shifting towards site-specific ADCs due to their advantages in manufacturability, characterization and safety. In this work we report the identification of a highly efficacious site-specific thailanstatin ADC. The site of conjugation played a critical role on both the in vitro and in vivo potency of these ADCs. During the course of this study, we developed a novel methodology of loading a single site with multiple payloads using an in situ generated multi-drug carrying peptidic linker that allowed us to rapidly screen for optimal conjugation sites. Using this methodology, we were able to identify a double-cysteine mutant ADC delivering four-loaded thailanstatin that was very efficacious in a gastric cancer xenograft model at 3mg/kg and was also shown to be efficacious against T-DM1 resistant and MDR1 overexpressing tumor cell lines.

Entry, Descent and Landing Systems Analysis Study: Phase 2 Report on Exploration Feed-Forward Systems

Science.gov (United States)

Dwyer Ciancolo, Alicia M.; Davis, Jody L.; Engelund, Walter C.; Komar, D. R.; Queen, Eric M.; Samareh, Jamshid A.; Way, David W.; Zang, Thomas A.; Murch, Jeff G.; Krizan, Shawn A.;

Parents and Siblings As Early Resources for Young Children's Learning in Mexican-Descent Families.

Science.gov (United States)

Perez-Granados, Deanne R.; Callanan, Maureen A.

1997-01-01

Interviews with parents from 50 Mexican-descent families revealed that parents encouraged their preschool children to ask questions about science and causal relationships; older and younger siblings learned different skills from one another; and children learned through observation and imitation. Discusses issues of "match" between home…

Kinetic comparison of older men and women during walk-to-stair descent transition.

Science.gov (United States)

Singhal, Kunal; Kim, Jemin; Casebolt, Jeffrey; Lee, Sangwoo; Han, Ki Hoon; Kwon, Young-Hoo

2014-09-01

Stair walking is one of the most challenging tasks for older adults, with women reporting higher incidence of falls. The purpose of this study was to investigate the gender differences in kinetics during stair descent transition. Twenty-eight participants (12 male and 16 female; 68.5 and 69.0 years of mean age, respectively) performed stair descent from level walking in a step-over-step manner at a self-selected speed over a custom-made three-step staircase with embedded force plates. Kinematic and force data were combined using inverse dynamics to generate kinetic data for gender comparison. The top and the first step on the staircase were chosen for analysis. Women showed a higher trail leg peak hip abductor moment (-1.0 Nm/kg), lower trail leg peak knee extensor moment and eccentric power (0.74 Nm/kg and 3.15 W/kg), and lower peak concentric power at trail leg ankle joint (1.29 W/kg) as compared to men (ppredispose women to a higher risk of fall. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of working memory and executive function on stair ascent and descent in young and older adults.

Science.gov (United States)

Gaillardin, Florence; Baudry, Stéphane

2018-06-01

This study assessed the influence of attention division, working memory and executive function on stair ascent and descent in young and older adults. Twenty young (25.5 ± 2.1 yrs) and 20 older adults (68.4 ± 5.4 yrs) ascended and descended a 3-step staircase with no simultaneous cognitive task (single-motor task) or while performing a cognitive task (dual-task condition). The cognitive task involved either 1) recalling a word list of the subject's word-span minus 2 words (SPAN-2) to assess the attention division effect, 2) a word list of subject's word-span (SPAN-O) to assess the working memory effect, or 3) recalling in alphabetical order, a word list of the subject's word-span (SPAN-A) to assess the executive function effect. Word-span corresponds to the longest string of words that can be recalled correctly. The duration of ascent and descent of stairs was used to assess the cognitive-motor interaction. Stair ascent and descent duration did not differ between age groups for the single-motor task, and was similar between single-motor task and SPAN-2 in both groups (p > 0.05). In contrast, stair ascent and descent duration increased with SPAN-O compared with SPAN-2 for both groups (p SPAN-A than SPAN-O only in older adults. Healthy aging was not associated with a decrease in the capacity to perform motor-cognitive dual tasks that involved ascending and descending of stairs when the cognitive task only required working memory. However, the decrease in dual-task performance involving executive functioning may reflect a subclinical cognitive decline in healthy older adults. Copyright © 2018 Elsevier Inc. All rights reserved.

In Vitro Evaluation of Third Generation PAMAM Dendrimer Conjugates

Directory of Open Access Journals (Sweden)

Mohammad Najlah

2017-10-01

Full Text Available The present study compares the use of high generation G3 and low generation G0 Polyamidoamine (PAMAM dendrimers as drug carriers of naproxen (NAP, a poorly water soluble drug. Naproxen was conjugated to G3 in different ratios and to G0 in a 1:1 ratio via a diethylene glycol linker. A lauroyl chain (L, a lipophilic permeability enhancer, was attached to G3 and G0 prodrugs. The G3 and G0 conjugates were more hydrophilic than naproxen as evaluated by the measurement of partitioning between 1-octanol and a phosphate buffer at pH 7.4 and pH 1.2. The unmodified surface PAMAM-NAP conjugates showed significant solubility enhancements of NAP at pH 1.2; however, with the number of NAP conjugated to G3, this was limited to 10 molecules. The lactate dehydrogenase (LDH assay indicated that the G3 dendrimer conjugates had a concentration dependent toxicity towards Caco-2 cells. Attaching naproxen to the surface of the dendrimer increased the IC50 of the resulting prodrugs towards Caco-2 cells. The lauroyl G3 conjugates showed the highest toxicity amongst the PAMAM dendrimer conjugates investigated and were significantly more toxic than the lauroyl-G0-naproxen conjugates. The permeability of naproxen across monolayers of Caco-2 cells was significantly increased by its conjugation to either G3 or G0 PAMAM dendrimers. Lauroyl-G0 conjugates displayed considerably lower cytotoxicity than G3 conjugates and may be preferable for use as a drug carrier for low soluble drugs such as naproxen.

Ti and N adatom descent pathways to the terrace from atop two-dimensional TiN/TiN(001) islands

Energy Technology Data Exchange (ETDEWEB)

Edström, D., E-mail: daned@ifm.liu.se [Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-58183 Linköping (Sweden); Sangiovanni, D.G.; Hultman, L.; Chirita, V. [Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-58183 Linköping (Sweden); Petrov, I.; Greene, J.E. [Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-58183 Linköping (Sweden); Frederick Seitz Materials Research Laboratory and the Materials Science Department, University of Illinois at Urbana-Champaign, Urbana, IL 61801 (United States)

2014-05-02

We use classical molecular dynamics and the modified embedded atom method to determine residence times and descent pathways of Ti and N adatoms on square, single-atom-high, TiN islands on TiN(001). Simulations are carried out at 1000 K, which is within the optimal range for TiN(001) epitaxial growth. Results show that the frequency of descent events, and overall adatom residence times, depend strongly on both the TiN(001) diffusion barrier for each species as well as the adatom island-edge location immediately prior to descent. Ti adatoms, with a low diffusion barrier, rapidly move toward the island periphery, via funneling, where they diffuse along upper island edges. The primary descent mechanism for Ti adatoms is via push-out/exchange with Ti island-edge atoms, a process in which the adatom replaces an island edge atom by moving down while pushing the edge atom out onto the terrace to occupy an epitaxial position along the island edge. Double push-out events are also observed for Ti adatoms descending at N corner positions. N adatoms, with a considerably higher diffusion barrier on TiN(001), require much longer times to reach island edges and, consequently, have significantly longer residence times. N adatoms are found to descend onto the terrace by direct hopping over island edges and corner atoms, as well as by concerted push-out/exchange with N atoms adjacent to Ti corners. For both adspecies, we also observe several complex adatom/island interactions, before and after descent onto the terrace, including two instances of Ti island-atom ascent onto the island surface. - Highlights: • We use classical molecular dynamics to model Ti and N adatom migration on TiN(001) islands. • N adatoms remain on islands significantly longer than Ti adatoms. • Ti adatoms descend via push-out/exchange, N adatoms primarily by direct hops. • N adatoms act as precursors for multilayer formation and surface roughening.

Ti and N adatom descent pathways to the terrace from atop two-dimensional TiN/TiN(001) islands

International Nuclear Information System (INIS)

Edström, D.; Sangiovanni, D.G.; Hultman, L.; Chirita, V.; Petrov, I.; Greene, J.E.

2014-01-01

We use classical molecular dynamics and the modified embedded atom method to determine residence times and descent pathways of Ti and N adatoms on square, single-atom-high, TiN islands on TiN(001). Simulations are carried out at 1000 K, which is within the optimal range for TiN(001) epitaxial growth. Results show that the frequency of descent events, and overall adatom residence times, depend strongly on both the TiN(001) diffusion barrier for each species as well as the adatom island-edge location immediately prior to descent. Ti adatoms, with a low diffusion barrier, rapidly move toward the island periphery, via funneling, where they diffuse along upper island edges. The primary descent mechanism for Ti adatoms is via push-out/exchange with Ti island-edge atoms, a process in which the adatom replaces an island edge atom by moving down while pushing the edge atom out onto the terrace to occupy an epitaxial position along the island edge. Double push-out events are also observed for Ti adatoms descending at N corner positions. N adatoms, with a considerably higher diffusion barrier on TiN(001), require much longer times to reach island edges and, consequently, have significantly longer residence times. N adatoms are found to descend onto the terrace by direct hopping over island edges and corner atoms, as well as by concerted push-out/exchange with N atoms adjacent to Ti corners. For both adspecies, we also observe several complex adatom/island interactions, before and after descent onto the terrace, including two instances of Ti island-atom ascent onto the island surface. - Highlights: • We use classical molecular dynamics to model Ti and N adatom migration on TiN(001) islands. • N adatoms remain on islands significantly longer than Ti adatoms. • Ti adatoms descend via push-out/exchange, N adatoms primarily by direct hops. • N adatoms act as precursors for multilayer formation and surface roughening

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

Science.gov (United States)

Gaebler, John A.; Tolson, Robert H.

2010-01-01

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

NON–DESCENT VAGINAL HYSTERECTOMY FOR BENIGN GYNAECOLOGICAL DISEASE – A PROSPECTIVE STUDY

Directory of Open Access Journals (Sweden)

Thulasi

2016-04-01

Full Text Available OBJECTIVE To assess safety and feasibility of non-descent vaginal hysterectomy for benign gynaecological disease. METHODS A prospective study was conducted at the Department of Obstetrics and Gynaecology of P K Das Institute of Medical Sciences from January 2013 to December 2013. An effort was made to perform hysterectomies vaginally in women with benign or premalignant conditions in the absence of prolapse. A suspected adnexal pathology, endometriosis, immobility of uterus, uterus size more than 16 weeks was excluded from the study. Vaginal hysterectomy was done in usual manner. In bigger size uterus, morcellation techniques like bisection, debulking, coring, myomectomy, or combination of these were used to remove the uterus. Data regarding age, parity, uterine size, estimated blood loss, length of operation, intraoperative and postoperative complications and hospital stay were recorded. RESULTS A total of 100 cases were selected for non-descent vaginal hysterectomy. Among them, 97 cases successfully underwent nondescent vaginal hysterectomy. Majority of the patients (55% were in age group 40-45 yrs. Four patients were nulligravida and eight patients had previous LSCS. Uterine size was ≤ 12 weeks in 84 cases and > 12-16 weeks in 16 cases. Commonest indication was leiomyoma of uterus (43%. Mean duration of surgery was 70±20.5 minutes. Mean blood loss was 150±65 mL. Reasons for failure to perform NDVH was difficulty in opening pouch of Douglas in two cases because of adhesions and in one case there was difficulty in reaching the fundal myoma which prevented the uterine descent. Intra–operatively, one case had bladder injury (1% that had previous 2 LSCS. Postoperatively, complications were minimal which included postoperative fever (11%, UTI (8% and vaginal cuff infection was (4%. Mean hospital stay was 3.5 days. CONCLUSION Vaginal hysterectomy is safe, feasible in most of the women requiring hysterectomy for benign conditions with less

CONJUGATED BLOCK-COPOLYMERS FOR ELECTROLUMINESCENT DIODES

NARCIS (Netherlands)

Hilberer, A; Gill, R.E; Herrema, J.K; Malliaras, G.G; Wildeman, J.; Hadziioannou, G

In this article we review results obtained in our laboratory on the design and study of new light-emitting polymers. We are interested in the synthesis and characterisation of block copolymers with regularly alternating conjugated and non conjugated sequences. The blocks giving rise to luminescence

Tetrafullerene conjugates for all-organic photovoltaics

NARCIS (Netherlands)

Fernández, G.; Sánchez, L.; Veldman, D.; Wienk, M.M.; Atienza, C.M.; Guldi, D.M.; Janssen, R.A.J.; Martin, N.

2008-01-01

The synthesis of two new tetrafullerene nanoconjugates in which four C60 units are covalently connected through different -conjugated oligomers (oligo(p-phenylene ethynylene) and oligo(p-phenylene vinylene)) is described. The photovoltaic (PV) response of these C60-based conjugates was evaluated by

Novel Aflatoxin Derivatives and Protein Conjugates

Directory of Open Access Journals (Sweden)

Reinhard Niessner

2007-03-01

Full Text Available Aflatoxins, a group of structurally related mycotoxins, are well known for their toxic and carcinogenic effects in humans and animals. Aflatoxin derivatives and protein conjugates are needed for diverse analytical applications. This work describes a reliable and fast synthesis of novel aflatoxin derivatives, purification by preparative HPLC and characterisation by ESI-MS and one- and two-dimensional NMR. Novel aflatoxin bovine serum albumin conjugates were prepared and characterised by UV absorption and MALDI-MS. These aflatoxin protein conjugates are potentially interesting as immunogens for the generation of aflatoxin selective antibodies with novel specificities.

Structure Property Relationships in Organic Conjugated Systems

OpenAIRE

O'Neill, Luke

2008-01-01

A series of pi(п) conjugated oligomers containing 1 to 6 monomer units were studied by absorption and photoluminescence spectroscopies. The results are discussed and examined with regard to the variation of the optical properties with the increase of effective conjugation length. It was found that there was a linear relationship between the positioning of the absorption and photoluminescence maxima plotted against inverse conjugation length. The relationships are in good agreement with the si...

The influence of ALN-Al gradient material gradient index on ballistic performance

International Nuclear Information System (INIS)

Wang Youcong; Liu Qiwen; Li Yao; Shen Qiang

2013-01-01

Ballistic performance of the gradient material is superior to laminated material, and gradient materials have different gradient types. Using ls-dyna to simulate the ballistic performance of ALN-AL gradient target plates which contain three gradient index (b = 1, b = 0.5, b = 2). Through Hopkinson bar numerical simulation to the target plate materials, we obtained the reflection stress wave and transmission stress wave state of gradient material to get the best gradient index. The internal stress state of gradient material is simulated by amplification processing of the target plate model. When the gradient index b is equal to 1, the gradient target plate is best of all.

Sources and Bioactive Properties of Conjugated Dietary Fatty Acids.

Science.gov (United States)

Hennessy, Alan A; Ross, Paul R; Fitzgerald, Gerald F; Stanton, Catherine

2016-04-01

The group of conjugated fatty acids known as conjugated linoleic acid (CLA) isomers have been extensively studied with regard to their bioactive potential in treating some of the most prominent human health malignancies. However, CLA isomers are not the only group of potentially bioactive conjugated fatty acids currently undergoing study. In this regard, isomers of conjugated α-linolenic acid, conjugated nonadecadienoic acid and conjugated eicosapentaenoic acid, to name but a few, have undergone experimental assessment. These studies have indicated many of these conjugated fatty acid isomers commonly possess anti-carcinogenic, anti-adipogenic, anti-inflammatory and immune modulating properties, a number of which will be discussed in this review. The mechanisms through which these bioactivities are mediated have not yet been fully elucidated. However, existing evidence indicates that these fatty acids may play a role in modulating the expression of several oncogenes, cell cycle regulators, and genes associated with energy metabolism. Despite such bioactive potential, interest in these conjugated fatty acids has remained low relative to the CLA isomers. This may be partly attributed to the relatively recent emergence of these fatty acids as bioactives, but also due to a lack of awareness regarding sources from which they can be produced. In this review, we will also highlight the common sources of these conjugated fatty acids, including plants, algae, microbes and chemosynthesis.

Preparation and immunological properties of procaine-protein conjugates

International Nuclear Information System (INIS)

Liakopoulou, A.

1981-01-01

Procaine was conjugated to BSA and rat and rabbit Gf using the carbodiimide method and 14 C-procaine as tracer. The composition of the conjugates could be varied depending on the time of incubation and the concentration of procaine in the reaction mixtures. Procaine-BSA conjugates were soluble in water or saline. However, procaine conjugates to rat or rabbit Gf were not readily soluble in saline. These conjugates were good for immunization purposes, but it was cumbersome to work with them when clear solutions were needed, as in the immunochemical procedures used in this study. The immunological properties of the conjugates were studied in rats and rabbits. Rats responded with production of IgGa and precipitating antibodies to the procaine group, but IgE antibodies to the immunogen could not be detected. Furthermore, precipitating antibodies towards the procaine group were raised in rabbits. When BSA was the protein carrier, antibodies to the carrier molecule were also detected in both rats and rabbits. The conjugates of procaine to rat or rabbit Gf did not elicit antibody response to the carrier molecule when used in the homologous species. Hapten inhibition studies suggested that, in the rabbit, antibodies were also produced with specificity directed towards the molecular configuration of the hapten-carrier bond. (author)

IRDye78 Conjugates for Near-Infrared Fluorescence Imaging

Directory of Open Access Journals (Sweden)

Atif Zaheer

2002-10-01

Full Text Available The detection of human malignancies by near-infrared (NIR fluorescence will require the conjugation of cancer-specific ligands to NIR fluorophores that have optimal photoproperties and pharmacokinetics. IRDye78, a tetra-sulfonated heptamethine indocyanine NIR fluorophore, meets most of the criteria for an in vivo imaging agent, and is available as an N-hydroxysuccinimide ester for conjugation to low-molecular-weight ligands. However, IRDye78 has a high charge-to-mass ratio, complicating purification of conjugates. It also has a potentially labile linkage between fluorophore and ligand. We have developed an ion-pairing purification strategy for IRDye78 that can be performed with a standard C18 column under neutral conditions, thus preserving the stability of fluorophore, ligand, and conjugate. By employing parallel evaporative light scatter and absorbance detectors, all reactants and products are identified, and conjugate purity is maximized. We describe reversible and irreversible conversions of IRDye78 that can occur during sample purification, and describe methods for preserving conjugate stability. Using seven ligands, spanning several classes of small molecules and peptides (neutral, charged, and/or hydrophobic, we illustrate the robustness of these methods, and confirm that IRDye78 conjugates so purified retain bioactivity and permit NIR fluorescence imaging of specific targets.

Gradient waveform synthesis for magnetic propulsion using MRI gradient coils

International Nuclear Information System (INIS)

Han, B H; Lee, S Y; Park, S

2008-01-01

Navigating an untethered micro device in a living subject is of great interest for both diagnostic and therapeutic applications. Magnetic propulsion of an untethered device carrying a magnetic core in it is one of the promising methods to navigate the device. MRI gradients coils are thought to be suitable for navigating the device since they are capable of magnetic propulsion in any direction while providing magnetic resonance images. For precise navigation of the device, especially in the peripheral region of the gradient coils, the concomitant gradient fields, as well as the linear gradient fields in the main magnetic field direction, should be considered in driving the gradient coils. For simple gradient coil configurations, the Maxwell coil in the z-direction and the Golay coil in the x- and y-directions, we have calculated the magnetic force fields, which are not necessarily the same as the conventional linear gradient fields of MRI. Using the calculated magnetic force fields, we have synthesized gradient waveforms to navigate the device along a desired path

Doxorubicin conjugated to D-alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS): conjugation chemistry, characterization, in vitro and in vivo evaluation.

Science.gov (United States)

Cao, Na; Feng, Si-Shen

2008-10-01

To develop a polymer-anticancer drug conjugate, D-alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS) was employed as a carrier of doxorubicin (DOX) to enhance its therapeutic effects and reduce its side effects. Doxorubicin was chemically conjugated to TPGS. The molecular structure, drug loading efficiency, drug release kinetics and stability of the conjugate were characterized. The cellular uptake, intracellular distribution, and cytotoxicity were accessed by using MCF-7 breast cancer cells and C6 glioma cells as in vitro cell model. The conjugate showed higher cellular uptake efficiency and broader distribution within the cells. Judged by IC(50), the conjugate was found 31.8, 69.6, 84.1% more effective with MCF-7 cells and 43.9, 87.7, 42.2% more effective with C6 cells than the parent drug after 24, 48, 72 h culture, respectively. The in vivo pharmacokinetics and biodistribution were investigated after an i.v. administration at 5 mg DOX/kg body weight in rats. Promisingly, 4.5-fold increase in the half-life and 24-fold increase in the area-under-the-curve (AUC) of DOX were achieved for the TPGS-DOX conjugate compared with the free DOX. The drug level in heart, gastric and intestine was significantly reduced, which is an indication of reduced side effects. Our TPGS-DOX conjugate showed great potential to be a prodrug of higher therapeutic effects and fewer side effects than DOX itself.

Bis-polymer lipid-peptide conjugates and nanoparticles thereof